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+610a4451423ad7f82916c736cd8adb86a5a64c59,A Survey on Search Based Face Annotation Using Weakly Labelled Facial Images,"Volume 4, Issue 11, November 2014                                  ISSN: 2277 128X
+International Journal of Advanced Research in
+Computer Science and Software Engineering
+Research Paper
+Available online at: www.ijarcsse.com
+A Survey on Search Based Face Annotation Using Weakly
+Labelled Facial Images
+Shital A. Shinde*, Prof. Archana Chaugule
+Department of Computer Engg, DYPIET Pimpri,
+Savitri Bai Phule Pune University, Maharashtra India"
+61542874efb0b4c125389793d8131f9f99995671,Fair comparison of skin detection approaches on publicly available datasets,"Fair comparison of skin detection approaches on publicly available datasets
+Alessandra Luminia and Loris Nannib
+. DISI, Università di Bologna, Via Sacchi 3, 47521 Cesena, Italy.
+DEI - University of Padova, Via Gradenigo, 6 - 35131- Padova, Italy."
+6180bc0816b1776ca4b32ced8ea45c3c9ce56b47,Fast Randomized Algorithms for Convex Optimization and Statistical Estimation,"Fast Randomized Algorithms for Convex Optimization and
+Statistical Estimation
+Mert Pilanci
+Electrical Engineering and Computer Sciences
+University of California at Berkeley
+Technical Report No. UCB/EECS-2016-147
+http://www.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-147.html
+August 14, 2016"
+61f04606528ecf4a42b49e8ac2add2e9f92c0def,Deep Deformation Network for Object Landmark Localization,"Deep Deformation Network for Object Landmark
+Localization
+Xiang Yu, Feng Zhou and Manmohan Chandraker
+NEC Laboratories America, Department of Media Analytics"
+614a7c42aae8946c7ad4c36b53290860f6256441,Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks,"Joint Face Detection and Alignment using
+Multi-task Cascaded Convolutional Networks
+Kaipeng Zhang, Zhanpeng Zhang, Zhifeng Li, Senior Member, IEEE, and Yu Qiao, Senior Member, IEEE"
+0d88ab0250748410a1bc990b67ab2efb370ade5d,Error handling in multimodal biometric systems using reliability measures,"Author(s) :
+ERROR HANDLING IN MULTIMODAL BIOMETRIC SYSTEMS USING
+RELIABILITY MEASURES  (ThuPmOR6)
+(EPFL, Switzerland)
+(EPFL, Switzerland)
+(EPFL, Switzerland)
+(EPFL, Switzerland)
+Krzysztof Kryszczuk
+Jonas Richiardi
+Plamen Prodanov
+Andrzej Drygajlo"
+0d538084f664b4b7c0e11899d08da31aead87c32,Deformable Part Descriptors for Fine-Grained Recognition and Attribute Prediction,"Deformable Part Descriptors for
+Fine-grained Recognition and Attribute Prediction
+Ning Zhang1
+Ryan Farrell1,2
+Forrest Iandola1
+ICSI / UC Berkeley 2Brigham Young University
+Trevor Darrell1"
+0dccc881cb9b474186a01fd60eb3a3e061fa6546,Effective face frontalization in unconstrained images,"Effective Face Frontalization in Unconstrained Images
+Tal Hassner1, Shai Harel1 †, Eran Paz1 † and Roee Enbar2
+The open University of Israel. 2Adience.
+Figure 1: Frontalized faces. Top: Input photos; bottom: our frontalizations,
+obtained without estimating 3D facial shapes.
+“Frontalization” is the process of synthesizing frontal facing views of faces
+ppearing in single unconstrained photos. Recent reports have suggested
+that this process may substantially boost the performance of face recogni-
+tion systems. This, by transforming the challenging problem of recognizing
+faces viewed from unconstrained viewpoints to the easier problem of rec-
+ognizing faces in constrained, forward facing poses. Previous frontalization
+methods did this by attempting to approximate 3D facial shapes for each
+query image. We observe that 3D face shape estimation from unconstrained
+photos may be a harder problem than frontalization and can potentially in-
+troduce facial misalignments. Instead, we explore the simpler approach of
+using a single, unmodiﬁed, 3D surface as an approximation to the shape of
+ll input faces. We show that this leads to a straightforward, efﬁcient and
+easy to implement method for frontalization. More importantly, it produces
+esthetic new frontal views and is surprisingly effective when used for face
+recognition and gender estimation."
+0d6b28691e1aa2a17ffaa98b9b38ac3140fb3306,Review of Perceptual Resemblance of Local Plastic Surgery Facial Images using Near Sets,"Review of Perceptual Resemblance of Local
+Plastic Surgery Facial Images using Near Sets
+Prachi V. Wagde1, Roshni Khedgaonkar2
+,2 Department of Computer Technology,
+YCCE Nagpur, India"
+0d3882b22da23497e5de8b7750b71f3a4b0aac6b,Context is routinely encoded during emotion perception.,"Research Article
+Context Is Routinely Encoded
+During Emotion Perception
+1(4) 595 –599
+© The Author(s) 2010
+Reprints and permission:
+sagepub.com/journalsPermissions.nav
+DOI: 10.1177/0956797610363547
+http://pss.sagepub.com
+Lisa Feldman Barrett1,2,3 and Elizabeth A. Kensinger1,3
+Boston College; 2Psychiatric Neuroimaging Program, Massachusetts General Hospital, Harvard Medical School; and 3Athinoula A. Martinos
+Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School"
+0d760e7d762fa449737ad51431f3ff938d6803fe,LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded Systems,"LCDet: Low-Complexity Fully-Convolutional Neural Networks for
+Object Detection in Embedded Systems
+Subarna Tripathi
+UC San Diego ∗
+Gokce Dane
+Qualcomm Inc.
+Byeongkeun Kang
+UC San Diego
+Vasudev Bhaskaran
+Qualcomm Inc.
+Truong Nguyen
+UC San Diego"
+0dd72887465046b0f8fc655793c6eaaac9c03a3d,Real-Time Head Orientation from a Monocular Camera Using Deep Neural Network,"Real-time Head Orientation from a Monocular
+Camera using Deep Neural Network
+Byungtae Ahn, Jaesik Park, and In So Kweon
+KAIST, Republic of Korea"
+0d33b6c8b4d1a3cb6d669b4b8c11c2a54c203d1a,Detection and Tracking of Faces in Videos: A Review of Related Work,"Detection and Tracking of Faces in Videos: A Review
+© 2016 IJEDR | Volume 4, Issue 2 | ISSN: 2321-9939
+of Related Work
+Seema Saini, 2 Parminder Sandal
+Student, 2Assistant Professor
+, 2Dept. of Electronics & Comm., S S I E T, Punjab, India
+________________________________________________________________________________________________________"
+0da4c3d898ca2fff9e549d18f513f4898e960aca,The Headscarf Effect Revisited: Further Evidence for a Culture-Based Internal Face Processing Advantage.,"Wang, Y., Thomas, J., Weissgerber, S. C., Kazemini, S., Ul-Haq, I., &
+Quadflieg, S. (2015). The Headscarf Effect Revisited: Further Evidence for a
+36. 10.1068/p7940
+Peer reviewed version
+Link to published version (if available):
+0.1068/p7940
+Link to publication record in Explore Bristol Research
+PDF-document
+University of Bristol - Explore Bristol Research
+General rights
+This document is made available in accordance with publisher policies. Please cite only the published
+version using the reference above. Full terms of use are available:
+http://www.bristol.ac.uk/pure/about/ebr-terms.html
+Take down policy
+Explore Bristol Research is a digital archive and the intention is that deposited content should not be
+removed. However, if you believe that this version of the work breaches copyright law please contact
+nd include the following information in your message:
+• Your contact details
+• Bibliographic details for the item, including a URL
+• An outline of the nature of the complaint"
+956317de62bd3024d4ea5a62effe8d6623a64e53,Lighting Analysis and Texture Modification of 3D Human Face Scans,"Lighting Analysis and Texture Modification of 3D Human
+Face Scans
+Author
+Zhang, Paul, Zhao, Sanqiang, Gao, Yongsheng
+Published
+Conference Title
+Digital Image Computing Techniques and Applications
+https://doi.org/10.1109/DICTA.2007.4426825
+Copyright Statement
+© 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/
+republish this material for advertising or promotional purposes or for creating new collective
+works for resale or redistribution to servers or lists, or to reuse any copyrighted component of
+this work in other works must be obtained from the IEEE.
+Downloaded from
+http://hdl.handle.net/10072/17889
+Link to published version
+http://www.ieee.org/
+Griffith Research Online
+https://research-repository.griffith.edu.au"
+959bcb16afdf303c34a8bfc11e9fcc9d40d76b1c,Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial Networks,"Temporal Coherency based Criteria for Predicting
+Video Frames using Deep Multi-stage Generative
+Adversarial Networks
+Prateep Bhattacharjee1, Sukhendu Das2
+Visualization and Perception Laboratory
+Department of Computer Science and Engineering
+Indian Institute of Technology Madras, Chennai, India"
+951f21a5671a4cd14b1ef1728dfe305bda72366f,Use of l2/3-norm Sparse Representation for Facial Expression Recognition,"International Journal of Science and Research (IJSR)
+ISSN (Online): 2319-7064
+Impact Factor (2012): 3.358
+Use of ℓ2/3-norm Sparse Representation for Facial
+Expression Recognition
+Sandeep Rangari1, Sandeep Gonnade2
+MATS University, MATS School of Engineering and Technology, Arang, Raipur, India
+MATS University, MATS School of Engineering and Technology, Arang, Raipur, India
+three
+to  discriminate
+represents  emotion,"
+9547a7bce2b85ef159b2d7c1b73dea82827a449f,Facial expression recognition using Gabor motion energy filters,"Facial Expression Recognition Using Gabor Motion Energy Filters
+Tingfan Wu
+Dept. Computer Science Engineering
+UC San Diego
+Marian S. Bartlett
+Javier R. Movellan
+Institute for Neural Computation
+UC San Diego"
+9513503867b29b10223f17c86e47034371b6eb4f,Comparison of Optimisation Algorithms for Deformable Template Matching,"Comparison of optimisation algorithms for
+deformable template matching
+Vasileios Zografos
+Link¨oping University, Computer Vision Laboratory
+ISY, SE-581 83 Link¨oping, SWEDEN"
+956c634343e49319a5e3cba4f2bd2360bdcbc075,A novel incremental principal component analysis and its application for face recognition,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 36, NO. 4, AUGUST 2006
+A Novel Incremental Principal Component Analysis
+nd Its Application for Face Recognition
+Haitao Zhao, Pong Chi Yuen, Member, IEEE, and James T. Kwok, Member, IEEE"
+95ea564bd983129ddb5535a6741e72bb1162c779,Multi-Task Learning by Deep Collaboration and Application in Facial Landmark Detection,"Multi-Task Learning by Deep Collaboration and
+Application in Facial Landmark Detection
+Ludovic Trottier
+Philippe Giguère
+Brahim Chaib-draa
+Laval University, Québec, Canada"
+958c599a6f01678513849637bec5dc5dba592394,Generalized Zero-Shot Learning for Action Recognition with Web-Scale Video Data,"Noname manuscript No.
+(will be inserted by the editor)
+Generalized Zero-Shot Learning for Action
+Recognition with Web-Scale Video Data
+Kun Liu · Wu Liu · Huadong Ma ·
+Wenbing Huang · Xiongxiong Dong
+Received: date / Accepted: date"
+59fc69b3bc4759eef1347161e1248e886702f8f7,Final Report of Final Year Project HKU-Face : A Large Scale Dataset for Deep Face Recognition,"Final Report of Final Year Project
+HKU-Face: A Large Scale Dataset for
+Deep Face Recognition
+Haoyu Li
+035141841
+COMP4801 Final Year Project
+Project Code: 17007"
+59bfeac0635d3f1f4891106ae0262b81841b06e4,Face Verification Using the LARK Face Representation,"Face Veriﬁcation Using the LARK Face
+Representation
+Hae Jong Seo, Student Member, IEEE, Peyman Milanfar, Fellow, IEEE,"
+59efb1ac77c59abc8613830787d767100387c680,DIF : Dataset of Intoxicated Faces for Drunk Person Identification,"DIF : Dataset of Intoxicated Faces for Drunk Person
+Identification
+Devendra Pratap Yadav
+Indian Institute of Technology Ropar
+Abhinav Dhall
+Indian Institute of Technology Ropar"
+59eefa01c067a33a0b9bad31c882e2710748ea24,Fast Landmark Localization with 3D Component Reconstruction and CNN for Cross-Pose Recognition,"IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
+Fast Landmark Localization
+with 3D Component Reconstruction and CNN for
+Cross-Pose Recognition
+Gee-Sern (Jison) Hsu, Hung-Cheng Shie, Cheng-Hua Hsieh"
+59d225486161b43b7bf6919b4a4b4113eb50f039,Complex Event Recognition from Images with Few Training Examples,"Complex Event Recognition from Images with Few Training Examples
+Unaiza Ahsan∗
+Chen Sun∗∗
+James Hays∗
+Irfan Essa∗
+*Georgia Institute of Technology
+**University of Southern California1"
+5945464d47549e8dcaec37ad41471aa70001907f,Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos,"Noname manuscript No.
+(will be inserted by the editor)
+Every Moment Counts: Dense Detailed Labeling of Actions in Complex
+Videos
+Serena Yeung · Olga Russakovsky · Ning Jin · Mykhaylo Andriluka · Greg Mori ·
+Li Fei-Fei
+Received: date / Accepted: date"
+59c9d416f7b3d33141cc94567925a447d0662d80,Matrix factorization over max-times algebra for data mining,"Universität des Saarlandes
+Max-Planck-Institut für Informatik
+Matrix factorization over max-times
+lgebra for data mining
+Masterarbeit im Fach Informatik
+Master’s Thesis in Computer Science
+von / by
+Sanjar Karaev
+ngefertigt unter der Leitung von / supervised by
+Dr. Pauli Miettinen
+egutachtet von / reviewers
+Dr. Pauli Miettinen
+Prof. Gerhard Weikum
+November 2013
+UNIVERSITASSARAVIENSIS"
+59bece468ed98397d54865715f40af30221aa08c,Deformable part-based robust face detection under occlusion by using face decomposition into face components,"Deformable Part-based Robust Face Detection
+under Occlusion by Using Face Decomposition
+into Face Components
+Darijan Marčetić, Slobodan Ribarić
+University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia
+{darijan.marcetic,"
+59a35b63cf845ebf0ba31c290423e24eb822d245,The FaceSketchID System: Matching Facial Composites to Mugshots,"The FaceSketchID System: Matching Facial
+Composites to Mugshots
+Scott J. Klum, Student Member, IEEE, Hu Han, Member, IEEE, Brendan F. Klare, Member, IEEE,
+nd Anil K. Jain, Fellow, IEEE
+tedious, and may not"
+59f325e63f21b95d2b4e2700c461f0136aecc171,Kernel sparse representation with local patterns for face recognition,"978-1-4577-1302-6/11/$26.00 ©2011 IEEE
+FOR FACE RECOGNITION
+. INTRODUCTION"
+59031a35b0727925f8c47c3b2194224323489d68,Sparse Variation Dictionary Learning for Face Recognition with a Single Training Sample per Person,"Sparse Variation Dictionary Learning for Face Recognition with A Single
+Training Sample Per Person
+Meng Yang, Luc Van Gool
+ETH Zurich
+Switzerland"
+926c67a611824bc5ba67db11db9c05626e79de96,Enhancing Bilinear Subspace Learning by Element Rearrangement,"Enhancing Bilinear Subspace Learning
+y Element Rearrangement
+Dong Xu, Shuicheng Yan, Stephen Lin,
+Thomas S. Huang, and
+Shih-Fu Chang"
+923ede53b0842619831e94c7150e0fc4104e62f7,Masked correlation filters for partially occluded face recognition,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE
+ICASSP 2016"
+92b61b09d2eed4937058d0f9494d9efeddc39002,BoxCars: Improving Vehicle Fine-Grained Recognition using 3D Bounding Boxes in Traffic Surveillance,"Under review in IJCV manuscript No.
+(will be inserted by the editor)
+BoxCars: Improving Vehicle Fine-Grained Recognition using
+D Bounding Boxes in Traf‌f‌ic Surveillance
+Jakub Sochor · Jakub ˇSpaˇnhel · Adam Herout
+Received: date / Accepted: date"
+920a92900fbff22fdaaef4b128ca3ca8e8d54c3e,Learning Pattern Transformation Manifolds with Parametric Atom Selection,"LEARNING PATTERN TRANSFORMATION MANIFOLDS WITH PARAMETRIC ATOM
+SELECTION
+Elif Vural and Pascal Frossard
+Ecole Polytechnique F´ed´erale de Lausanne (EPFL)
+Signal Processing Laboratory (LTS4)
+Switzerland-1015 Lausanne"
+9207671d9e2b668c065e06d9f58f597601039e5e,Face Detection Using a 3D Model on Face Keypoints,"Face Detection Using a 3D Model on
+Face Keypoints
+Adrian Barbu, Gary Gramajo"
+9282239846d79a29392aa71fc24880651826af72,Classification of extreme facial events in sign language videos,"Antonakos et al. EURASIP Journal on Image and Video Processing 2014, 2014:14
+http://jivp.eurasipjournals.com/content/2014/1/14
+RESEARCH
+Open Access
+Classification of extreme facial events in sign
+language videos
+Epameinondas Antonakos1,2*, Vassilis Pitsikalis1 and Petros Maragos1"
+92115b620c7f653c847f43b6c4ff0470c8e55dab,Training Deformable Object Models for Human Detection Based on Alignment and Clustering,"Training Deformable Object Models for Human
+Detection Based on Alignment and Clustering
+Benjamin Drayer and Thomas Brox
+Department of Computer Science,
+Centre of Biological Signalling Studies (BIOSS),
+University of Freiburg, Germany"
+928b8eb47288a05611c140d02441660277a7ed54,Exploiting Images for Video Recognition with Hierarchical Generative Adversarial Networks,"Exploiting Images for Video Recognition with Hierarchical Generative
+Adversarial Networks
+Feiwu Yu1, Xinxiao Wu1 ∗, Yuchao Sun1, Lixin Duan2
+Beijing Laboratory of Intelligent Information Technology, School of Computer Science,
+Big Data Research Center, University of Electronic Science and Technology of China
+Beijing Institute of Technology"
+92c2dd6b3ac9227fce0a960093ca30678bceb364,On Color Texture Normalization for Active Appearance Models,"Provided by the author(s) and NUI Galway in accordance with publisher policies. Please cite the published
+version when available.
+Title
+On color texture normalization for active appearance models
+Author(s)
+Ionita, Mircea C.; Corcoran, Peter M.; Buzuloiu, Vasile
+Publication
+009-05-12
+Publication
+Information
+Ionita, M. C., Corcoran, P., & Buzuloiu, V. (2009). On Color
+Texture Normalization for Active Appearance Models. Image
+Processing, IEEE Transactions on, 18(6), 1372-1378.
+Publisher
+Link to
+publisher's
+version
+http://dx.doi.org/10.1109/TIP.2009.2017163
+Item record
+http://hdl.handle.net/10379/1350"
+927ba64123bd4a8a31163956b3d1765eb61e4426,Customer satisfaction measuring based on the most significant facial emotion,"Customer satisfaction measuring based on the most
+significant facial emotion
+Mariem Slim, Rostom Kachouri, Ahmed Atitallah
+To cite this version:
+Mariem Slim, Rostom Kachouri, Ahmed Atitallah. Customer satisfaction measuring based on the
+most significant facial emotion. 15th IEEE International Multi-Conference on Systems, Signals
+Devices (SSD 2018), Mar 2018, Hammamet, Tunisia. <hal-01790317>
+HAL Id: hal-01790317
+https://hal-upec-upem.archives-ouvertes.fr/hal-01790317
+Submitted on 11 May 2018
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entific research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destinée au dépôt et à la diffusion de documents
+scientifiques de niveau recherche, publiés ou non,
+émanant des établissements d’enseignement et de"
+927ad0dceacce2bb482b96f42f2fe2ad1873f37a,Interest-Point based Face Recognition System,"Interest-Point based Face Recognition System
+Interest-Point based Face Recognition System
+Cesar Fernandez and Maria Asuncion Vicente
+Miguel Hernandez University
+Spain
+. Introduction
+Among  all  applications  of  face  recognition  systems,  surveillance  is  one  of  the  most
+hallenging ones. In such an application, the goal is to detect known criminals in crowded
+environments, like airports or train stations. Some attempts have been made, like those of
+Tokio (Engadget, 2006) or Mainz (Deutsche Welle, 2006), with limited success.
+The first task to be carried out in an automatic surveillance system involves the detection of
+ll the faces in the images taken by the video cameras. Current face detection algorithms are
+highly reliable and thus, they will not be the focus of our work. Some of the best performing
+examples are the Viola-Jones algorithm (Viola & Jones, 2004) or the Schneiderman-Kanade
+lgorithm (Schneiderman & Kanade, 2000).
+The second task to be carried out involves the comparison of all detected faces among the
+database of known criminals. The ideal behaviour of an automatic system performing this
+task  would  be  to  get  a  100%  correct  identification  rate,  but  this  behaviour  is  far  from  the
+apabilities  of  current  face  recognition  algorithms.  Assuming  that  there  will  be  false
+identifications,  supervised  surveillance  systems  seem  to  be  the  most  realistic  option:  the"
+929bd1d11d4f9cbc638779fbaf958f0efb82e603,"Improving the Performance of Facial Expression Recognition Using Dynamic, Subtle and Regional Features","This is the author’s version of a work that was submitted/accepted for pub-
+lication in the following source:
+Zhang, Ligang & Tjondronegoro, Dian W. (2010) Improving the perfor-
+mance of facial expression recognition using dynamic, subtle and regional
+features.
+In Kok, WaiWong, B. Sumudu, U. Mendis, & Abdesselam ,
+Bouzerdoum (Eds.) Neural Information Processing. Models and Applica-
+tions, Lecture Notes in Computer Science, Sydney, N.S.W, pp. 582-589.
+This ﬁle was downloaded from: http://eprints.qut.edu.au/43788/
+(cid:13) Copyright 2010 Springer-Verlag
+Conference proceedings published, by Springer Verlag, will be available
+via Lecture Notes in Computer Science http://www.springer.de/comp/lncs/
+Notice: Changes introduced as a result of publishing processes such as
+opy-editing and formatting may not be reflected in this document. For a
+deﬁnitive version of this work, please refer to the published source:
+http://dx.doi.org/10.1007/978-3-642-17534-3_72"
+0cb7e4c2f6355c73bfc8e6d5cdfad26f3fde0baf,F Acial E Xpression R Ecognition Based on Wapa and Oepa F Ast Ica,"International Journal of Artificial Intelligence & Applications (IJAIA), Vol. 5, No. 3, May 2014
+FACIAL EXPRESSION RECOGNITION BASED ON
+WAPA AND OEPA FASTICA
+Humayra Binte Ali1 and David M W Powers2
+Computer Science, Engineering and Mathematics School, Flinders University, Australia
+Computer Science, Engineering and Mathematics School, Flinders University, Australia"
+0c8a0a81481ceb304bd7796e12f5d5fa869ee448,A Spatial Regularization of LDA for Face Recognition,"International Journal of Fuzzy Logic and Intelligent Systems, vol. 10, no. 2, June 2010, pp. 95-100
+A Spatial Regularization of LDA for Face Recognition
+Lae-Jeong Park
+Department of Electronics Engineering, Gangnung-Wonju National University
+23 Chibyun-Dong, Kangnung, 210-702, Korea
+Tel : +82-33-640-2389, Fax : +82-33-646-0740, E-mail :"
+0c36c988acc9ec239953ff1b3931799af388ef70,Face Detection Using Improved Faster RCNN,"Face Detection Using Improved Faster RCNN
+Changzheng Zhang, Xiang Xu, Dandan Tu*
+Huawei Cloud BU, China
+{zhangzhangzheng, xuxiang12,
+Figure1.Face detection results of FDNet1.0"
+0c5ddfa02982dcad47704888b271997c4de0674b,Model-driven and Data-driven Approaches for some Object Recognition Problems,
+0c069a870367b54dd06d0da63b1e3a900a257298,Weakly Supervised Learning of Foreground-Background Segmentation Using Masked RBMs,"Author manuscript, published in ""ICANN 2011 - International Conference on Artificial Neural Networks (2011)"""
+0c75c7c54eec85e962b1720755381cdca3f57dfb,Face Landmark Fitting via Optimized Part Mixtures and Cascaded Deformable Model,"Face Landmark Fitting via Optimized Part
+Mixtures and Cascaded Deformable Model
+Xiang Yu, Member, IEEE, Junzhou Huang, Member, IEEE,
+Shaoting Zhang, Senior Member, IEEE, and Dimitris N. Metaxas, Fellow, IEEE"
+0ca36ecaf4015ca4095e07f0302d28a5d9424254,Improving Bag-of-Visual-Words Towards Effective Facial Expressive Image Classification,"Improving Bag-of-Visual-Words Towards Effective Facial Expressive
+Image Classiﬁcation
+Dawood Al Chanti1 and Alice Caplier1
+Univ. Grenoble Alpes, CNRS, Grenoble INP∗ , GIPSA-lab, 38000 Grenoble, France
+Keywords:
+BoVW, k-means++, Relative Conjunction Matrix, SIFT, Spatial Pyramids, TF.IDF."
+0cfca73806f443188632266513bac6aaf6923fa8,Predictive Uncertainty in Large Scale Classification using Dropout - Stochastic Gradient Hamiltonian Monte Carlo,"Predictive Uncertainty in Large Scale Classiﬁcation
+using Dropout - Stochastic Gradient Hamiltonian
+Monte Carlo.
+Vergara, Diego∗1, Hern´andez, Sergio∗2, Valdenegro-Toro, Mat´ıas∗∗3 and Jorquera, Felipe∗4.
+Laboratorio de Procesamiento de Informaci´on Geoespacial, Universidad Cat´olica del Maule, Chile.
+German Research Centre for Artiﬁcial Intelligence, Bremen, Germany.
+Email:"
+0c3f7272a68c8e0aa6b92d132d1bf8541c062141,Kruskal-Wallis-Based Computationally Efficient Feature Selection for Face Recognition,"Hindawi Publishing Corporation
+e Scientiﬁc World Journal
+Volume 2014, Article ID 672630, 6 pages
+http://dx.doi.org/10.1155/2014/672630
+Research Article
+Kruskal-Wallis-Based Computationally Efficient Feature
+Selection for Face Recognition
+Sajid Ali Khan,1,2 Ayyaz Hussain,3 Abdul Basit,1 and Sheeraz Akram1
+Department of Software Engineering, Foundation University, Rawalpindi 46000, Pakistan
+Department of Computer Science, Shaheed Zulfikar Ali Bhutto Institute of Science and Technology Islamabad,
+Islamabad 44000, Pakistan
+Department of Computer Science and Software Engineering, International Islamic University, Islamabad 44000, Pakistan
+Correspondence should be addressed to Sajid Ali Khan;
+Received 5 December 2013; Accepted 10 February 2014; Published 21 May 2014
+Academic Editors: S. Balochian, V. Bhatnagar, and Y. Zhang
+Copyright © 2014 Sajid Ali Khan et al. This is an open access article distributed under the Creative Commons Attribution License,
+which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
+Face recognition in today’s technological world, and face recognition applications attain much more importance. Most of the
+existing work used frontal face images to classify face image. However these techniques fail when applied on real world face images.
+The proposed technique effectively extracts the prominent facial features. Most of the features are redundant and do not contribute"
+0c5afb209b647456e99ce42a6d9d177764f9a0dd,Recognizing Action Units for Facial Expression Analysis,"Recognizing Action Units for
+Facial Expression Analysis
+Ying-li Tian, Member, IEEE, Takeo Kanade, Fellow, IEEE, and Jeffrey F. Cohn, Member, IEEE"
+0c377fcbc3bbd35386b6ed4768beda7b5111eec6,A Unified Probabilistic Framework for Spontaneous Facial Action Modeling and Understanding,"A Unified Probabilistic Framework
+for Spontaneous Facial Action Modeling
+nd Understanding
+Yan Tong, Member, IEEE, Jixu Chen, Student Member, IEEE, and Qiang Ji, Senior Member, IEEE"
+0cb2dd5f178e3a297a0c33068961018659d0f443,IARPA Janus Benchmark-B Face Dataset,"© 2017 Noblis, Inc.  IARPA Janus Benchmark-B Face Dataset Cameron Whitelam, Emma Taborsky*, Austin Blanton, Brianna Maze*, Jocelyn Adams*, Tim Miller*, Nathan Kalka*, Anil K. Jain**, James A. Duncan*, Kristen Allen, Jordan Cheney*, Patrick Grother***  Noblis* Michigan State University** NIST*** 21 July 2017"
+0cd8895b4a8f16618686f622522726991ca2a324,Discrete Choice Models for Static Facial Expression Recognition,"Discrete Choice Models for Static Facial Expression
+Recognition
+Gianluca Antonini1, Matteo Sorci1, Michel Bierlaire2, and Jean-Philippe Thiran1
+Ecole Polytechnique Federale de Lausanne, Signal Processing Institute
+Ecole Polytechnique Federale de Lausanne, Operation Research Group
+Ecublens, 1015 Lausanne, Switzerland
+Ecublens, 1015 Lausanne, Switzerland"
+0cf7da0df64557a4774100f6fde898bc4a3c4840,Shape matching and object recognition using low distortion correspondences,"Shape Matching and Object Recognition using Low Distortion Correspondences
+Alexander C. Berg Tamara L. Berg
+Jitendra Malik
+Department of Electrical Engineering and Computer Science
+U.C. Berkeley"
+0cbe059c181278a373292a6af1667c54911e7925,'Owl' and 'Lizard': patterns of head pose and eye pose in driver gaze classification,"Owl and Lizard: Patterns of Head Pose and Eye
+Pose in Driver Gaze Classiﬁcation
+Lex Fridman1, Joonbum Lee1, Bryan Reimer1, and Trent Victor2
+Massachusetts Institute of Technology (MIT)
+Chalmers University of Technology, SAFER"
+0c4659b35ec2518914da924e692deb37e96d6206,Registering a MultiSensor Ensemble of Images,"Registering a MultiSensor Ensemble of Images
+Jeff Orchard, Member, IEEE, and Richard Mann"
+0ced7b814ec3bb9aebe0fcf0cac3d78f36361eae,Central Local Directional Pattern Value Flooding Co-occurrence Matrix based Features for Face Recognition,"Dr. P Chandra Sekhar Reddy, International Journal of Computer Science and Mobile Computing, Vol.6 Issue.1, January- 2017, pg. 221-227
+Available Online at www.ijcsmc.com
+International Journal of Computer Science and Mobile Computing
+A Monthly Journal of Computer Science and Information Technology
+ISSN 2320–088X
+IMPACT FACTOR: 6.017
+IJCSMC, Vol. 6, Issue. 1, January 2017, pg.221 – 227
+Central Local Directional Pattern Value
+Flooding Co-occurrence Matrix based
+Features for Face Recognition
+Dr. P Chandra Sekhar Reddy
+Professor, CSE Department, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad"
+0c53ef79bb8e5ba4e6a8ebad6d453ecf3672926d,Weakly Supervised PatchNets: Describing and Aggregating Local Patches for Scene Recognition,"SUBMITTED TO JOURNAL
+Weakly Supervised PatchNets: Describing and
+Aggregating Local Patches for Scene Recognition
+Zhe Wang, Limin Wang, Yali Wang, Bowen Zhang, and Yu Qiao, Senior Member, IEEE"
+6601a0906e503a6221d2e0f2ca8c3f544a4adab7,Detection of Ancient Settlement Mounds : Archaeological Survey Based on the SRTM Terrain Model,"SRTM-2  2/9/06  3:27 PM  Page 321
+Detection of Ancient Settlement Mounds:
+Archaeological Survey Based on the
+SRTM Terrain Model
+B.H. Menze, J.A. Ur, and A.G. Sherratt"
+660b73b0f39d4e644bf13a1745d6ee74424d4a16,Constructing Kernel Machines in the Empirical Kernel Feature Space,",250+OPEN ACCESS BOOKS106,000+INTERNATIONALAUTHORS AND EDITORS113+ MILLIONDOWNLOADSBOOKSDELIVERED TO151 COUNTRIESAUTHORS AMONGTOP 1%MOST CITED SCIENTIST12.2%AUTHORS AND EDITORSFROM TOP 500 UNIVERSITIESSelection of our books indexed in theBook Citation Index in Web of Science™Core Collection (BKCI)Chapter from the book Reviews, Refinements and New Ideas in Face RecognitionDownloaded from: http://www.intechopen.com/books/reviews-refinements-and-new-ideas-in-face-recognitionPUBLISHED BYWorld's largest Science,Technology & Medicine Open Access book publisherInterested in publishing with InTechOpen?Contact us at"
+66d512342355fb77a4450decc89977efe7e55fa2,Learning Non-linear Transform with Discrim- Inative and Minimum Information Loss Priors,"Under review as a conference paper at ICLR 2018
+LEARNING NON-LINEAR TRANSFORM WITH DISCRIM-
+INATIVE AND MINIMUM INFORMATION LOSS PRIORS
+Anonymous authors
+Paper under double-blind review"
+6643a7feebd0479916d94fb9186e403a4e5f7cbf,Chapter 8 3 D Face Recognition,"Chapter 8
+D Face Recognition
+Ajmal Mian and Nick Pears"
+661ca4bbb49bb496f56311e9d4263dfac8eb96e9,Datasheets for Datasets,"Datasheets for Datasets
+Timnit Gebru 1 Jamie Morgenstern 2 Briana Vecchione 3 Jennifer Wortman Vaughan 1 Hanna Wallach 1
+Hal Daumé III 1 4 Kate Crawford 1 5"
+66d087f3dd2e19ffe340c26ef17efe0062a59290,Dog Breed Identification,"Dog Breed Identiﬁcation
+Whitney LaRow
+Brian Mittl
+Vijay Singh"
+6618cff7f2ed440a0d2fa9e74ad5469df5cdbe4c,Ordinal Regression with Multiple Output CNN for Age Estimation,"Ordinal Regression with Multiple Output CNN for Age Estimation
+Zhenxing Niu1
+Gang Hua3
+Xidian University 2Xi’an Jiaotong University 3Microsoft Research Asia
+Xinbo Gao1
+Mo Zhou1
+Le Wang2"
+66a2c229ac82e38f1b7c77a786d8cf0d7e369598,A Probabilistic Adaptive Search System for Exploring the Face Space,"Proceedings of the 2016 Industrial and Systems Engineering Research Conference
+H. Yang, Z. Kong, and MD Sarder, eds.
+A Probabilistic Adaptive Search System
+for Exploring the Face Space
+Andres G. Abad and Luis I. Reyes Castro
+Escuela Superior Politecnica del Litoral (ESPOL)
+Guayaquil-Ecuador"
+66a9935e958a779a3a2267c85ecb69fbbb75b8dc,Fast and Robust Fixed-Rank Matrix Recovery,"FAST AND ROBUST FIXED-RANK MATRIX RECOVERY
+Fast and Robust Fixed-Rank Matrix
+Recovery
+German Ros*, Julio Guerrero, Angel Sappa, Daniel Ponsa and
+Antonio Lopez"
+66533107f9abdc7d1cb8f8795025fc7e78eb1122,Visual Servoing for a User's Mouth with Effective Intention Reading in a Wheelchair-based Robotic Arm,"Vi	a
+i a Whee
+W	y	g Sgy Dae	i iy g	S	g iz ad Ze	ga Biey
+y EECS AST 373	1 	g	Dg Y	g	G	 Taej 305	701 REA
+z VR Cee ETR 161 ajg	Dg Y	g	G	 Taej 305	350 REA
+Abac
+Thee exi he c	eaive aciviy bewee a h
+a beig ad ehabi
+a eae ehabi
+e ad ha he bee(cid:12) f ehabi
+	ch a ai	
+eadig i e f he eeia
+fied
+f ad afey f a
+
+bic a ye ARES  ad i h	a	b
+ieaci ech
+ech
+
+vi	a
+66810438bfb52367e3f6f62c24f5bc127cf92e56,Face Recognition of Illumination Tolerance in 2D Subspace Based on the Optimum Correlation Filter,"Face Recognition of Illumination Tolerance in 2D
+Subspace Based on the Optimum Correlation
+Filter
+Xu Yi
+Department of Information Engineering, Hunan Industry Polytechnic, Changsha, China
+images  will  be  tested  to  project"
+66af2afd4c598c2841dbfd1053bf0c386579234e,Context-assisted face clustering framework with human-in-the-loop,"Noname manuscript No.
+(will be inserted by the editor)
+Context Assisted Face Clustering Framework with
+Human-in-the-Loop
+Liyan Zhang · Dmitri V. Kalashnikov ·
+Sharad Mehrotra
+Received: date / Accepted: date"
+66e6f08873325d37e0ec20a4769ce881e04e964e,The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding,"Int J Comput Vis (2014) 108:59–81
+DOI 10.1007/s11263-013-0695-z
+The SUN Attribute Database: Beyond Categories for Deeper Scene
+Understanding
+Genevieve Patterson · Chen Xu · Hang Su ·
+James Hays
+Received: 27 February 2013 / Accepted: 28 December 2013 / Published online: 18 January 2014
+© Springer Science+Business Media New York 2014"
+661da40b838806a7effcb42d63a9624fcd684976,An Illumination Invariant Accurate Face Recognition with Down Scaling of DCT Coefficients,"An Illumination Invariant Accurate
+Face Recognition with Down Scaling
+of DCT Coefﬁcients
+Virendra P. Vishwakarma, Sujata Pandey and M. N. Gupta
+Department of Computer Science and Engineering, Amity School of Engineering and Technology, New Delhi, India
+In this paper, a novel approach for illumination normal-
+ization under varying lighting conditions is presented.
+Our approach utilizes the fact that discrete cosine trans-
+form (DCT) low-frequency coefficients correspond to
+illumination variations in a digital image. Under varying
+illuminations, the images captured may have low con-
+trast; initially we apply histogram equalization on these
+for contrast stretching. Then the low-frequency DCT
+oefficients are scaled down to compensate the illumi-
+nation variations. The value of scaling down factor and
+the number of low-frequency DCT coefficients, which
+re to be rescaled, are obtained experimentally. The
+lassification is done using k−nearest neighbor classi-
+fication and nearest mean classification on the images
+obtained by inverse DCT on the processed coefficients."
+66886f5af67b22d14177119520bd9c9f39cdd2e6,Learning Additive Kernel For Feature Transformation and Its Application to CNN Features,"T. KOBAYASHI: LEARNING ADDITIVE KERNEL
+Learning Additive Kernel For Feature
+Transformation and Its Application to CNN
+Features
+Takumi Kobayashi
+National Institute of Advanced Industrial
+Science and Technology
+Tsukuba, Japan"
+3edb0fa2d6b0f1984e8e2c523c558cb026b2a983,Automatic Age Estimation Based on Facial Aging Patterns,"Automatic Age Estimation Based on
+Facial Aging Patterns
+Xin Geng, Zhi-Hua Zhou, Senior Member, IEEE,
+Kate Smith-Miles, Senior Member, IEEE"
+3e4b38b0574e740dcbd8f8c5dfe05dbfb2a92c07,Facial Expression Recognition with Local Binary Patterns and Linear Programming,"FACIAL EXPRESSION RECOGNITION WITH LOCAL BINARY PATTERNS
+AND LINEAR PROGRAMMING
+Xiaoyi Feng1, 2, Matti Pietikäinen1, Abdenour Hadid1
+Machine Vision Group, Infotech Oulu and Dept. of Electrical and Information Engineering
+P. O. Box 4500 Fin-90014 University of Oulu, Finland
+2 College of Electronics and Information, Northwestern Polytechnic University
+710072 Xi’an, China
+In  this  work,  we  propose  a  novel  approach  to  recognize  facial  expressions  from  static
+images. First, the Local Binary Patterns (LBP) are used to efficiently represent the facial
+images and then the Linear Programming (LP) technique is adopted to classify the seven
+facial  expressions  anger,  disgust,  fear,  happiness,  sadness,  surprise  and  neutral.
+Experimental results demonstrate an average recognition accuracy of 93.8% on the JAFFE
+database, which outperforms the rates of all other reported methods on the same database.
+Introduction
+Facial  expression  recognition  from  static
+images  is  a  more  challenging  problem
+than  from  image  sequences  because  less
+information  for  expression  actions
+vailable.  However,  information  in  a
+single  image  is  sometimes  enough  for"
+3e4acf3f2d112fc6516abcdddbe9e17d839f5d9b,Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs,"Deep Value Networks Learn to
+Evaluate and Iteratively Reﬁne Structured Outputs
+Michael Gygli 1 * Mohammad Norouzi 2 Anelia Angelova 2"
+3e3f305dac4fbb813e60ac778d6929012b4b745a,Feature sampling and partitioning for visual vocabulary generation on large action classification datasets,"Feature sampling and partitioning for visual vocabulary
+generation on large action classiﬁcation datasets.
+Michael Sapienza1, Fabio Cuzzolin1, and Philip H.S. Torr2
+Department of Computing and Communications Technology, Oxford Brookes University.
+Department of Engineering Science, University of Oxford."
+3ea8a6dc79d79319f7ad90d663558c664cf298d4,Automatic Facial Expression Recognition from Video Sequences,"(cid:13) Copyright by Ira Cohen, 2000"
+3e4f84ce00027723bdfdb21156c9003168bc1c80,A co-training approach to automatic face recognition,"© EURASIP, 2011  -  ISSN 2076-1465
+9th European Signal Processing Conference (EUSIPCO 2011)
+INTRODUCTION"
+3e04feb0b6392f94554f6d18e24fadba1a28b65f,Subspace Image Representation for Facial Expression Analysis and Face Recognition and its Relation to the Human Visual System,"Subspace Image Representation for Facial
+Expression Analysis and Face Recognition
+nd its Relation to the Human Visual System
+Ioan Buciu1,2 and Ioannis Pitas1
+Department of Informatics, Aristotle University of Thessaloniki GR-541 24,
+Thessaloniki, Box 451, Greece.
+Electronics Department, Faculty of Electrical Engineering and Information
+Technology, University of Oradea 410087, Universitatii 1, Romania.
+Summary. Two main theories exist with respect to face encoding and representa-
+tion in the human visual system (HVS). The ﬁrst one refers to the dense (holistic)
+representation of the face, where faces have “holon”-like appearance. The second one
+laims that a more appropriate face representation is given by a sparse code, where
+only a small fraction of the neural cells corresponding to face encoding is activated.
+Theoretical and experimental evidence suggest that the HVS performs face analysis
+(encoding, storing, face recognition, facial expression recognition) in a structured
+nd hierarchical way, where both representations have their own contribution and
+goal. According to neuropsychological experiments, it seems that encoding for face
+recognition, relies on holistic image representation, while a sparse image represen-
+tation is used for facial expression analysis and classiﬁcation. From the computer
+vision perspective, the techniques developed for automatic face and facial expres-"
+3e685704b140180d48142d1727080d2fb9e52163,Single Image Action Recognition by Predicting Space-Time Saliency,"Single Image Action Recognition by Predicting
+Space-Time Saliency
+Marjaneh Safaei and Hassan Foroosh"
+3e687d5ace90c407186602de1a7727167461194a,Photo Tagging by Collection-Aware People Recognition,"Photo Tagging by Collection-Aware People Recognition
+Cristina Nader Vasconcelos
+Vinicius Jardim
+Asla S´a
+Paulo Cezar Carvalho"
+50f0c495a214b8d57892d43110728e54e413d47d,Pairwise support vector machines and their application to large scale problems,"Submitted 8/11; Revised 3/12; Published 8/12
+Pairwise Support Vector Machines and their Application to Large
+Scale Problems
+Carl Brunner
+Andreas Fischer
+Institute for Numerical Mathematics
+Technische Universit¨at Dresden
+01062 Dresden, Germany
+Klaus Luig
+Thorsten Thies
+Cognitec Systems GmbH
+Grossenhainer Str. 101
+01127 Dresden, Germany
+Editor: Corinna Cortes"
+501096cca4d0b3d1ef407844642e39cd2ff86b37,Illumination Invariant Face Image Representation Using Quaternions,"Illumination Invariant Face Image
+Representation using Quaternions
+Dayron Rizo-Rodr´ıguez, Heydi M´endez-V´azquez, and Edel Garc´ıa-Reyes
+Advanced Technologies Application Center. 7a # 21812 b/ 218 and 222,
+Rpto. Siboney, Playa, P.C. 12200, La Habana, Cuba."
+501eda2d04b1db717b7834800d74dacb7df58f91,Discriminative Sparse Representation for Expression Recognition,"Pedro Miguel Neves Marques    Discriminative Sparse Representation for Expression Recognition     Master Thesis in Electrical and Computer Engineering September, 2014"
+5083c6be0f8c85815ead5368882b584e4dfab4d1,Automated Face Analysis for Affective Computing Jeffrey,"Please do not quote.  In press, Handbook of affective computing. New York, NY: Oxford
+Automated Face Analysis for Affective Computing
+Jeffrey F. Cohn & Fernando De la Torre"
+5058a7ec68c32984c33f357ebaee96c59e269425,A Comparative Evaluation of Regression Learning Algorithms for Facial Age Estimation,"A Comparative Evaluation of Regression Learning
+Algorithms for Facial Age Estimation
+Carles Fern´andez1, Ivan Huerta2, and Andrea Prati2
+Herta Security
+Pau Claris 165 4-B, 08037 Barcelona, Spain
+DPDCE, University IUAV
+Santa Croce 1957, 30135 Venice, Italy"
+50ff21e595e0ebe51ae808a2da3b7940549f4035,Age Group and Gender Estimation in the Wild With Deep RoR Architecture,"IEEE TRANSACTIONS ON LATEX CLASS FILES, VOL. XX, NO. X, AUGUST 2017
+Age Group and Gender Estimation in the Wild with
+Deep RoR Architecture
+Ke Zhang, Member, IEEE, Ce Gao, Liru Guo, Miao Sun, Student Member, IEEE, Xingfang Yuan, Student
+Member, IEEE, Tony X. Han, Member, IEEE, Zhenbing Zhao, Member, IEEE and Baogang Li"
+5042b358705e8d8e8b0655d07f751be6a1565482,Review on Emotion Detection in Image,"International Journal of
+Emerging Research in Management &Technology
+ISSN: 2278-9359 (Volume-4, Issue-8)
+Research  Article
+August
+Review  on Emotion Detection  in Image
+Aswinder Kaur*                                                                                                        Kapil Dewan
+CSE & PCET, PTU                                                                                             HOD, CSE & PCET, PTU
+Punjab, India                                                                                                            Punj ab, India"
+50e47857b11bfd3d420f6eafb155199f4b41f6d7,3D Human Face Reconstruction Using a Hybrid of Photometric Stereo and Independent Component Analysis,"International Journal of Computer, Consumer and Control (IJ3C), Vol. 2, No.1 (2013)
+D Human Face Reconstruction Using a Hybrid of Photometric
+Stereo and Independent Component Analysis
+*Cheng-Jian Lin, 2Shyi-Shiun Kuo, 1Hsueh-Yi Lin, 2Shye-Chorng Kuo and 1Cheng-Yi Yu"
+50eb75dfece76ed9119ec543e04386dfc95dfd13,Learning Visual Entities and Their Visual Attributes from Text Corpora,"Learning Visual Entities and their Visual Attributes from Text Corpora
+Erik Boiy
+Dept. of Computer Science
+K.U.Leuven, Belgium
+Koen Deschacht
+Dept. of Computer Science
+K.U.Leuven, Belgium
+Marie-Francine Moens
+Dept. of Computer Science
+K.U.Leuven, Belgium"
+50a0930cb8cc353e15a5cb4d2f41b365675b5ebf,Robust Facial Landmark Detection and Face Tracking in Thermal Infrared Images using Active Appearance Models,
+50eb2ee977f0f53ab4b39edc4be6b760a2b05f96,Emotion recognition based on texture analysis of facial expression,"Australian Journal of Basic and Applied Sciences, 11(5) April 2017, Pages: 1-11
+AUSTRALIAN JOURNAL OF BASIC AND
+APPLIED SCIENCES
+ISSN:1991-8178        EISSN: 2309-8414
+Journal home page: www.ajbasweb.com
+Emotion  Recognition  Based  on  Texture  Analysis  of  Facial  Expressions
+Using Wavelets Transform
+Suhaila N. Mohammed and 2Loay E. George
+Assistant Lecturer, Computer Science Department, College of Science, Baghdad University, Baghdad, Iraq,
+Assistant Professor, Computer Science Department, College of Science, Baghdad University, Baghdad, Iraq,
+Address For Correspondence:
+Suhaila N. Mohammed, Baghdad University, Computer Science Department, College of Science, Baghdad, Iraq.
+A R T I C L E   I N F O
+Article history:
+Received 18 January 2017
+Accepted 28 March 2017
+Available online 15 April 2017
+Keywords:
+Facial  Emotion,  Face  Detection,
+Template  Based  Methods,  Texture"
+50d15cb17144344bb1879c0a5de7207471b9ff74,"Divide, Share, and Conquer: Multi-task Attribute Learning with Selective Sharing","Divide, Share, and Conquer: Multi-task
+Attribute Learning with Selective Sharing
+Chao-Yeh Chen*, Dinesh Jayaraman*, Fei Sha, and Kristen Grauman"
+50d961508ec192197f78b898ff5d44dc004ef26d,A Low Indexed Content Based Neural Network Approach for Natural Objects Recognition,"International Journal of Computer science & Information Technology (IJCSIT), Vol 1, No 2, November 2009
+A LOW INDEXED CONTENT BASED
+NEURAL NETWORK APPROACH FOR
+NATURAL OBJECTS RECOGNITION
+G.Shyama Chandra Prasad1 and Dr. A.Govardhan 2  Dr. T.V.Rao 3
+Research Scholar, JNTUH, Hyderabad, AP. India
+Principal, JNTUH College of Engineering, jagitial, Karimnagar, AP, India
+Principal, Chaithanya Institute of Engineering and Technology, Kakinada, AP, India"
+50ccc98d9ce06160cdf92aaf470b8f4edbd8b899,Towards robust cascaded regression for face alignment in the wild,"Towards Robust Cascaded Regression for Face Alignment in the Wild
+Chengchao Qu1,2 Hua Gao3
+Eduardo Monari2
+J¨urgen Beyerer2,1
+Jean-Philippe Thiran3
+Vision and Fusion Laboratory (IES), Karlsruhe Institute of Technology (KIT)
+Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (Fraunhofer IOSB)
+Signal Processing Laboratory (LTS5), ´Ecole Polytechnique F´ed´erale de Lausanne (EPFL)"
+5028c0decfc8dd623c50b102424b93a8e9f2e390,Revisiting Classifier Two-sample Tests,"Published as a conference paper at ICLR 2017
+REVISITING CLASSIFIER TWO-SAMPLE TESTS
+David Lopez-Paz1, Maxime Oquab1,2
+Facebook AI Research, 2WILLOW project team, Inria / ENS / CNRS"
+505e55d0be8e48b30067fb132f05a91650666c41,A Model of Illumination Variation for Robust Face Recognition,"A Model of Illumination Variation for Robust Face Recognition
+Florent Perronnin and Jean-Luc Dugelay
+Institut Eur´ecom
+Multimedia Communications Department
+BP 193, 06904 Sophia Antipolis Cedex, France
+fflorent.perronnin,"
+507c9672e3673ed419075848b4b85899623ea4b0,Multi-View Facial Expression Classification,"Faculty of Informatics
+Institute for Anthropomatics
+Chair Prof. Dr.-Ing. R. Stiefelhagen
+Facial Image Processing and Analysis Group
+Multi-View Facial Expression
+Classiﬁcation
+DIPLOMA THESIS OF
+Nikolas Hesse
+ADVISORS
+Dr.-Ing. Hazım Kemal Ekenel
+Dipl.-Inform. Hua Gao
+Dipl.-Inform. Tobias Gehrig
+MARCH 2011
+KIT – University of the State of Baden-Württemberg and National Laboratory of the Helmholtz Association
+www.kit.edu"
+680d662c30739521f5c4b76845cb341dce010735,Part and Attribute Discovery from Relative Annotations,"Int J Comput Vis (2014) 108:82–96
+DOI 10.1007/s11263-014-0716-6
+Part and Attribute Discovery from Relative Annotations
+Subhransu Maji · Gregory Shakhnarovich
+Received: 25 February 2013 / Accepted: 14 March 2014 / Published online: 26 April 2014
+© Springer Science+Business Media New York 2014"
+68a2ee5c5b76b6feeb3170aaff09b1566ec2cdf5,Age Classification Based on Simple Lbp Transitions,"AGE CLASSIFICATION BASED ON
+SIMPLE LBP TRANSITIONS
+Research Scholar & Assoc Professor, Aditya institute of Technology and Management, Tekkalli-532 201, A.P.,
+Gorti Satyanarayana Murty
+India,
+Dr. V.Vijaya Kumar
+A. Obulesu
+Dean-Computer Sciences (CSE & IT), Anurag Group of Institutions, Hyderabad – 500088, A.P., India.,
+3Asst. Professor, Dept. Of CSE, Anurag Group of Institutions, Hyderabad – 500088, A.P., India."
+68d2afd8c5c1c3a9bbda3dd209184e368e4376b9,Representation Learning by Rotating Your Faces,"Representation Learning by Rotating Your Faces
+Luan Tran, Xi Yin, and Xiaoming Liu, Member, IEEE"
+6859b891a079a30ef16f01ba8b85dc45bd22c352,"2D Face Recognition Based on PCA & Comparison of Manhattan Distance, Euclidean Distance & Chebychev Distance","International Journal of Emerging Technology and Advanced Engineering
+Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 10, October 2014)
+D Face Recognition Based on PCA & Comparison of
+Manhattan Distance, Euclidean Distance & Chebychev
+Distance
+Rajib Saha1, Sayan Barman2
+RCC Institute of Information Technology, Kolkata, India"
+68d08ed9470d973a54ef7806318d8894d87ba610,Drive Video Analysis for the Detection of Traffic Near-Miss Incidents,"Drive Video Analysis for the Detection of Trafﬁc Near-Miss Incidents
+Hirokatsu Kataoka1, Teppei Suzuki1
+, Shoko Oikawa3, Yasuhiro Matsui4 and Yutaka Satoh1"
+68caf5d8ef325d7ea669f3fb76eac58e0170fff0,Long-term face tracking in the wild using deep learning,
+68003e92a41d12647806d477dd7d20e4dcde1354,Fuzzy Based Image Dimensionality Reduction Using Shape Primitives for Efficient Face Recognition,"ISSN: 0976-9102 (ONLINE)
+DOI: 10.21917/ijivp.2013.0101
+ICTACT JOURNAL ON IMAGE AND VIDEO PROCESSING, NOVEMBER 2013, VOLUME: 04, ISSUE: 02
+FUZZY BASED IMAGE DIMENSIONALITY REDUCTION USING SHAPE
+PRIMITIVES FOR EFFICIENT FACE RECOGNITION
+P. Chandra Sekhar Reddy1, B. Eswara Reddy2 and V. Vijaya Kumar3
+Deprtment of Computer Science and Engineering, Nalla Narasimha Reddy Education Society’s Group of Institutions, India
+E-Mail:
+Deprtment of Computer Science and Engineering, JNTUA College of Engineering, India
+Deprtment of Computer Science and Engineering, Anurag Group of Institutions, India
+E-mail:
+E-mail:"
+68d4056765c27fbcac233794857b7f5b8a6a82bf,Example-Based Face Shape Recovery Using the Zenith Angle of the Surface Normal,"Example-Based Face Shape Recovery Using the
+Zenith Angle of the Surface Normal
+Mario Castel´an1, Ana J. Almaz´an-Delf´ın2, Marco I. Ram´ırez-Sosa-Mor´an3,
+nd Luz A. Torres-M´endez1
+CINVESTAV Campus Saltillo, Ramos Arizpe 25900, Coahuila, M´exico
+Universidad Veracruzana, Facultad de F´ısica e Inteligencia Artiﬁcial, Xalapa 91000,
+ITESM, Campus Saltillo, Saltillo 25270, Coahuila, M´exico
+Veracruz, M´exico"
+684f5166d8147b59d9e0938d627beff8c9d208dd,Discriminative Block-Diagonal Representation Learning for Image Recognition,"IEEE TRANS. NNLS, JUNE 2017
+Discriminative Block-Diagonal Representation
+Learning for Image Recognition
+Zheng Zhang, Yong Xu, Senior Member, IEEE, Ling Shao, Senior Member, IEEE, Jian Yang, Member, IEEE"
+68e9c837431f2ba59741b55004df60235e50994d,Detecting Faces Using Region-based Fully Convolutional Networks,"Detecting Faces Using Region-based Fully
+Convolutional Networks
+Yitong Wang Xing Ji Zheng Zhou Hao Wang Zhifeng Li∗
+Tencent AI Lab, China"
+685f8df14776457c1c324b0619c39b3872df617b,Face Recognition with Preprocessing and Neural Networks,"Master of Science Thesis in Electrical Engineering
+Department of Electrical Engineering, Linköping University, 2016
+Face Recognition with
+Preprocessing and Neural
+Networks
+David Habrman"
+68484ae8a042904a95a8d284a7f85a4e28e37513,Spoofing Deep Face Recognition with Custom Silicone Masks,"Spooﬁng Deep Face Recognition with Custom Silicone Masks
+Sushil Bhattacharjee Amir Mohammadi
+S´ebastien Marcel
+Idiap Research Institute. Centre du Parc, Rue Marconi 19, Martigny (VS), Switzerland
+{sushil.bhattacharjee; amir.mohammadi;"
+687e17db5043661f8921fb86f215e9ca2264d4d2,A robust elastic and partial matching metric for face recognition,"A Robust Elastic and Partial Matching Metric for Face Recognition
+Gang Hua
+Amir Akbarzadeh
+Microsoft Corporate
+One Microsoft Way, Redmond, WA 98052
+{ganghua,"
+688754568623f62032820546ae3b9ca458ed0870,Resting high frequency heart rate variability is not associated with the recognition of emotional facial expressions in healthy human adults,"ioRxiv preprint first posted online Sep. 27, 2016;
+http://dx.doi.org/10.1101/077784
+The copyright holder for this preprint (which was not
+peer-reviewed) is the author/funder. It is made available under a
+CC-BY-NC-ND 4.0 International license
+Resting high frequency heart rate variability is not associated with the
+recognition of emotional facial expressions in healthy human adults.
+Brice Beffara1,2,3, Nicolas Vermeulen3,4, Martial Mermillod1,2
+Univ. Grenoble Alpes, LPNC, F-38040, Grenoble, France
+CNRS, LPNC UMR 5105, F-38040, Grenoble, France
+IPSY, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
+Fund for Scientiﬁc Research (FRS-FNRS), Brussels, Belgium
+Correspondence concerning this article should be addressed to Brice Beffara, Of‌f‌ice E250, Institut
+de Recherches en Sciences Psychologiques, IPSY - Place du Cardinal Mercier, 10 bte L3.05.01 B-1348
+Louvain-la-Neuve, Belgium. E-mail:
+Author note
+This study explores whether the myelinated vagal connection between the heart and the brain
+is involved in emotion recognition. The Polyvagal theory postulates that the activity of the
+myelinated vagus nerve underlies socio-emotional skills. It has been proposed that the perception
+of emotions could be one of this skills dependent on heart-brain interactions. However, this"
+68f9cb5ee129e2b9477faf01181cd7e3099d1824,ALDA Algorithms for Online Feature Extraction,"ALDA Algorithms for Online Feature Extraction
+Youness Aliyari Ghassabeh, Hamid Abrishami Moghaddam"
+68d40176e878ebffbc01ffb0556e8cb2756dd9e9,Locality Repulsion Projection and Minutia Extraction Based Similarity Measure for Face Recognition,"International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622
+International Conference on Humming Bird ( 01st March 2014)
+RESEARCH ARTICLE
+OPEN ACCESS
+Locality Repulsion Projection and Minutia Extraction Based
+Similarity Measure for Face Recognition
+Agnel AnushyaP.1,RamyaP.2
+AgnelAnushya P. is currently pursuing M.E (Computer Science and engineering) at Vins Christian college of
+Ramya P. is currently working as an Asst. Professor in the dept. of Information Technology at Vins Christian
+Engineering.
+ollege of Engineering."
+6889d649c6bbd9c0042fadec6c813f8e894ac6cc,Analysis of Robust Soft Learning Vector Quantization and an application to Facial Expression Recognition,"Analysis of Robust Soft Learning Vector
+Quantization and an application to Facial
+Expression Recognition"
+68c17aa1ecbff0787709be74d1d98d9efd78f410,Gender Classification from Face Images Using Mutual Information and Feature Fusion,"International Journal of Optomechatronics, 6: 92–119, 2012
+Copyright # Taylor & Francis Group, LLC
+ISSN: 1559-9612 print=1559-9620 online
+DOI: 10.1080/15599612.2012.663463
+GENDER CLASSIFICATION FROM FACE IMAGES
+USING MUTUAL INFORMATION AND FEATURE
+FUSION
+Claudio Perez, Juan Tapia, Pablo Este´vez, and Claudio Held
+Department of Electrical Engineering and Advanced Mining Technology
+Center, Universidad de Chile, Santiago, Chile
+In this article we report a new method for gender classiﬁcation from frontal face images
+using feature selection based on mutual information and fusion of features extracted from
+intensity, shape, texture, and from three different spatial scales. We compare the results of
+three different mutual information measures: minimum redundancy and maximal relevance
+(mRMR), normalized mutual information feature selection (NMIFS), and conditional
+mutual information feature selection (CMIFS). We also show that by fusing features
+extracted from six different methods we signiﬁcantly improve the gender classiﬁcation
+results relative to those previously published, yielding 99.13% of the gender classiﬁcation
+rate on the FERET database.
+Keywords: Feature fusion, feature selection, gender classiﬁcation, mutual information, real-time gender"
+68f61154a0080c4aae9322110c8827978f01ac2e,"Recognizing blurred , non-frontal , illumination and expression variant partially occluded faces","Research Article
+Journal of the Optical Society of America A
+Recognizing blurred, non-frontal, illumination and
+expression variant partially occluded faces
+ABHIJITH PUNNAPPURATH1* AND AMBASAMUDRAM NARAYANAN RAJAGOPALAN1
+Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai 600036, India.
+*Corresponding author:
+Compiled June 26, 2016
+The focus of this paper is on the problem of recognizing faces across space-varying motion blur, changes
+in pose, illumination, and expression, as well as partial occlusion, when only a single image per subject
+is available in the gallery. We show how the blur incurred due to relative motion between the camera and
+the subject during exposure can be estimated from the alpha matte of pixels that straddle the boundary
+etween the face and the background. We also devise a strategy to automatically generate the trimap re-
+quired for matte estimation. Having computed the motion via the matte of the probe, we account for pose
+variations by synthesizing from the intensity image of the frontal gallery, a face image that matches the
+pose of the probe. To handle illumination and expression variations, and partial occlusion, we model the
+probe as a linear combination of nine blurred illumination basis images in the synthesized non-frontal
+pose, plus a sparse occlusion. We also advocate a recognition metric that capitalizes on the sparsity of the
+occluded pixels. The performance of our method is extensively validated on synthetic as well as real face
+data. © 2016 Optical Society of America"
+6888f3402039a36028d0a7e2c3df6db94f5cb9bb,Classifier-to-generator Attack: Estimation,"Under review as a conference paper at ICLR 2018
+CLASSIFIER-TO-GENERATOR ATTACK: ESTIMATION
+OF TRAINING DATA DISTRIBUTION FROM CLASSIFIER
+Anonymous authors
+Paper under double-blind review"
+57c59011614c43f51a509e10717e47505c776389,Unsupervised Human Action Detection by Action Matching,"Unsupervised Human Action Detection by Action Matching
+Basura Fernando∗ Sareh Shirazi† Stephen Gould∗
+The Australian National University †Queensland University of Technology"
+571f493c0ade12bbe960cfefc04b0e4607d8d4b2,Review on Content Based Image Retrieval: From Its Origin to the New Age,"International Journal of Research Studies in Science, Engineering and Technology
+Volume 3, Issue 2, February 2016, PP 18-41
+ISSN 2349-4751 (Print) & ISSN 2349-476X (Online)
+Review on Content Based Image Retrieval: From Its Origin to the
+New Age
+Mrs. P. Nalini
+Assistant Professor, ECE
+Dr. B. L. Malleswari
+Principal
+Mahatma Gandhi Institute of Technology
+Sridevi Women's Engineering College
+Hyderabad, India
+Hyderabad, India"
+57f8e1f461ab25614f5fe51a83601710142f8e88,Region Selection for Robust Face Verification using UMACE Filters,"Region Selection for Robust Face Verification using UMACE Filters
+Salina Abdul Samad*, Dzati Athiar Ramli, Aini Hussain
+Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering,
+Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia.
+In  this  paper,  we  investigate  the  verification  performances  of  four  subdivided  face  images  with  varying  expressions.  The
+objective of this study is to evaluate which part of the face image is more tolerant to facial expression and still retains its personal
+haracteristics due to the variations of the image. The Unconstrained Minimum Average Correlation Energy (UMACE) filter is
+implemented to perform the verification process because of its advantages such as shift–invariance, ability to trade-off between
+discrimination and distortion tolerance, e.g. variations in pose, illumination and facial expression. The database obtained from the
+facial expression database of Advanced Multimedia Processing (AMP) Lab at CMU is used in this study. Four equal
+sizes of face regions i.e. bottom, top, left and right halves are used for the purpose of this study. The results show that the bottom
+half of the face region gives the best performance in terms of the PSR values with zero false accepted rate (FAR) and zero false
+rejection rate (FRR) compared to the other three regions.
+. Introduction
+Face  recognition  is  a  well  established  field  of  research,
+nd a large number of algorithms have been proposed in the
+literature. Various classifiers have been explored to improve
+the accuracy of face classification. The basic approach is to
+use distance-base methods which measure Euclidean distance
+etween any two vectors and then compare it with the preset"
+57a1466c5985fe7594a91d46588d969007210581,A taxonomy of face-models for system evaluation,"A Taxonomy of Face-models for System Evaluation
+Vijay N. Iyer, Shane. R. Kirkbride, Brian C. Parks, Walter J. Scheirer and Terrance. E. Boult
+Motivation and Data Types
+Synthetic Data Types
+Unverified – Have no underlying physical or
+statistical basis
+Physics -Based – Based on structure and
+materials combined with the properties
+formally modeled in physics.
+Statistical  – Use statistics from real
+data/experiments to estimate/learn model
+parameters. Generally have measurements
+of accuracy
+Guided Synthetic – Individual models based
+on individual people. No attempt to capture
+properties of large groups, a unique model
+per person. For faces, guided models are
+omposed of 3D structure models and skin
+textures,  capturing many artifacts  not
+easily  parameterized. Can be combined with"
+57246142814d7010d3592e3a39a1ed819dd01f3b,Verification of Very Low-Resolution Faces Using An Identity-Preserving Deep Face Super-resolution Network,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES
+http://www.merl.com
+Veriﬁcation of Very Low-Resolution Faces Using An
+Identity-Preserving Deep Face Super-resolution Network
+Ataer-Cansizoglu, E.; Jones, M.J.; Zhang, Z.; Sullivan, A.
+TR2018-116 August 24, 2018"
+574705812f7c0e776ad5006ae5e61d9b071eebdb,A Novel Approach for Face Recognition Using PCA and Artificial Neural Network,"Karthik G et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.5, May- 2014, pg. 780-787
+Available Online at www.ijcsmc.com
+International Journal of Computer Science and Mobile Computing
+A Monthly Journal of Computer Science and Information Technology
+ISSN 2320–088X
+IJCSMC, Vol. 3, Issue. 5, May 2014, pg.780 – 787
+RESEARCH ARTICLE
+A Novel Approach for Face Recognition
+Using PCA and Artificial Neural Network
+Karthik G1, Sateesh Kumar H C2
+¹Deptartment of Telecommunication Engg., Dayananda Sagar College of Engg., India
+²Department of Telecommunication Engg., Dayananda Sagar College of Engg., India
+email : 2 email :"
+571b83f7fc01163383e6ca6a9791aea79cafa7dd,SeqFace: Make full use of sequence information for face recognition,"SeqFace: Make full use of sequence information for face recognition
+Wei Hu1 ∗
+Yangyu Huang2
+Guodong Yuan2
+Fan Zhang1
+Ruirui Li1
+Wei Li1
+College of Information Science and Technology,
+Beijing University of Chemical Technology, China
+YUNSHITU Corp., China"
+574ad7ef015995efb7338829a021776bf9daaa08,AdaScan: Adaptive Scan Pooling in Deep Convolutional Neural Networks for Human Action Recognition in Videos,"AdaScan: Adaptive Scan Pooling in Deep Convolutional Neural Networks
+for Human Action Recognition in Videos
+Amlan Kar1,∗
+Nishant Rai1,∗
+Karan Sikka2,3,†
+Gaurav Sharma1
+IIT Kanpur‡
+SRI International
+UCSD"
+57a14a65e8ae15176c9afae874854e8b0f23dca7,Seeing Mixed Emotions: The Specificity of Emotion Perception From Static and Dynamic Facial Expressions Across Cultures,"UvA-DARE (Digital Academic Repository)
+Seeing mixed emotions: The specificity of emotion perception from static and dynamic
+facial expressions across cultures
+Fang, X.; Sauter, D.A.; van Kleef, G.A.
+Published in:
+Journal of Cross-Cultural Psychology
+0.1177/0022022117736270
+Link to publication
+Citation for published version (APA):
+Fang, X., Sauter, D. A., & van Kleef, G. A. (2018). Seeing mixed emotions: The specificity of emotion perception
+from static and dynamic facial expressions across cultures. Journal of Cross-Cultural Psychology, 49(1), 130-
+48. DOI: 10.1177/0022022117736270
+General rights
+It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s),
+other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons).
+Disclaimer/Complaints regulations
+If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating
+your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask
+the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam,
+The Netherlands. You will be contacted as soon as possible."
+57d37ad025b5796457eee7392d2038910988655a,Aeaeêêìáîî Áåèääååaeììáçae Çç Àááêêêàáááä Aeçîîäìì Ììììçê,"GEERATVEEETATF
+
+DagaEha
+UdeheS	eviif
+f.DahaWeiha
+ATheiS	biediaia
+Re	ieefheDegeef
+aefSciece
+TheSch
+
+Decebe2009"
+3b1aaac41fc7847dd8a6a66d29d8881f75c91ad5,Sparse Representation-Based Open Set Recognition,"Sparse Representation-based Open Set Recognition
+He Zhang, Student Member, IEEE and Vishal M. Patel, Senior Member, IEEE"
+3bc776eb1f4e2776f98189e17f0d5a78bb755ef4,View Synthesis from Image and Video for Object Recognition Applications,
+3b15a48ffe3c6b3f2518a7c395280a11a5f58ab0,On knowledge transfer in object class recognition,"On Knowledge Transfer in
+Object Class Recognition
+A dissertation approved by
+TECHNISCHE UNIVERSITÄT DARMSTADT
+Fachbereich Informatik
+for the degree of
+Doktor-Ingenieur (Dr.-Ing.)
+presented by
+MICHAEL STARK
+Dipl.-Inform.
+orn in Mainz, Germany
+Prof. Dr.-Ing. Michael Goesele, examiner
+Prof. Martial Hebert, Ph.D., co-examiner
+Prof. Dr. Bernt Schiele, co-examiner
+Date of Submission: 12th of August, 2010
+Date of Defense: 23rd of September, 2010
+Darmstadt, 2010"
+3baa3d5325f00c7edc1f1427fcd5bdc6a420a63f,Enhancing Convolutional Neural Networks for Face Recognition with Occlusion Maps and Batch Triplet Loss,"Enhancing Convolutional Neural Networks for Face Recognition with
+Occlusion Maps and Batch Triplet Loss
+Daniel S´aez Triguerosa,b, Li Menga,∗, Margaret Hartnettb
+School of Engineering and Technology, University of Hertfordshire, Hatﬁeld AL10 9AB, UK
+IDscan Biometrics (a GBG company), London E14 9QD, UK"
+3ba8f8b6bfb36465018430ffaef10d2caf3cfa7e,Local Directional Number Pattern for Face Analysis: Face and Expression Recognition,"Local Directional Number Pattern for Face
+Analysis: Face and Expression Recognition
+Adin Ramirez Rivera, Student Member, IEEE, Jorge Rojas Castillo, Student Member, IEEE,
+nd Oksam Chae, Member, IEEE"
+3b9d94752f8488106b2c007e11c193f35d941e92,"Appearance, Visual and Social Ensembles for Face Recognition in Personal Photo Collections","#2052
+CVPR 2013 Submission #2052. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
+#2052
+Appearance, Visual and Social Ensembles for
+Face Recognition in Personal Photo Collections
+Anonymous CVPR submission
+Paper ID 2052"
+3b557c4fd6775afc80c2cf7c8b16edde125b270e,Face recognition: Perspectives from the real world,"Face Recognition: Perspectives from the
+Real-World
+Bappaditya Mandal
+Institute for Infocomm Research, A*STAR,
+Fusionopolis Way, #21-01 Connexis (South Tower), Singapore 138632.
+Phone: +65 6408 2071; Fax: +65 6776 1378;
+E-mail:"
+3b410ae97e4564bc19d6c37bc44ada2dcd608552,Scalability Analysis of Audio-Visual Person Identity Verification,"Scalability Analysis of Audio-Visual Person
+Identity Veriﬁcation
+Jacek Czyz1, Samy Bengio2, Christine Marcel2, and Luc Vandendorpe1
+Communications Laboratory,
+Universit´e catholique de Louvain, B-1348 Belgium,
+IDIAP, CH-1920 Martigny,
+Switzerland"
+6f5ce5570dc2960b8b0e4a0a50eab84b7f6af5cb,Low Resolution Face Recognition Using a Two-Branch Deep Convolutional Neural Network Architecture,"Low Resolution Face Recognition Using a
+Two-Branch Deep Convolutional Neural Network
+Architecture
+Erfan Zangeneh, Mohammad Rahmati, and Yalda Mohsenzadeh"
+6f288a12033fa895fb0e9ec3219f3115904f24de,Learning Expressionlets via Universal Manifold Model for Dynamic Facial Expression Recognition,"Learning Expressionlets via Universal Manifold
+Model for Dynamic Facial Expression Recognition
+Mengyi Liu, Student Member, IEEE, Shiguang Shan, Senior Member, IEEE, Ruiping Wang, Member, IEEE,
+Xilin Chen, Senior Member, IEEE"
+6f957df9a7d3fc4eeba53086d3d154fc61ae88df,Modélisation et suivi des déformations faciales : applications à la description des expressions du visage dans le contexte de la langue des signes,"Mod´elisation et suivi des d´eformations faciales :
+pplications `a la description des expressions du visage
+dans le contexte de la langue des signes
+Hugo Mercier
+To cite this version:
+Hugo Mercier. Mod´elisation et suivi des d´eformations faciales : applications `a la description
+des expressions du visage dans le contexte de la langue des signes. Interface homme-machine
+[cs.HC]. Universit´e Paul Sabatier - Toulouse III, 2007. Fran¸cais. <tel-00185084>
+HAL Id: tel-00185084
+https://tel.archives-ouvertes.fr/tel-00185084
+Submitted on 5 Nov 2007
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entiﬁc research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destin´ee au d´epˆot et `a la diffusion de documents
+scientiﬁques de niveau recherche, publi´es ou non,"
+6f7d06ced04ead3b9a5da86b37e7c27bfcedbbdd,Multi-Scale Fully Convolutional Network for Fast Face Detection,"Pages 51.1-51.12
+DOI: https://dx.doi.org/10.5244/C.30.51"
+6f7a8b3e8f212d80f0fb18860b2495be4c363eac,Creating Capsule Wardrobes from Fashion Images,"Creating Capsule Wardrobes from Fashion Images
+Wei-Lin Hsiao
+UT-Austin
+Kristen Grauman
+UT-Austin"
+6f6b4e2885ea1d9bea1bb2ed388b099a5a6d9b81,"Structured Output SVM Prediction of Apparent Age, Gender and Smile from Deep Features","Structured Output SVM Prediction of Apparent Age,
+Gender and Smile From Deep Features
+Michal Uˇriˇc´aˇr
+CMP, Dept. of Cybernetics
+FEE, CTU in Prague
+Radu Timofte
+Computer Vision Lab
+D-ITET, ETH Zurich
+Rasmus Rothe
+Computer Vision Lab
+D-ITET, ETH Zurich
+Luc Van Gool
+PSI, ESAT, KU Leuven
+CVL, D-ITET, ETH Zurich
+Jiˇr´ı Matas
+CMP, Dept. of Cybernetics
+FEE, CTU in Prague"
+6f08885b980049be95a991f6213ee49bbf05c48d,Author's Personal Copy Multi-kernel Appearance Model ☆,"This article appeared in a journal published by Elsevier. The attached
+opy is furnished to the author for internal non-commercial research
+nd education use, including for instruction at the authors institution
+nd sharing with colleagues.
+Other uses, including reproduction and distribution, or selling or
+licensing copies, or posting to personal, institutional or third party
+websites are prohibited.
+In most cases authors are permitted to post their version of the
+rticle (e.g. in Word or Tex form) to their personal website or
+institutional repository. Authors requiring further information
+regarding Elsevier’s archiving and manuscript policies are
+encouraged to visit:
+http://www.elsevier.com/authorsrights"
+6f35b6e2fa54a3e7aaff8eaf37019244a2d39ed3,Learning probabilistic classifiers for human–computer interaction applications,"DOI 10.1007/s00530-005-0177-4
+R E G U L A R PA P E R
+Nicu Sebe · Ira Cohen · Fabio G. Cozman ·
+Theo Gevers · Thomas S. Huang
+Learning probabilistic classiﬁers for human–computer
+interaction applications
+Published online: 10 May 2005
+(cid:1) Springer-Verlag 2005
+intelligent
+interaction,"
+6f3054f182c34ace890a32fdf1656b583fbc7445,Age Estimation Robust to Optical and Motion Blurring by Deep Residual CNN,"Article
+Age Estimation Robust to Optical and Motion
+Blurring by Deep Residual CNN
+Jeon Seong Kang, Chan Sik Kim, Young Won Lee, Se Woon Cho and Kang Ryoung Park *
+Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro, 1-gil, Jung-gu,
+Seoul 100-715, Korea; (J.S.K.); (C.S.K.);
+(Y.W.L.); (S.W.C.)
+* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735
+Received: 9 March 2018; Accepted: 10 April 2018; Published: 13 April 2018"
+6fa3857faba887ed048a9e355b3b8642c6aab1d8,Face Recognition in Challenging Environments: An Experimental and Reproducible Research Survey,"Face Recognition in Challenging Environments:
+An Experimental and Reproducible Research
+Survey
+Manuel G¨unther and Laurent El Shafey and S´ebastien Marcel"
+6f7ce89aa3e01045fcd7f1c1635af7a09811a1fe,A novel rank order LoG filter for interest point detection,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE
+ICASSP 2012"
+6fe2efbcb860767f6bb271edbb48640adbd806c3,Soft Biometrics; Human Identification Using Comparative Descriptions,"SOFT BIOMETRICS: HUMAN IDENTIFICATION USING COMPARATIVE DESCRIPTIONS
+Soft Biometrics; Human Identiﬁcation using
+Comparative Descriptions
+Daniel A. Reid, Mark S. Nixon, Sarah V. Stevenage"
+6fdc0bc13f2517061eaa1364dcf853f36e1ea5ae,DAISEE: Dataset for Affective States in E-Learning Environments,"DAISEE: Dataset for Affective States in
+E-Learning Environments
+Abhay Gupta1, Richik Jaiswal2, Sagar Adhikari2, Vineeth Balasubramanian2
+Microsoft India R&D Pvt. Ltd.
+Department of Computer Science, IIT Hyderabad
+{cs12b1032, cs12b1034,"
+6f5151c7446552fd6a611bf6263f14e729805ec7,Facial Action Unit Recognition using Filtered Local Binary Pattern Features with Bootstrapped and Weighted ECOC Classi ers,".=?E= )?JE 7EJ 4A?CEJE KIEC
+?= *E=HO 2=JJAH .A=JKHAI MEJD
+-++ +=IIEAHI
+55EJD
++AJHA BH 8EIE 5FAA?D 5EC= 2H?AIIEC 7ELAHIEJO B 5KHHAO
+5KHHAO /7  %:0 7
+)>IJH=?J 9EJDE JDA ?JANJ B=?A ANFHAIIE ?=IIE?=JE KIEC JDA
+B=?E= =?JE IOIJA .)+5 MA JDA FH>A B
+EC B=?E= =?JE KEJI )7I 6DA EI J JH=E = IECA
+AHHH?HHA?JEC KJFKJ -++ KJE?=II ?=IIEAH J AIJE=JA JDA
+FH>=>EEJEAI JD=J A=?D A B IALAH= ?O ??KHHEC )7 CHKFI EI
+FHAIAJ E JDA FH>A E=CA 2=JJ I?=EC EI J ?=E>H=JA JDA -++
+KJFKJI J FH>=>EEJEAI =FFHFHE=JA IKI B JDAIA FH>=>EEJEAI =HA
+J=A J >J=E = IAF=H=JA FH>=>EEJO BH A=?D )7 .A=JKHA
+ANJH=?JE EI >O CAAH=JEC = =HCA K>AH B ?= >E=HO F=J
+JAH *2 BA=JKHAI JDA IAA?JEC BH JDAIA KIEC B=IJ ?HHA=JE
+JAHEC .+*. 6DA >E=I L=HE=?A FHFAHJEAI B JDA ?=IIEAH
+=HA MA IDM JD=J >JD JDAIA IKH?AI B AHHH ?= >A HA
+>O AD=?EC -++ JDHKCD JDA =FFE?=JE B >JIJH=FFEC
+?=IIIAF=H=>EEJO MAECDJEC"
+03c56c176ec6377dddb6a96c7b2e95408db65a7a,A Novel Geometric Framework on Gram Matrix Trajectories for Human Behavior Understanding,"A Novel Geometric Framework on Gram Matrix
+Trajectories for Human Behavior Understanding
+Anis Kacem, Mohamed Daoudi, Boulbaba Ben Amor, Stefano Berretti, and Juan Carlos Alvarez-Paiva"
+0322e69172f54b95ae6a90eb3af91d3daa5e36ea,Face Classification using Adjusted Histogram in Grayscale,"Face Classiﬁcation using Adjusted Histogram in
+Grayscale
+Weenakorn Ieosanurak, and Watcharin Klongdee"
+03f7041515d8a6dcb9170763d4f6debd50202c2b,Clustering Millions of Faces by Identity,"Clustering Millions of Faces by Identity
+Charles Otto, Student Member, IEEE, Dayong Wang, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
+038ce930a02d38fb30d15aac654ec95640fe5cb0,Approximate structured output learning for Constrained Local Models with application to real-time facial feature detection and tracking on low-power devices,"Approximate Structured Output Learning for Constrained Local
+Models with Application to Real-time Facial Feature Detection and
+Tracking on Low-power Devices
+Shuai Zheng, Paul Sturgess and Philip H. S. Torr"
+03c1fc9c3339813ed81ad0de540132f9f695a0f8,Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification,"Proceedings of Machine Learning Research 81:1–15, 2018
+Conference on Fairness, Accountability, and Transparency
+Gender Shades: Intersectional Accuracy Disparities in
+Commercial Gender Classiﬁcation∗
+Joy Buolamwini
+MIT Media Lab 75 Amherst St. Cambridge, MA 02139
+Timnit Gebru
+Microsoft Research 641 Avenue of the Americas, New York, NY 10011
+Editors: Sorelle A. Friedler and Christo Wilson"
+0339459a5b5439d38acd9c40a0c5fea178ba52fb,Multimodal recognition of emotions in car environments,"D|C|I&I 2009 Prague
+Multimodal recognition of emotions in car
+environments
+Dragoş DatcuA and Léon J.M. RothkrantzB"
+032825000c03b8ab4c207e1af4daeb1f225eb025,A Novel Approach for Human Face Detection in Color Images Using Skin Color and Golden Ratio,"J. Appl. Environ. Biol. Sci., 7(10)159-164, 2017
+ISSN: 2090-4274
+© 2017, TextRoad Publication
+Journal of Applied Environmental
+nd Biological Sciences
+www.textroad.com
+A Novel Approach for Human Face Detection in Color Images Using Skin
+Color and Golden Ratio
+Faizan Ullah*1, Dilawar Shah1, Sabir Shah1, Abdus Salam2, Shujaat Ali1
+Department of Computer Science, Bacha Khan University, Charsadda, KPK, Pakistan1
+Department of Computer Science, Abdul WaliKhan University, Mardan, KPK, Pakistan2
+Received: May 9, 2017
+Accepted: August 2, 2017"
+03a8f53058127798bc2bc0245d21e78354f6c93b,Max-margin additive classifiers for detection,"Max-Margin Additive Classiﬁers for Detection
+Subhransu Maji and Alexander C. Berg
+Sam Hare
+VGG Reading Group
+October 30, 2009"
+03fc466fdbc8a2efb6e3046fcc80e7cb7e86dc20,A real time system for model-based interpretation of the dynamics of facial expressions,"A Real Time System for Model-based Interpretation of
+the Dynamics of Facial Expressions
+Christoph Mayer, Matthias Wimmer, Freek Stulp, Zahid Riaz, Anton Roth, Martin Eggers, Bernd Radig
+Technische Universit¨at M¨unchen
+Boltzmannstr. 3, 85748 Garching
+. Motivation
+Recent progress in the ﬁeld of Computer Vision allows
+intuitive interaction via speech, gesture or facial expressions
+etween humans and technical systems.Model-based tech-
+niques facilitate accurately interpreting images with faces
+y exploiting a priori knowledge, such as shape and texture
+information. This renders them an inevitable component
+to realize the paradigm of intuitive human-machine interac-
+tion.
+Our demonstration shows model-based recognition of
+facial expressions in real-time via the state-of-the-art
+Candide-3 face model [1] as visible in Figure 1. This three-
+dimensional and deformable model is highly appropriate
+for real-world face interpretation applications. However,
+its complexity challenges the task of model ﬁtting and we"
+03b98b4a2c0b7cc7dae7724b5fe623a43eaf877b,Acume: A Novel Visualization Tool for Understanding Facial Expression and Gesture Data,"Acume: A Novel Visualization Tool for Understanding Facial
+Expression and Gesture Data"
+03adcf58d947a412f3904a79f2ab51cfdf0e838a,Video-based face recognition: a survey,"World Journal of Science and Technology 2012, 2(4):136-139
+ISSN: 2231 – 2587
+Available Online: www.worldjournalofscience.com
+_________________________________________________________________
+Proceedings of ""Conference on Advances in Communication and Computing (NCACC'12)”
+Held at R.C.Patel Institute of Technology, Shirpur, Dist. Dhule,Maharastra,India.
+April 21, 2012
+Video-based face recognition: a survey
+Shailaja A Patil1 and Pramod J Deore2
+Department of Electronics and Telecommunication, R.C.Patel Institute of Technology,Shirpur,Dist.Dhule.Maharashtra,India."
+03f14159718cb495ca50786f278f8518c0d8c8c9,Performance evaluation of HOG and Gabor features for vision-based vehicle detection,"015 IEEE International Conference on Control System, Computing and Engineering, Nov 27 – Nov 29, 2015 Penang, Malaysia
+015 IEEE International Conference on Control System,
+Computing and Engineering (ICCSCE2015)
+Technical Session 1A – DAY 1 – 27th Nov 2015
+Time: 3.00 pm – 4.30 pm
+Venue: Jintan
+Topic: Signal and Image Processing
+.00 pm – 3.15pm
+.15 pm – 3.30pm
+.30 pm – 3.45pm
+.45 pm – 4.00pm
+.00 pm – 4.15pm
+.15 pm – 4.30pm
+.30 pm – 4.45pm
+A 01 ID3
+Can  Subspace  Based  Learning  Approach  Perform  on  Makeup  Face
+Recognition?
+Khor Ean Yee, Pang Ying Han, Ooi Shih Yin and Wee Kuok Kwee
+A 02 ID35
+Performance  Evaluation  of  HOG  and  Gabor  Features  for  Vision-based"
+0394040749195937e535af4dda134206aa830258,Geodesic entropic graphs for dimension and entropy estimation in manifold learning,"Geodesic Entropic Graphs for Dimension and
+Entropy Estimation in Manifold Learning
+Jose A. Costa and Alfred O. Hero III
+December 16, 2003"
+03ac1c694bc84a27621da6bfe73ea9f7210c6d45,Chapter 1 Introduction to information security foundations and applications,"Chapter 1
+Introduction to information security
+foundations and applications
+Ali Ismail Awad1,2
+.1 Background
+Information security has extended to include several research directions like user
+uthentication and authorization, network security, hardware security, software secu-
+rity, and data cryptography. Information security has become a crucial need for
+protecting almost all information transaction applications. Security is considered as
+n important science discipline whose many multifaceted complexities deserve the
+synergy of the computer science and engineering communities.
+Recently, due to the proliferation of Information and Communication Tech-
+nologies, information security has started to cover emerging topics such as cloud
+omputing security, smart cities’ security and privacy, healthcare and telemedicine,
+the Internet-of-Things (IoT) security [1], the Internet-of-Vehicles security, and sev-
+eral types of wireless sensor networks security [2,3]. In addition, information security
+has extended further to cover not only technical security problems but also social and
+organizational security challenges [4,5].
+Traditional systems’ development approaches were focusing on the system’s
+usability where security was left to the last stage with less priority. However, the"
+0394e684bd0a94fc2ff09d2baef8059c2652ffb0,Median Robust Extended Local Binary Pattern for Texture Classification,"Median Robust Extended Local Binary Pattern
+for Texture Classiﬁcation
+Li Liu, Songyang Lao, Paul W. Fieguth, Member, IEEE, Yulan Guo,
+Xiaogang Wang, and Matti Pietikäinen, Fellow, IEEE
+Index Terms— Texture descriptors, rotation invariance, local
+inary pattern (LBP), feature extraction, texture analysis.
+how the texture recognition process works in humans as
+well as in the important role it plays in the wide variety of
+pplications of computer vision and image analysis [1], [2].
+The many applications of texture classiﬁcation include medical
+image analysis and understanding, object recognition, biomet-
+rics, content-based image retrieval, remote sensing, industrial
+inspection, and document classiﬁcation.
+As a classical pattern recognition problem, texture classiﬁ-
+ation primarily consists of two critical subproblems: feature
+extraction and classiﬁer designation [1], [2]. It is generally
+greed that the extraction of powerful texture features plays a
+relatively more important role, since if poor features are used
+even the best classiﬁer will fail to achieve good recognition
+results. Consequently, most research in texture classiﬁcation"
+03f4c0fe190e5e451d51310bca61c704b39dcac8,CHEAVD: a Chinese natural emotional audio-visual database,"J Ambient Intell Human Comput
+DOI 10.1007/s12652-016-0406-z
+O R I G I N A L R E S E A R C H
+CHEAVD: a Chinese natural emotional audio–visual database
+Ya Li1
+• Jianhua Tao1,2,3
+• Linlin Chao1
+• Wei Bao1,4
+• Yazhu Liu1,4
+Received: 30 March 2016 / Accepted: 22 August 2016
+Ó Springer-Verlag Berlin Heidelberg 2016"
+031055c241b92d66b6984643eb9e05fd605f24e2,Multi-fold MIL Training for Weakly Supervised Object Localization,"Multi-fold MIL Training for Weakly Supervised Object Localization
+Ramazan Gokberk Cinbis
+Jakob Verbeek Cordelia Schmid
+Inria∗"
+0332ae32aeaf8fdd8cae59a608dc8ea14c6e3136,Large Scale 3D Morphable Models,"Int J Comput Vis
+DOI 10.1007/s11263-017-1009-7
+Large Scale 3D Morphable Models
+James Booth1
+Stefanos Zafeiriou1
+· Anastasios Roussos1,3 · Allan Ponniah2 · David Dunaway2 ·
+Received: 15 March 2016 / Accepted: 24 March 2017
+© The Author(s) 2017. This article is an open access publication"
+034addac4637121e953511301ef3a3226a9e75fd,Implied Feedback: Learning Nuances of User Behavior in Image Search,"Implied Feedback: Learning Nuances of User Behavior in Image Search
+Devi Parikh
+Virginia Tech"
+03701e66eda54d5ab1dc36a3a6d165389be0ce79,Improved Principal Component Regression for Face Recognition Under Illumination Variations,"Improved Principal Component Regression for Face
+Recognition Under Illumination Variations
+Shih-Ming Huang and Jar-Ferr Yang, Fellow, IEEE"
+9b318098f3660b453fbdb7a579778ab5e9118c4c,Joint Patch and Multi-label Learning for Facial Action Unit and Holistic Expression Recognition,"Joint Patch and Multi-label Learning for Facial
+Action Unit and Holistic Expression Recognition
+Kaili Zhao, Wen-Sheng Chu, Student Member, IEEE, Fernando De la Torre,
+Jeffrey F. Cohn, and Honggang Zhang, Senior Member, IEEE
+lassiﬁers without"
+9b474d6e81e3b94e0c7881210e249689139b3e04,VG-RAM Weightless Neural Networks for Face Recognition,"VG-RAM Weightless Neural Networks for
+Face Recognition
+Alberto F. De Souza, Claudine Badue, Felipe Pedroni, Stiven Schwanz Dias,
+Hallysson Oliveira and Soterio Ferreira de Souza
+Departamento de Inform´atica
+Universidade Federal do Esp´ırito Santo
+Av. Fernando Ferrari, 514, 29075-910 - Vit´oria-ES
+Brazil
+. Introduction
+Computerized human face recognition has many practical applications, such as access control,
+security monitoring, and surveillance systems, and has been one of the most challenging and
+ctive research areas in computer vision for many decades (Zhao et al.; 2003). Even though
+urrent machine recognition systems have reached a certain level of maturity, the recognition
+of faces with different facial expressions, occlusions, and changes in illumination and/or pose
+is still a hard problem.
+A general statement of the problem of machine recognition of faces can be formulated as fol-
+lows: given an image of a scene, (i) identify or (ii) verify one or more persons in the scene
+using a database of faces. In identiﬁcation problems, given a face as input, the system reports
+ack the identity of an individual based on a database of known individuals; whereas in veri-
+ﬁcation problems, the system conﬁrms or rejects the claimed identity of the input face. In both"
+9bcfadd22b2c84a717c56a2725971b6d49d3a804,How to Detect a Loss of Attention in a Tutoring System using Facial Expressions and Gaze Direction,"How to Detect a Loss of Attention in a Tutoring System
+using Facial Expressions and Gaze Direction
+Mark ter Maat"
+9b164cef4b4ad93e89f7c1aada81ae7af802f3a4,A Fully Automatic and Haar like Feature Extraction-Based Method for Lip Contour Detection,"Research Journal of Recent Sciences _________________________________________________ ISSN 2277-2502
+Vol. 2(1), 17-20, January (2013)
+Res.J.Recent Sci.
+A Fully Automatic and Haar like Feature Extraction-Based Method for Lip
+Contour Detection
+Zahedi Morteza and Mohamadian Zahra
+School of Computer Engineering, Shahrood University of Technology, Shahrood, IRAN
+Received 26th September 2012, revised 27th October 2012, accepted 6th November 2012
+Available online at: www.isca.in"
+9bac481dc4171aa2d847feac546c9f7299cc5aa0,Matrix Product State for Higher-Order Tensor Compression and Classification,"Matrix Product State for Higher-Order Tensor
+Compression and Classiﬁcation
+Johann A. Bengua1, Ho N. Phien1, Hoang D. Tuan1 and Minh N. Do2"
+9b7974d9ad19bb4ba1ea147c55e629ad7927c5d7,Faical Expression Recognition by Combining Texture and Geometrical Features,"Faical Expression Recognition by Combining
+Texture and Geometrical Features
+Renjie Liu, Ruofei Du, Bao-Liang Lu*"
+9b6d0b3fbf7d07a7bb0d86290f97058aa6153179,"NII , Japan at the first THUMOS Workshop 2013","NII, Japan at the ﬁrst THUMOS Workshop 2013
+Sang Phan, Duy-Dinh Le, Shin’ichi Satoh
+National Institute of Informatics
+-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, Japan 101-8430"
+9e8637a5419fec97f162153569ec4fc53579c21e,Segmentation and Normalization of Human Ears Using Cascaded Pose Regression,"Segmentation and Normalization of Human Ears
+using Cascaded Pose Regression
+Anika Pflug and Christoph Busch
+University of Applied Sciences Darmstadt - CASED,
+Haardtring 100,
+64295 Darmstadt, Germany
+http://www.h-da.de"
+9e4b052844d154c3431120ec27e78813b637b4fc,Local gradient pattern - A novel feature representation for facial expression recognition,"Journal of AI and Data Mining
+Vol. 2, No .1, 2014, 33-38.
+Local gradient pattern - A novel feature representation for facial
+expression recognition
+M. Shahidul Islam
+Department of Computer Science, School of Applied Statistics, National Institute of Development Administration, Bangkok, Thailand.
+Received 23 April 2013; accepted 16 June 2013
+*Corresponding author: (M.Shahidul Islam)"
+9ea73660fccc4da51c7bc6eb6eedabcce7b5cead,Talking head detection by likelihood-ratio test,"Talking Head Detection by Likelihood-Ratio Test†
+Carl Quillen, Kara Greenﬁeld, and William Campbell
+MIT Lincoln Laboratory,
+Lexington MA 02420, USA"
+9e9052256442f4e254663ea55c87303c85310df9,Review On Attribute - assisted Reranking for Image Search,"International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
+Volume 4 Issue 10, October 2015
+Review On Attribute-assisted Reranking for
+Image Search
+Waghmare Supriya, Wavhal Archana, Patil Nital, Tapkir Yogita, Prof. Yogesh Thorat"
+9ef2b2db11ed117521424c275c3ce1b5c696b9b3,Robust Face Alignment Using a Mixture of Invariant Experts,"Robust Face Alignment Using a Mixture of Invariant Experts
+Oncel Tuzel†
+Salil Tambe‡∗
+Tim K. Marks†
+Intel Corporation
+Mitsubishi Electric Research Labs (MERL)
+{oncel,"
+9e5acdda54481104aaf19974dca6382ed5ff21ed,Automatic localization of facial landmarks from expressive images of high complexity,"Yulia Gizatdinova and Veikko Surakka
+Automatic localization of facial
+landmarks from expressive images
+of high complexity
+DEPARTMENT OF COMPUTER SCIENCES
+UNIVERSITY OF TAMPERE
+D‐2008‐9
+TAMPERE 2008"
+9e0285debd4b0ba7769b389181bd3e0fd7a02af6,From Face Images and Attributes to Attributes,"From face images and attributes to attributes
+Robert Torfason, Eirikur Agustsson, Rasmus Rothe, Radu Timofte
+Computer Vision Laboratory, ETH Zurich, Switzerland"
+040dc119d5ca9ea3d5fc39953a91ec507ed8cc5d,Large-scale Bisample Learning on ID vs. Spot Face Recognition,"Noname manuscript No.
+(will be inserted by the editor)
+Large-scale Bisample Learning on ID vs. Spot Face Recognition
+Xiangyu Zhu∗ · Hao Liu∗ · Zhen Lei · Hailin Shi · Fan Yang · Dong
+Yi · Stan Z. Li
+Received: date / Accepted: date"
+047f6afa87f48de7e32e14229844d1587185ce45,An Improvement of Energy-Transfer Features Using DCT for Face Detection,"An Improvement of Energy-Transfer Features
+Using DCT for Face Detection
+Radovan Fusek, Eduard Sojka, Karel Mozdˇreˇn, and Milan ˇSurkala
+Technical University of Ostrava, FEECS, Department of Computer Science,
+7. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic"
+04b851f25d6d49e61a528606953e11cfac7df2b2,Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition,"Optical Flow Guided Feature: A Fast and Robust Motion Representation for
+Video Action Recognition
+Shuyang Sun1,2, Zhanghui Kuang2, Lu Sheng3, Wanli Ouyang1, Wei Zhang2
+The University of Sydney 2SenseTime Research 3The Chinese University of Hong Kong
+{shuyang.sun
+{wayne.zhang"
+0447bdb71490c24dd9c865e187824dee5813a676,Manifold Estimation in View-based Feature Space for Face Synthesis Across Pose,"Manifold Estimation in View-based Feature
+Space for Face Synthesis Across Pose
+Paper 27"
+0435a34e93b8dda459de49b499dd71dbb478dc18,"VEGAC: Visual Saliency-based Age, Gender, and Facial Expression Classification Using Convolutional Neural Networks","VEGAC: Visual Saliency-based Age, Gender, and Facial Expression Classification
+Using Convolutional Neural Networks
+Ayesha Gurnani£1, Vandit Gajjar£1, Viraj Mavani£1, Yash Khandhediya£1
+Department of Electronics and Communication Engineering and
+Computer Vision Group, L. D. College of Engineering, Ahmedabad, India
+{gurnani.ayesha.52, gajjar.vandit.381, mavani.viraj.604,
+the  need  for  handcrafted  facial  descriptors  and  data
+preprocessing.  D-CNN  models  have  been  not  only
+successfully  applied  to  human  face  analysis,  but  also  for
+the visual saliency detection [21, 22, 23]. Visual Saliency
+is  fundamentally  an  intensity  map  where  higher  intensity
+signifies  regions,  where  a  general  human  being  would
+look, and lower intensities mean decreasing level of visual
+ttention.  It’s  a  measure  of  visual  attention  of  humans
+ased  on  the  content  of  the  image.  It  has  numerous
+pplications  in  computer  vision  and  image  processing
+tasks. It is still an open problem when considering the MIT
+Saliency Benchmark [24].
+In  previous  five  years,  considering  age  estimation,
+gender  classification  and  facial  expression  classification"
+044ba70e6744e80c6a09fa63ed6822ae241386f2,Early Prediction for Physical Human Robot Collaboration in the Operating Room,"TO APPEAR IN AUTONOMOUS ROBOTS, SPECIAL ISSUE IN LEARNING FOR HUMAN-ROBOT COLLABORATION
+Early Prediction for Physical Human Robot
+Collaboration in the Operating Room
+Tian Zhou, Student Member, IEEE, and Juan Wachs, Member, IEEE"
+04dcdb7cb0d3c462bdefdd05508edfcff5a6d315,Assisting the training of deep neural networks with applications to computer vision,"Assisting the training of deep neural networks
+with applications to computer vision
+Adriana Romero
+tesi  doctoral  està  subjecta  a
+Aquesta
+CompartirIgual  4.0. Espanya de Creative Commons.
+Esta tesis doctoral está sujeta a la licencia  Reconocimiento - NoComercial – CompartirIgual
+.0.  España de Creative Commons.
+This  doctoral  thesis  is  licensed  under  the Creative  Commons  Attribution-NonCommercial-
+ShareAlike 4.0. Spain License.
+llicència Reconeixement-  NoComercial  –"
+044fdb693a8d96a61a9b2622dd1737ce8e5ff4fa,Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions,"Dynamic Texture Recognition Using Local Binary
+Patterns with an Application to Facial Expressions
+Guoying Zhao and Matti Pietik¨ainen, Senior Member, IEEE"
+04f55f81bbd879773e2b8df9c6b7c1d324bc72d8,Multi-view Face Analysis Based on Gabor Features,"Multi-view Face Analysis Based on Gabor Features
+Hongli Liu，  Weifeng Liu，  Yanjiang Wang
+College of Information and Control Engineering in China University of Petroleum,
+Qingdao 266580, China"
+0431e8a01bae556c0d8b2b431e334f7395dd803a,Learning Localized Perceptual Similarity Metrics for Interactive Categorization,"Learning Localized Perceptual Similarity Metrics for Interactive Categorization
+Catherine Wah ∗
+Google Inc.
+google.com"
+04b4c779b43b830220bf938223f685d1057368e9,Video retrieval based on deep convolutional neural network,"Video retrieval based on deep convolutional
+neural network
+Yajiao Dong
+School of Information and Electronics,
+Beijing Institution of Technology, Beijing, China
+Jianguo Li
+School of Information and Electronics,
+Beijing Institution of Technology, Beijing, China"
+04616814f1aabe3799f8ab67101fbaf9fd115ae4,UNIVERSITÉ DE CAEN BASSE NORMANDIE U . F . R . de Sciences,"UNIVERSIT´EDECAENBASSENORMANDIEU.F.R.deSciences´ECOLEDOCTORALESIMEMTH`ESEPr´esent´eeparM.GauravSHARMAsoutenuele17D´ecembre2012envuedel’obtentionduDOCTORATdel’UNIVERSIT´EdeCAENSp´ecialit´e:InformatiqueetapplicationsArrˆet´edu07aoˆut2006Titre:DescriptionS´emantiquedesHumainsPr´esentsdansdesImagesVid´eo(SemanticDescriptionofHumansinImages)TheworkpresentedinthisthesiswascarriedoutatGREYC-UniversityofCaenandLEAR–INRIAGrenobleJuryM.PatrickPEREZDirecteurdeRechercheINRIA/Technicolor,RennesRapporteurM.FlorentPERRONNINPrincipalScientistXeroxRCE,GrenobleRapporteurM.JeanPONCEProfesseurdesUniversit´esENS,ParisExaminateurMme.CordeliaSCHMIDDirectricedeRechercheINRIA,GrenobleDirectricedeth`eseM.Fr´ed´ericJURIEProfesseurdesUniversit´esUniversit´edeCaenDirecteurdeth`ese"
+047d7cf4301cae3d318468fe03a1c4ce43b086ed,Co-Localization of Audio Sources in Images Using Binaural Features and Locally-Linear Regression,"Co-Localization of Audio Sources in Images Using
+Binaural Features and Locally-Linear Regression
+Antoine Deleforge, Radu Horaud, Yoav Y. Schechner, Laurent Girin
+To cite this version:
+Antoine Deleforge, Radu Horaud, Yoav Y. Schechner, Laurent Girin. Co-Localization of Audio
+Sources in Images Using Binaural Features and Locally-Linear Regression. IEEE Transactions
+on Audio Speech and Language Processing, 2015, 15p. <hal-01112834>
+HAL Id: hal-01112834
+https://hal.inria.fr/hal-01112834
+Submitted on 3 Feb 2015
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entiﬁc research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destin´ee au d´epˆot et `a la diffusion de documents
+scientiﬁques de niveau recherche, publi´es ou non,
+´emanant des ´etablissements d’enseignement et de"
+04317e63c08e7888cef480fe79f12d3c255c5b00,Face Recognition Using a Unified 3D Morphable Model,"Face Recognition Using a Unified 3D Morphable Model
+Hu, G., Yan, F., Chan, C-H., Deng, W., Christmas, W., Kittler, J., & Robertson, N. M. (2016). Face Recognition
+Using a Unified 3D Morphable Model. In Computer Vision – ECCV 2016: 14th European Conference,
+Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VIII (pp. 73-89). (Lecture Notes in
+Computer Science; Vol. 9912). Springer Verlag. DOI: 10.1007/978-3-319-46484-8_5
+Published in:
+Computer Vision – ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14,
+016, Proceedings, Part VIII
+Document Version:
+Peer reviewed version
+Queen's University Belfast - Research Portal:
+Link to publication record in Queen's University Belfast Research Portal
+Publisher rights
+The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-46484-8_5
+General rights
+Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other
+opyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated
+with these rights.
+Take down policy
+The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to"
+0470b0ab569fac5bbe385fa5565036739d4c37f8,Automatic face naming with caption-based supervision,"Automatic Face Naming with Caption-based Supervision
+Matthieu Guillaumin, Thomas Mensink, Jakob Verbeek, Cordelia Schmid
+To cite this version:
+Matthieu Guillaumin, Thomas Mensink, Jakob Verbeek, Cordelia Schmid. Automatic Face Naming
+with Caption-based Supervision. CVPR 2008 - IEEE Conference on Computer Vision
+Pattern Recognition,
+iety,
+<10.1109/CVPR.2008.4587603>. <inria-00321048v2>
+008,
+pp.1-8,
+008, Anchorage, United
+<http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4587603>.
+IEEE Computer
+States.
+HAL Id: inria-00321048
+https://hal.inria.fr/inria-00321048v2
+Submitted on 11 Apr 2011
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entific research documents, whether they are pub-"
+6a3a07deadcaaab42a0689fbe5879b5dfc3ede52,Learning to Estimate Pose by Watching Videos,"Learning to Estimate Pose by Watching Videos
+Prabuddha Chakraborty and Vinay P. Namboodiri
+Department of Computer Science and Engineering
+IIT Kanpur
+{prabudc, vinaypn}"
+6afed8dc29bc568b58778f066dc44146cad5366c,Kernel Hebbian Algorithm for Single-Frame Super-Resolution,"Kernel Hebbian Algorithm for Single-Frame
+Super-Resolution
+Kwang In Kim1, Matthias O. Franz1, and Bernhard Sch¨olkopf1
+Max Planck Institute f¨ur biologische Kybernetik
+Spemannstr. 38, D-72076 T¨ubingen, Germany
+{kimki, mof,
+http://www.kyb.tuebingen.mpg.de/"
+6a16b91b2db0a3164f62bfd956530a4206b23fea,A Method for Real-Time Eye Blink Detection and Its Application,"A Method for Real-Time Eye Blink Detection and Its Application
+Chinnawat Devahasdin Na Ayudhya
+Mahidol Wittayanusorn School
+Puttamonton, Nakornpatom 73170, Thailand"
+6a806978ca5cd593d0ccd8b3711b6ef2a163d810,Facial Feature Tracking for Emotional Dynamic Analysis,"Facial feature tracking for Emotional Dynamic
+Analysis
+Thibaud Senechal1, Vincent Rapp1, and Lionel Prevost2
+ISIR, CNRS UMR 7222
+Univ. Pierre et Marie Curie, Paris
+{rapp,
+LAMIA, EA 4540
+Univ. of Fr. West Indies & Guyana"
+6a8a3c604591e7dd4346611c14dbef0c8ce9ba54,An Affect-Responsive Interactive Photo Frame,"ENTERFACE’10, JULY 12TH - AUGUST 6TH, AMSTERDAM, THE NETHERLANDS.
+An Affect-Responsive Interactive Photo Frame
+Hamdi Dibeklio˘glu, Ilkka Kosunen, Marcos Ortega Hortas, Albert Ali Salah, Petr Zuz´anek"
+6a52e6fce541126ff429f3c6d573bc774f5b8d89,Role of Facial Emotion in Social Correlation,"Role of Facial Emotion in Social Correlation
+Pankaj Mishra, Raﬁk Hadﬁ, and Takayuki Ito
+Department of Computer Science and Engineering
+Nagoya Institute of Technology, Gokiso, Showa-ku, Nagoya, 466-8555 Japan
+{pankaj.mishra,"
+6aefe7460e1540438ffa63f7757c4750c844764d,Non-rigid Segmentation Using Sparse Low Dimensional Manifolds and Deep Belief Networks,"Non-rigid Segmentation using Sparse Low Dimensional Manifolds and
+Deep Belief Networks ∗
+Jacinto C. Nascimento
+Instituto de Sistemas e Rob´otica
+Instituto Superior T´ecnico, Portugal"
+6a7e464464f70afea78552c8386f4d2763ea1d9c,Facial Landmark Localization – A Literature Survey,"Review Article
+International Journal of Current Engineering and Technology
+E-ISSN 2277 – 4106, P-ISSN 2347 - 5161
+©2014 INPRESSCO
+, All Rights Reserved
+Available at http://inpressco.com/category/ijcet
+Facial Landmark Localization – A Literature Survey
+Dhananjay RathodȦ*, Vinay A, Shylaja SSȦ and S NatarajanȦ
+ȦDepartment of Information Science and Engineering, PES Institute of Technology, Bangalore, Karnataka, India
+Accepted 25 May 2014, Available online 01 June2014, Vol.4, No.3 (June 2014)"
+32925200665a1bbb4fc8131cd192cb34c2d7d9e3,An Active Appearance Model with a Derivative-Free Optimization,"MVA2009 IAPR Conference on Machine Vision Applications, May 20-22, 2009, Yokohama, JAPAN
+An Active Appearance Model with a Derivative-Free
+Optimization
+Jixia ZHANG‡, Franck DAVOINE†, Chunhong PAN‡
+CNRS†, Institute of Automation of the Chinese Academy of Sciences‡
+95, Zhongguancun Dong Lu, PO Box 2728 − Beijing 100190 − PR China
+LIAMA Sino-French IT Lab."
+322c063e97cd26f75191ae908f09a41c534eba90,Improving Image Classification Using Semantic Attributes,"Noname manuscript No.
+(will be inserted by the editor)
+Improving Image Classiﬁcation using Semantic Attributes
+Yu Su · Fr´ed´eric Jurie
+Received: date / Accepted: date"
+325b048ecd5b4d14dce32f92bff093cd744aa7f8,Multi-Image Graph Cut Clothing Segmentation for Recognizing People,"#2670
+CVPR 2008 Submission #2670. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
+#2670
+Multi-Image Graph Cut Clothing Segmentation for Recognizing People
+Anonymous CVPR submission
+Paper ID 2670"
+32f7e1d7fa62b48bedc3fcfc9d18fccc4074d347,Hierarchical Sparse and Collaborative Low-Rank representation for emotion recognition,"HIERARCHICAL SPARSE AND COLLABORATIVE LOW-RANK REPRESENTATION FOR
+EMOTION RECOGNITION
+Xiang Xiang, Minh Dao, Gregory D. Hager, Trac D. Tran
+Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA
+{xxiang, minh.dao, ghager1,"
+321bd4d5d80abb1bae675a48583f872af3919172,Entropy-weighted feature-fusion method for head-pose estimation,"Wang et al. EURASIP Journal on Image and Video Processing  (2016) 2016:44
+DOI 10.1186/s13640-016-0152-3
+EURASIP Journal on Image
+nd Video Processing
+R EV I E W
+Entropy-weighted feature-fusion method
+for head-pose estimation
+Xiao-Meng Wang*, Kang Liu and Xu Qian
+Open Access"
+32575ffa69d85bbc6aef5b21d73e809b37bf376d,Measuring Biometric Sample Quality in Terms of Biometric Information,"-)5741/ *1-641+ 5)2- 37)16; 1 6-45 . *1-641+ 1.4)61
+;K=H=
+5?D B 1BH=JE 6A?DCO -CEAAHEC
+7ELAHIEJO B JJ=M=
+J=HE
+)*564)+6
+6DEI F=FAH = AM =FFH=?D J A=
+IKHA L=HE=JEI E >EAJHE? I=FA GK=EJO 9A >ACE MEJD
+JDA EJKEJE JD=J J = >EAJHE? I=FA ME HA
+JDA =KJ B EBH=JE =L=E=>A 1 H
+J A=IKHA JDA =KJ B EBH=JE MA
+>EAJHE? EBH=JE =I JDA E K?AHJ=EJO
+=>KJ JDA B = FAHI J = IAJ B >EAJHE? A=
+IKHAAJI 9A JDA IDM JD=J JDA >EAJHE? EBH=JE BH
+= FAHI =O >A >O JDA HA=JELA AJHFO D(p(cid:107)q)
+>AJMAA JDA FFK=JE BA=JKHA q JDA FAHII
+BA=JKHA p 6DA >EAJHE? EBH=JE BH = IOI
+JA EI JDA A= D(p(cid:107)q) BH = FAHII E JDA FFK=JE 1
+J FH=?JE?=O A=IKHA D(p(cid:107)q) MEJD I=
+FAI MA = =CHEJD MDE?D HACK=HEAI = /=KIIE="
+32728e1eb1da13686b69cc0bd7cce55a5c963cdd,Automatic Facial Emotion Recognition Method Based on Eye Region Changes,"Automatic Facial Emotion Recognition Method Based on Eye
+Region Changes
+Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran
+Mina Navraan
+Nasrollah Moghadam Charkari*
+Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran
+Muharram Mansoorizadeh
+Faculty of Electrical and Computer Engineering, Bu-Ali Sina University, Hamadan, Iran
+Received: 19/Apr/2015            Revised: 19/Mar/2016            Accepted: 19/Apr/2016"
+324b9369a1457213ec7a5a12fe77c0ee9aef1ad4,Dynamic Facial Analysis: From Bayesian Filtering to Recurrent Neural Network,"Dynamic Facial Analysis: From Bayesian Filtering to Recurrent Neural Network
+Jinwei Gu Xiaodong Yang Shalini De Mello Jan Kautz
+NVIDIA"
+32df63d395b5462a8a4a3c3574ae7916b0cd4d1d,Facial expression recognition using ensemble of classifiers,"978-1-4577-0539-7/11/$26.00 ©2011 IEEE
+ICASSP 2011"
+35308a3fd49d4f33bdbd35fefee39e39fe6b30b7,Efficient and effective human action recognition in video through motion boundary description with a compact set of trajectories,"biblio.ugent.be   The UGent Institutional Repository is the electronic archiving and dissemination platform for allUGent research publications. Ghent University has implemented a mandate stipulating that allacademic publications of UGent researchers should be deposited and archived in this repository.Except for items where current copyright restrictions apply, these papers are available in OpenAccess.   This item is the archived peer-reviewed author-version of:   Efficient and effective human action recognition in video through motion boundary description witha compact set of trajectories   Jeong-Jik Seo, Jisoo Son, Hyung-Il Kim, Wesley De Neve, and Yong Man Ro   In: 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition,1, 1-6, 2015.     To refer to or to cite this work, please use the citation to the published version:   Seo, J., Son, J., Kim, H., De Neve, W., and Ro, Y. M. (2015). Efficient and effective human actionrecognition in video through motion boundary description with a compact set of trajectories. 11thIEEE International Conference and Workshops on Automatic Face and Gesture Recognition 1 1-6.http://dx.doi.org/10.1109/FG.2015.7163123"
+352d61eb66b053ae5689bd194840fd5d33f0e9c0,Analysis Dictionary Learning based Classification: Structure for Robustness,"Analysis Dictionary Learning based
+Classiﬁcation: Structure for Robustness
+Wen Tang, Ashkan Panahi, Hamid Krim, and Liyi Dai"
+3538d2b5f7ab393387ce138611ffa325b6400774,A DSP-based approach for the implementation of face recognition algorithms,"A DSP-BASED APPROACH FOR THE IMPLEMENTATION OF FACE RECOGNITION
+ALGORITHMS
+A. U. Batur
+B. E. Flinchbaugh
+M. H. Hayes IIl
+Center for Signal and Image Proc.
+Georgia Inst. Of Technology
+Atlanta, GA
+Imaging and Audio Lab.
+Texas Instruments
+Dallas, TX
+Center for Signal and Image Proc.
+Georgia Inst. Of Technology
+Atlanta, CA"
+3504907a2e3c81d78e9dfe71c93ac145b1318f9c,Unconstrained Still/Video-Based Face Verification with Deep Convolutional Neural Networks,"Noname manuscript No.
+(will be inserted by the editor)
+Unconstrained Still/Video-Based Face Veriﬁcation with Deep
+Convolutional Neural Networks
+Jun-Cheng Chen∗
+Kumar∗ · Ching-Hui Chen∗ · Vishal M. Patel · Carlos D. Castillo ·
+Rama Chellappa
+· Rajeev Ranjan∗ · Swami Sankaranarayanan∗ · Amit
+Received: date / Accepted: date"
+35b1c1f2851e9ac4381ef41b4d980f398f1aad68,Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning,"Geometry Guided Convolutional Neural Networks for
+Self-Supervised Video Representation Learning
+Chuang Gan1, Boqing Gong2, Kun Liu3, Hao Su 4, Leonidas J. Guibas 5
+MIT-IBM Watson AI Lab , 2 Tencent AI Lab, 3 BUPT, 4 UCSD, 5 Stanford University"
+351c02d4775ae95e04ab1e5dd0c758d2d80c3ddd,ActionSnapping: Motion-Based Video Synchronization,"ActionSnapping: Motion-based Video
+Synchronization
+Jean-Charles Bazin and Alexander Sorkine-Hornung
+Disney Research"
+35e4b6c20756cd6388a3c0012b58acee14ffa604,Gender Classification in Large Databases,"Gender Classiﬁcation in Large Databases
+E. Ram´on-Balmaseda, J. Lorenzo-Navarro, and M. Castrill´on-Santana (cid:63)
+Universidad de Las Palmas de Gran Canaria
+SIANI
+Spain"
+35f084ddee49072fdb6e0e2e6344ce50c02457ef,A bilinear illumination model for robust face recognition,"A Bilinear Illumination Model
+for Robust Face Recognition
+The Harvard community has made this
+rticle openly available.  Please share  how
+this access benefits you. Your story matters
+Citation
+Lee, Jinho, Baback Moghaddam, Hanspeter Pfister, and Raghu
+Machiraju. 2005. A bilinear illumination model for robust face
+recognition. Proceedings of the Tenth IEEE International Conference
+on Computer Vision: October 17-21, 2005, Beijing, China. 1177-1184.
+Los Almamitos, C.A.: IEEE Computer Society.
+Published Version
+doi:10.1109/ICCV.2005.5
+Citable link
+http://nrs.harvard.edu/urn-3:HUL.InstRepos:4238979
+Terms of Use
+This article was downloaded from Harvard University’s DASH
+repository, and is made available under the terms and conditions
+pplicable to Other Posted Material, as set forth at http://
+nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-"
+353a89c277cca3e3e4e8c6a199ae3442cdad59b5,Learning from Multiple Views of Data,
+35e6f6e5f4f780508e5f58e87f9efe2b07d8a864,Summarization of User-Generated Sports Video by Using Deep Action Recognition Features,"This paper is a preprint (IEEE accepted status). IEEE copyright notice. 2018 IEEE.
+Personal use of this material is permitted. Permission from IEEE must be obtained for all
+other uses, in any current or future media, including reprinting/republishing this material for
+dvertising or promotional purposes, creating new collective works, for resale or redistribu-
+tion to servers or lists, or reuse of any copyrighted.
+A. Tejero-de-Pablos, Y. Nakashima, T. Sato, N. Yokoya, M. Linna and E. Rahtu, ”Sum-
+marization of User-Generated Sports Video by Using Deep Action Recognition Features,” in
+doi: 10.1109/TMM.2018.2794265
+keywords: Cameras; Feature extraction; Games; Hidden Markov models; Semantics;
+Three-dimensional displays; 3D convolutional neural networks; Sports video summarization;
+ction recognition; deep learning; long short-term memory; user-generated video,
+URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8259321&isnumber=4456689"
+352110778d2cc2e7110f0bf773398812fd905eb1,Matrix Completion for Weakly-Supervised Multi-Label Image Classification,"TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. X, NO. X, JUNE 2014
+Matrix Completion for Weakly-supervised
+Multi-label Image Classiﬁcation
+Ricardo Cabral, Fernando De la Torre, João P. Costeira, Alexandre Bernardino"
+6964af90cf8ac336a2a55800d9c510eccc7ba8e1,Temporal Relational Reasoning in Videos,"Temporal Relational Reasoning in Videos
+Bolei Zhou, Alex Andonian, Aude Oliva, Antonio Torralba
+MIT CSAIL"
+69ff40fd5ce7c3e6db95a2b63d763edd8db3a102,Human Age Estimation via Geometric and Textural Features,"HUMAN AGE ESTIMATION VIA GEOMETRIC AND TEXTURAL
+FEATURES
+Merve KILINC1 and Yusuf Sinan AKGUL2
+TUBITAK BILGEM UEKAE, Anibal Street, 41470, Gebze, Kocaeli, Turkey
+GIT Vision Lab, http://vision.gyte.edu.tr/, Department of Computer Engineering, Gebze Institute of Technology, 41400,
+Kocaeli, Turkey
+Keywords:
+Age estimation:age classiﬁcation:geometric features:LBP:Gabor:LGBP:cross ratio:FGNET:MORPH"
+69d29012d17cdf0a2e59546ccbbe46fa49afcd68,Subspace clustering of dimensionality-reduced data,"Subspace clustering of dimensionality-reduced data
+Reinhard Heckel, Michael Tschannen, and Helmut B¨olcskei
+ETH Zurich, Switzerland
+Email:"
+69a55c30c085ad1b72dd2789b3f699b2f4d3169f,Automatic Happiness Strength Analysis of a Group of People using Facial Expressions,"International Journal of Computer Trends and Technology (IJCTT) – Volume 34 Number 3 - April 2016
+Automatic Happiness Strength Analysis of a
+Group of People using Facial Expressions
+Sagiri Prasanthi#1, Maddali M.V.M. Kumar*2,
+#1PG Student, #2Assistant Professor
+#1, #2Department of MCA, St. Ann’s College of Engineering & Technology, Andhra Pradesh, India
+is  a  collective  concern"
+69526cdf6abbfc4bcd39616acde544568326d856,Face Verification Using Template Matching,"[17] B. Moghaddam, T. Jebara, and A. Pentland, “Bayesian face recogni-
+tion,” Pattern Recognit., vol. 33, no. 11, pp. 1771–1782, Nov. 2000.
+[18] A. Neﬁan, “A hidden Markov model-based approach for face detection
+nd recognition,” Ph.D. dissertation, Dept. Elect. Comput. Eng. Elect.
+Eng., Georgia Inst. Technol., Atlanta, 1999.
+[19] P. J. Phillips et al., “Overview of the face recognition grand challenge,”
+presented at the IEEE CVPR, San Diego, CA, Jun. 2005.
+[20] H. T. Tanaka, M. Ikeda, and H. Chiaki, “Curvature-based face surface
+recognition using spherical correlation-principal direction for curved
+object recognition,” in Proc. Int. Conf. Automatic Face and Gesture
+Recognition, 1998, pp. 372–377.
+[21] M. Turk and A. Pentland, “Eigenfaces for recognition,” J. Cognit. Sci.,
+pp. 71–86, 1991.
+[22] V. N. Vapnik, Statistical Learning Theory. New York: Wiley, 1998.
+[23] W. Zhao, R. Chellappa, A. Rosenfeld, and P. Phillips, “Face recogni-
+tion: A literature survey,” ACM Comput. Surveys, vol. 35, no. 44, pp.
+99–458, 2003.
+[24] W. Zhao, R. Chellappa, and P. J. Phillips, “Subspace linear discrimi-
+nant analysis for face recognition,” UMD TR4009, 1999.
+Face Veriﬁcation Using Template Matching"
+690d669115ad6fabd53e0562de95e35f1078dfbb,"Progressive versus Random Projections for Compressive Capture of Images, Lightfields and Higher Dimensional Visual Signals","Progressive versus Random Projections for Compressive Capture of Images,
+Lightﬁelds and Higher Dimensional Visual Signals
+Rohit Pandharkar
+MIT Media Lab
+75 Amherst St, Cambridge, MA
+Ashok Veeraraghavan
+01 Broadway, Cambridge MA
+Ramesh Raskar
+MIT Media Lab
+75 Amherst St, Cambridge, MA"
+69063f7e0a60ad6ce16a877bc8f11b59e5f7348e,Class-Specific Image Deblurring,"Class-Speciﬁc Image Deblurring
+Saeed Anwar1, Cong Phuoc Huynh1
+, Fatih Porikli1
+The Australian National University∗ Canberra ACT 2601, Australia
+NICTA, Locked Bag 8001, Canberra ACT 2601, Australia"
+3cb2841302af1fb9656f144abc79d4f3d0b27380,When 3 D-Aided 2 D Face Recognition Meets Deep Learning : An extended UR 2 D for Pose-Invariant Face Recognition,"See	discussions,	stats,	and	author	profiles	for	this	publication	at:	https://www.researchgate.net/publication/319928941
+When	3D-Aided	2D	Face	Recognition	Meets	Deep
+Learning:	An	extended	UR2D	for	Pose-Invariant
+Face	Recognition
+Article	·	September	2017
+CITATIONS
+authors:
+READS
+Xiang	Xu
+University	of	Houston
+Pengfei	Dou
+University	of	Houston
+8	PUBLICATIONS			10	CITATIONS
+9	PUBLICATIONS			29	CITATIONS
+SEE	PROFILE
+SEE	PROFILE
+Ha	Le
+University	of	Houston
+7	PUBLICATIONS			2	CITATIONS
+Ioannis	A	Kakadiaris"
+3cfbe1f100619a932ba7e2f068cd4c41505c9f58,A Realistic Simulation Tool for Testing Face Recognition Systems under Real-World Conditions,"A Realistic Simulation Tool for Testing Face Recognition
+Systems under Real-World Conditions∗
+M. Correa, J. Ruiz-del-Solar, S. Parra-Tsunekawa, R. Verschae
+Department of Electrical Engineering, Universidad de Chile
+Advanced Mining Technology Center, Universidad de Chile"
+3cd7b15f5647e650db66fbe2ce1852e00c05b2e4,"ACTIVE, an Extensible Cataloging Platform for Automatic Indexing of Audiovisual Content",
+3c374cb8e730b64dacb9fbf6eb67f5987c7de3c8,Measuring Gaze Orientation for Human-Robot Interaction,"Measuring Gaze Orientation for Human-Robot
+Interaction
+R. Brochard∗, B. Burger∗, A. Herbulot∗†, F. Lerasle∗†
+CNRS; LAAS; 7 avenue du Colonel Roche, 31077 Toulouse Cedex, France
+Universit´e de Toulouse; UPS; LAAS-CNRS : F-31077 Toulouse, France
+Introduction
+In the context of Human-Robot interaction estimating gaze orientation brings
+useful information about human focus of attention. This is a contextual infor-
+mation : when you point something you usually look at it. Estimating gaze
+orientation requires head pose estimation. There are several techniques to esti-
+mate head pose from images, they are mainly based on training [3, 4] or on local
+face features tracking [6]. The approach described here is based on local face
+features tracking in image space using online learning, it is a mixed approach
+since we track face features using some learning at feature level. It uses SURF
+features [2] to guide detection and tracking. Such key features can be matched
+etween images, used for object detection or object tracking [10]. Several ap-
+proaches work on ﬁxed size images like training techniques which mainly work
+on low resolution images because of computation costs whereas approaches based
+on local features tracking work on high resolution images. Tracking face features
+such as eyes, nose and mouth is a common problem in many applications such as"
+3c0bbfe664fb083644301c67c04a7f1331d9515f,The Role of Color and Contrast in Facial Age Estimation,"The Role of Color and Contrast in Facial Age Estimation
+Paper ID: 7
+No Institute Given"
+3c4f6d24b55b1fd3c5b85c70308d544faef3f69a,A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics,"A Hybrid Deep Learning Architecture for
+Privacy-Preserving Mobile Analytics
+Seyed Ali Ossia(cid:63), Ali Shahin Shamsabadi(cid:63), Ali Taheri(cid:63), Hamid R. Rabiee(cid:63),
+Nic Lane‡, Hamed Haddadi†
+(cid:63)Sharif University of Technology, ‡University College London, †Queen Mary University of London"
+3cb0ef5aabc7eb4dd8d32a129cb12b3081ef264f,Absolute Head Pose Estimation From Overhead Wide-Angle Cameras,"Absolute Head Pose Estimation From Overhead Wide-Angle Cameras
+Ying-Li Tian, Lisa Brown, Jonathan Connell,
+Sharat Pankanti, Arun Hampapur, Andrew Senior, Ruud Bolle
+IBM T.J. Watson Research Center
+9 Skyline Drive, Hawthorne, NY 10532 USA
+{ yltian,lisabr,jconnell,sharat,arunh,aws,bolle"
+3c56acaa819f4e2263638b67cea1ec37a226691d,Body Joint Guided 3-D Deep Convolutional Descriptors for Action Recognition,"Body Joint guided 3D Deep Convolutional
+Descriptors for Action Recognition
+Congqi Cao, Yifan Zhang, Member, IEEE, Chunjie Zhang, Member, IEEE, and Hanqing Lu, Senior Member, IEEE"
+3c8da376576938160cbed956ece838682fa50e9f,Aiding face recognition with social context association rule based re-ranking,"Chapter 4
+Aiding Face Recognition with
+Social Context Association Rule
+ased Re-Ranking
+Humans are very ef‌f‌icient at recognizing familiar face images even in challenging condi-
+tions. One reason for such capabilities is the ability to understand social context between
+individuals. Sometimes the identity of the person in a photo can be inferred based on the
+identity of other persons in the same photo, when some social context between them is
+known. This chapter presents an algorithm to utilize the co-occurrence of individuals as
+the social context to improve face recognition. Association rule mining is utilized to infer
+multi-level social context among subjects from a large repository of social transactions.
+The results are demonstrated on the G-album and on the SN-collection pertaining to 4675
+identities prepared by the authors from a social networking website. The results show that
+ssociation rules extracted from social context can be used to augment face recognition and
+improve the identiﬁcation performance.
+Introduction
+Face recognition capabilities of humans have inspired several researchers to understand
+the science behind it and use it in developing automated algorithms. Recently, it is also
+rgued that encoding social context among individuals can be leveraged for improved
+utomatic face recognition [175]. As shown in Figure 4.1, often times a person’s identity"
+56e4dead93a63490e6c8402a3c7adc493c230da5,Face Recognition Techniques: A Survey,"World Journal of Computer Application and Technology 1(2): 41-50, 2013
+DOI: 10.13189/wjcat.2013.010204
+http://www.hrpub.org
+Face Recognition Techniques: A Survey
+V.Vijayakumari
+Department of Electronics and Communication, Sri krishna College of Technology, Coimbatore, India
+*Corresponding Author:
+Copyright © 2013 Horizon Research Publishing All rights reserved."
+56e885b9094391f7d55023a71a09822b38b26447,Face Retrieval using Frequency Decoded Local Descriptor,"FREQUENCY DECODED LOCAL BINARY PATTERN
+Face Retrieval using Frequency Decoded Local
+Descriptor
+Shiv Ram Dubey, Member, IEEE"
+56a653fea5c2a7e45246613049fb16b1d204fc96,Quaternion Collaborative and Sparse Representation With Application to Color Face Recognition,"Quaternion Collaborative and Sparse Representation
+With Application to Color Face Recognition
+Cuiming Zou, Kit Ian Kou, Member, IEEE, and Yulong Wang, Student Member, IEEE
+representation-based"
+5666ed763698295e41564efda627767ee55cc943,Relatively-Paired Space Analysis: Learning a Latent Common Space From Relatively-Paired Observations,"Manuscript
+Click here to download Manuscript: template.tex
+Click here to view linked References
+Noname manuscript No.
+(will be inserted by the editor)
+Relatively-Paired Space Analysis: Learning a Latent Common
+Space from Relatively-Paired Observations
+Zhanghui Kuang · Kwan-Yee K. Wong
+Received: date / Accepted: date"
+5615d6045301ecbc5be35e46cab711f676aadf3a,Discriminatively Learned Hierarchical Rank Pooling Networks,"Discriminatively Learned Hierarchical Rank Pooling Networks
+Basura Fernando · Stephen Gould
+Received: date / Accepted: date"
+566038a3c2867894a08125efe41ef0a40824a090,Face recognition and gender classification in personal memories,"978-1-4244-2354-5/09/$25.00 ©2009 IEEE
+ICASSP 2009"
+56dca23481de9119aa21f9044efd7db09f618704,Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices,"Riemannian Dictionary Learning and Sparse
+Coding for Positive Deﬁnite Matrices
+Anoop Cherian
+Suvrit Sra"
+516a27d5dd06622f872f5ef334313350745eadc3,Fine-Grained Facial Expression Analysis Using Dimensional Emotion Model,"> REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) <
+Fine-Grained Facial Expression Analysis Us-
+ing Dimensional Emotion Model
+ǂFeng Zhou, ǂShu Kong, Charless C. Fowlkes, Tao Chen, *Baiying Lei, Member, IEEE"
+51c3050fb509ca685de3d9ac2e965f0de1fb21cc,Fantope Regularization in Metric Learning,"Fantope Regularization in Metric Learning
+Marc T. Law
+Nicolas Thome
+Matthieu Cord
+Sorbonne Universit´es, UPMC Univ Paris 06, UMR 7606, LIP6, F-75005, Paris, France"
+51c7c5dfda47647aef2797ac3103cf0e108fdfb4,Cs 395t: Celebrity Look-alikes *,"CS 395T: Celebrity Look-Alikes ∗
+Adrian Quark"
+519f4eb5fe15a25a46f1a49e2632b12a3b18c94d,Non-Lambertian Reflectance Modeling and Shape Recovery of Faces Using Tensor Splines,"Non-Lambertian Reflectance Modeling and
+Shape Recovery of Faces using Tensor Splines
+Ritwik Kumar, Student Member, IEEE, Angelos Barmpoutis, Member, IEEE,
+Arunava Banerjee, Member, IEEE, and Baba C. Vemuri, Fellow, IEEE"
+51cc78bc719d7ff2956b645e2fb61bab59843d2b,Face and Facial Expression Recognition with an Embedded System for Human-Robot Interaction,"Face and Facial Expression Recognition with an
+Embedded System for Human-Robot Interaction
+Yang-Bok Lee1, Seung-Bin Moon1, and Yong-Guk Kim 1*
+School of Computer Engineering, Sejong University, Seoul, Korea"
+511b06c26b0628175c66ab70dd4c1a4c0c19aee9,Face Recognition using Laplace Beltrami Operator by Optimal Linear Approximations,"International Journal of Engineering Research and General ScienceVolume 2, Issue 5, August – September 2014
+ISSN 2091-2730
+Face Recognition using Laplace Beltrami Operator by Optimal Linear
+Approximations
+Tapasya Sinsinwar1, P.K.Dwivedi2
+Professor and Director Academics, Institute of Engineering and Technology, Alwar, Rajasthan Technical University, Kota(Raj.)
+Research Scholar (M.Tech, IT), Institute of Engineering and Technology"
+5161e38e4ea716dcfb554ccb88901b3d97778f64,SSPP-DAN: Deep domain adaptation network for face recognition with single sample per person,"SSPP-DAN: DEEP DOMAIN ADAPTATION NETWORK FOR
+FACE RECOGNITION WITH SINGLE SAMPLE PER PERSON
+Sungeun Hong, Woobin Im, Jongbin Ryu, Hyun S. Yang
+School of Computing, KAIST, Republic of Korea"
+5121f42de7cb9e41f93646e087df82b573b23311,Classifying Online Dating Profiles on Tinder using FaceNet Facial Embeddings,"CLASSIFYING ONLINE DATING PROFILES ON TINDER USING FACENET FACIAL
+EMBEDDINGS
+Charles F. Jekel and Raphael T. Haftka
+Department of Mechanical & Aerospace Engineering - University of Florida - Gainesville, FL 32611"
+51d1a6e15936727e8dd487ac7b7fd39bd2baf5ee,"A Fast and Accurate System for Face Detection, Identification, and Verification","JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
+A Fast and Accurate System for Face Detection,
+Identiﬁcation, and Veriﬁcation
+Rajeev Ranjan, Ankan Bansal, Jingxiao Zheng, Hongyu Xu, Joshua Gleason, Boyu Lu, Anirudh Nanduri,
+Jun-Cheng Chen, Carlos D. Castillo, Rama Chellappa"
+5157dde17a69f12c51186ffc20a0a6c6847f1a29,Evolutionary Cost-Sensitive Extreme Learning Machine,"Evolutionary Cost-sensitive Extreme Learning
+Machine
+Lei Zhang, Member, IEEE, and David Zhang, Fellow, IEEE"
+3daafe6389d877fe15d8823cdf5ac15fd919676f,Human Action Localization with Sparse Spatial Supervision,"Human Action Localization
+with Sparse Spatial Supervision
+Philippe Weinzaepfel, Xavier Martin, and Cordelia Schmid, Fellow, IEEE"
+3daf1191d43e21a8302d98567630b0e2025913b0,Can Autism be Catered with Artificial Intelligence-Assisted Intervention Technology? A Literature Review,"Can Autism be Catered with Artiﬁcial Intelligence-Assisted Intervention
+Technology? A Literature Review
+Muhammad Shoaib Jaliawala∗, Rizwan Ahmed Khan∗†
+Faculty of Information Technology, Barrett Hodgson University, Karachi, Pakistan
+Universit´e Claude Bernard Lyon 1, France"
+3d36f941d8ec613bb25e80fb8f4c160c1a2848df,Out-of-Sample Generalizations for Supervised Manifold Learning for Classification,"Out-of-sample generalizations for supervised
+manifold learning for classiﬁcation
+Elif Vural and Christine Guillemot"
+3d5a1be4c1595b4805a35414dfb55716e3bf80d8,Hidden Two-Stream Convolutional Networks for Action Recognition,"Hidden Two-Stream Convolutional Networks for
+Action Recognition
+Yi Zhu, Zhenzhong Lan, Shawn Newsam, Alexander G. Hauptmann"
+3d62b2f9cef997fc37099305dabff356d39ed477,Joint Face Alignment and 3D Face Reconstruction with Application to Face Recognition,"Joint Face Alignment and 3D Face
+Reconstruction with Application to Face
+Recognition
+Feng Liu, Qijun Zhao, Member, IEEE, Xiaoming Liu, Member, IEEE and Dan Zeng"
+3dd4d719b2185f7c7f92cc97f3b5a65990fcd5dd,Ensemble of Hankel Matrices for Face Emotion Recognition,"Ensemble of Hankel Matrices for
+Face Emotion Recognition
+Liliana Lo Presti and Marco La Cascia
+DICGIM, Universit´a degli Studi di Palermo,
+V.le delle Scienze, Ed. 6, 90128 Palermo, Italy,
+DRAFT
+To appear in ICIAP 2015"
+3dcebd4a1d66313dcd043f71162d677761b07a0d,Local binary pattern domain local appearance face recognition,"Yerel Đkili Örüntü Ortamında Yerel Görünüme Dayalı Yüz Tanıma
+Local Binary Pattern Domain Local Appearance Face Recognition
+Hazım K. Ekenel1, Mika Fischer1, Erkin Tekeli2, Rainer Stiefelhagen1, Aytül Erçil2
+Institut für Theorestische Informatik, Universität Karlsruhe (TH), Karlsruhe, Germany
+Faculty of Engineering and Natural Sciences, Sabancı University, Đstanbul, Turkey
+Özetçe
+Bu bildiride, ayrık kosinüs dönüşümü tabanlı yerel görünüme
+dayalı  yüz  tanıma  algoritması  ile  yüz  imgelerinin  yerel  ikili
+örüntüye  (YĐÖ)  dayalı  betimlemesini  birleştiren  hızlı  bir  yüz
+tanıma  algoritması  sunulmuştur.  Bu  tümleştirmedeki  amaç,
+yerel  ikili  örüntünün  dayanıklı  imge  betimleme  yeteneği  ile
+yrık  kosinüs  dönüşümünün  derli-toplu  veri  betimleme
+yeteneğinden  yararlanmaktır.  Önerilen  yaklaşımda,  yerel
+görünümün  modellenmesinden  önce  girdi  yüz  imgesi  yerel
+ikili  örüntü  ile  betimlenmiştir.  Elde  edilen  YĐÖ  betimlemesi,
+irbirleri  ile  örtüşmeyen  bloklara  ayrılmış  ve  her  blok
+üzerinde  yerel  özniteliklerin  çıkartımı  için  ayrık  kosinüs
+dönüşümü uygulanmıştır.  Çıkartımı  yapılan  yerel  öznitelikler
+daha  sonra  arka  arkaya  eklenerek  global  öznitelik  vektörü
+oluşturulmuştur.  Önerilen  algoritma,  CMU  PIE  ve  FRGC"
+3d42e17266475e5d34a32103d879b13de2366561,The Global Dimensionality of Face Space,"Proc.4thIEEEInt’lConf.AutomaticFace&GestureRecognition,Grenoble,France,pp264–270
+The Global Dimensionality of Face Space
+(cid:3)
+http://venezia.rockefeller.edu/
+The Rockefeller University
+Penio S. Penev
+Laboratory of Computational Neuroscience
+Lawrence Sirovich
+Laboratory for Applied Mathematics
+Mount Sinai School of Medicine
+(cid:13) IEEE2000
+230 York Avenue, New York, NY 10021
+One Gustave L. Levy Place, New York, NY 10029"
+3df7401906ae315e6aef3b4f13126de64b894a54,Robust learning of discriminative projection for multicategory classification on the Stiefel manifold,"Robust Learning of Discriminative Projection for Multicategory Classiﬁcation on
+the Stiefel Manifold
+Duc-Son Pham and Svetha Venkatesh
+Dept. of Computing, Curtin University of Technology
+GPO Box U1987, Perth, WA 6845, Australia"
+3d1af6c531ebcb4321607bcef8d9dc6aa9f0dc5a,Random Multispace Quantization as an Analytic Mechanism for BioHashing of Biometric and Random Identity Inputs,"Random Multispace Quantization as
+n Analytic Mechanism for BioHashing
+of Biometric and Random Identity Inputs
+Andrew B.J. Teoh, Member, IEEE, Alwyn Goh, and David C.L. Ngo, Member, IEEE"
+3d94f81cf4c3a7307e1a976dc6cb7bf38068a381,Data-Dependent Label Distribution Learning for Age Estimation,"Data-Dependent Label Distribution Learning
+for Age Estimation
+Zhouzhou He, Xi Li, Zhongfei Zhang, Fei Wu, Xin Geng, Yaqing Zhang, Ming-Hsuan Yang, and Yueting Zhuang"
+5892f8367639e9c1e3cf27fdf6c09bb3247651ed,Estimating Missing Features to Improve Multimedia Information Retrieval,"Estimating Missing Features to Improve Multimedia Information Retrieval
+Abraham Bagherjeiran
+Nicole S. Love
+Chandrika Kamath (cid:3)"
+587f81ae87b42c18c565694c694439c65557d6d5,DeepFace: Face Generation using Deep Learning,"DeepFace: Face Generation using Deep Learning
+Hardie Cate
+Fahim Dalvi
+Zeshan Hussain"
+580054294ca761500ada71f7d5a78acb0e622f19,A Subspace Model-Based Approach to Face Relighting Under Unknown Lighting and Poses,"A Subspace Model-Based Approach to Face
+Relighting Under Unknown Lighting and Poses
+Hyunjung Shim, Student Member, IEEE, Jiebo Luo, Senior Member, IEEE, and Tsuhan Chen, Fellow, IEEE"
+58081cb20d397ce80f638d38ed80b3384af76869,Embedded Real-Time Fall Detection Using Deep Learning For Elderly Care,"Embedded Real-Time Fall Detection Using Deep
+Learning For Elderly Care
+Hyunwoo Lee∗
+Jooyoung Kim
+Dojun Yang
+Joon-Ho Kim
+Samsung Research, Samsung Electronics
+{hyun0772.lee, joody.kim, dojun.yang,"
+581e920ddb6ecfc2a313a3aa6fed3d933b917ab0,Automatic Mapping of Remote Crowd Gaze to Stimuli in the Classroom,"Automatic Mapping of Remote Crowd Gaze to
+Stimuli in the Classroom
+Thiago Santini1, Thomas K¨ubler1, Lucas Draghetti1, Peter Gerjets2, Wolfgang
+Wagner3, Ulrich Trautwein3, and Enkelejda Kasneci1
+University of T¨ubingen, T¨ubingen, Germany
+Leibniz-Institut f¨ur Wissensmedien, T¨ubingen, Germany
+Hector Research Institute of Education Sciences and Psychology, T¨ubingen,
+Germany"
+58fa85ed57e661df93ca4cdb27d210afe5d2cdcd,Facial expression recognition by re-ranking with global and local generic features,"Cancún Center, Cancún, México, December 4-8, 2016
+978-1-5090-4847-2/16/$31.00 ©2016 IEEE"
+5860cf0f24f2ec3f8cbc39292976eed52ba2eafd,COMPUTATION EvaBio: A TOOL FOR PERFORMANCE EVALUATION IN BIOMETRICS,"International Journal of Automated Identification Technology, 3(2), July-December 2011, pp. 51-60
+COMPUTATION EvaBio: A TOOL FOR PERFORMANCE
+EVALUATION IN BIOMETRICS
+Julien Mahier, Baptiste Hemery, Mohamad El-Abed*, Mohamed T. El-Allam, Mohamed Y.
+Bouhaddaoui and Christophe Rosenberger
+GREYC Laboratory, ENSICAEN - University of Caen Basse Normandie - CNRS,
+6 Boulevard Maréchal Juin, 14000 Caen Cedex - France"
+58bf72750a8f5100e0c01e55fd1b959b31e7dbce,PyramidBox: A Context-assisted Single Shot Face Detector,"PyramidBox: A Context-assisted Single Shot
+Face Detector.
+Xu Tang∗, Daniel K. Du∗, Zeqiang He, and Jingtuo Liu†
+Baidu Inc."
+58542eeef9317ffab9b155579256d11efb4610f2,"Face Recognition Revisited On Pose , Alignment , Color , Illumination And Expression-Pyten","International Journal of Science and Research (IJSR)
+ISSN (Online): 2319-7064
+Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611
+Face Recognition Revisited on Pose, Alignment,
+Color, Illumination and Expression-PyTen
+Mugdha Tripathi
+Computer Science, BIT Noida, India"
+58823377757e7dc92f3b70a973be697651089756,Automatic facial expression analysis,"Technical Report
+UCAM-CL-TR-861
+ISSN 1476-2986
+Number 861
+Computer Laboratory
+Automatic facial expression analysis
+Tadas Baltrusaitis
+October 2014
+5 JJ Thomson Avenue
+Cambridge CB3 0FD
+United Kingdom
+phone +44 1223 763500
+http://www.cl.cam.ac.uk/"
+5865e824e3d8560e07840dd5f75cfe9bf68f9d96,Embodied conversational agents for multimodal automated social skills training in people with autism spectrum disorders,"RESEARCH ARTICLE
+Embodied conversational agents for
+multimodal automated social skills training in
+people with autism spectrum disorders
+Hiroki Tanaka1*, Hideki Negoro2, Hidemi Iwasaka3, Satoshi Nakamura1
+Graduate School of Information Science, Nara Institute of Science and Technology, Ikoma-shi, Nara, 630-
+0101, Japan, 2 Center for Special Needs Education, Nara University of Education, Nara-shi, Nara, 630-8538,
+Japan, 3 Developmental Center for Child and Adult, Shigisan Hospital, Ikoma-gun, Nara, 636-0815, Japan"
+58bb77dff5f6ee0fb5ab7f5079a5e788276184cc,Facial expression recognition with PCA and LBP features extracting from active facial patches,"Facial Expression Recognition with PCA and LBP
+Features Extracting from Active Facial Patches
+Yanpeng Liua, Yuwen Caoa, Yibin Lia, Ming Liu, Rui Songa
+Yafang Wang, Zhigang Xu , Xin Maa†"
+58db008b204d0c3c6744f280e8367b4057173259,Facial Expression Recognition,"International  Journal  of Current Engineering  and Technology
+ISSN 2277 - 4106
+© 2012  INPRESSCO.  All  Rights Reserved.
+Available at http://inpressco.com/category/ijcet
+Research Article
+Facial Expression  Recognition
+Riti Kushwahaa and  Neeta Naina*
+Department of Computer  Engineering Malaviya National Institute of Technology, Jaipur, Rajasthan, India
+Accepted 3June  2012,  Available online 8 June 2012"
+677585ccf8619ec2330b7f2d2b589a37146ffad7,A flexible model for training action localization with varying levels of supervision,"A flexible model for training action localization
+with varying levels of supervision
+Guilhem Chéron∗ 1 2
+Jean-Baptiste Alayrac∗ 1
+Ivan Laptev1
+Cordelia Schmid2"
+6789bddbabf234f31df992a3356b36a47451efc7,Unsupervised Generation of Free-Form and Parameterized Avatars.,"Unsupervised Generation of Free-Form and
+Parameterized Avatars
+Adam Polyak, Yaniv Taigman, and Lior Wolf, Member, IEEE"
+675b2caee111cb6aa7404b4d6aa371314bf0e647,AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions,"AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions
+Chunhui Gu∗
+Yeqing Li∗
+Chen Sun∗
+David A. Ross∗
+Sudheendra Vijayanarasimhan∗
+Carl Vondrick∗
+George Toderici∗
+Caroline Pantofaru∗
+Susanna Ricco∗
+Rahul Sukthankar∗
+Cordelia Schmid† ∗
+Jitendra Malik‡ ∗"
+67484723e0c2cbeb936b2e863710385bdc7d5368,Anchor Cascade for Efficient Face Detection,"Anchor Cascade for Efﬁcient Face Detection
+Baosheng Yu and Dacheng Tao, Fellow, IEEE"
+670637d0303a863c1548d5b19f705860a23e285c,Face swapping: automatically replacing faces in photographs,"Face Swapping: Automatically Replacing Faces in Photographs
+Dmitri Bitouk
+Neeraj Kumar
+Samreen Dhillon∗
+Columbia University†
+Peter Belhumeur
+Shree K. Nayar
+Figure 1: We have developed a system that automatically replaces faces in an input image with ones selected from a large collection of
+face images, obtained by applying face detection to publicly available photographs on the internet. In this example, the faces of (a) two
+people are shown after (b) automatic replacement with the top three ranked candidates. Our system for face replacement can be used for face
+de-identiﬁcation, personalized face replacement, and creating an appealing group photograph from a set of “burst” mode images. Original
+images in (a) used with permission from Retna Ltd. (top) and Getty Images Inc. (bottom).
+Rendering, Computational Photography
+Introduction
+Advances in digital photography have made it possible to cap-
+ture large collections of high-resolution images and share them
+on the internet. While the size and availability of these col-
+lections is leading to many exciting new applications,
+lso creating new problems. One of the most
+important of"
+6742c0a26315d7354ab6b1fa62a5fffaea06da14,What does 2D geometric information really tell us about 3D face shape?,"BAS AND SMITH: WHAT DOES 2D GEOMETRIC INFORMATION REALLY TELL US ABOUT 3D FACE SHAPE?
+What does 2D geometric information
+really tell us about 3D face shape?
+Anil Bas and William A. P. Smith, Member, IEEE"
+67c703a864aab47eba80b94d1935e6d244e00bcb,Face Retrieval Based On Local Binary Pattern and Its Variants: A Comprehensive Study,"(IJACSA) International Journal of Advanced Computer Science and Applications
+Vol. 7, No. 6, 2016
+Face Retrieval Based On Local Binary Pattern and Its
+Variants: A Comprehensive Study
+Department of Computer Vision and Robotics, University of Science, VNU-HCM, Viet Nam
+Phan Khoi, Lam Huu Thien, Vo Hoai Viet
+face  searching,"
+672fae3da801b2a0d2bad65afdbbbf1b2320623e,Pose-Selective Max Pooling for Measuring Similarity,"Pose-Selective Max Pooling for Measuring Similarity
+Xiang Xiang1 and Trac D. Tran2
+Dept. of Computer Science
+Dept. of Electrical & Computer Engineering
+Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA"
+67ba3524e135c1375c74fe53ebb03684754aae56,A compact pairwise trajectory representation for action recognition,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE
+ICASSP 2017"
+6769cfbd85329e4815bb1332b118b01119975a95,Tied factor analysis for face recognition across large pose changes,"Tied factor analysis for face recognition across
+large pose changes"
+0be43cf4299ce2067a0435798ef4ca2fbd255901,Title A temporal latent topic model for facial expression recognition,"Title
+A temporal latent topic model for facial expression recognition
+Author(s)
+Shang, L; Chan, KP
+Citation
+The 10th Asian Conference on Computer Vision (ACCV 2010),
+Queenstown, New Zealand, 8-12 November 2010. In Lecture
+Notes in Computer Science, 2010, v. 6495, p. 51-63
+Issued Date
+http://hdl.handle.net/10722/142604
+Rights
+Creative Commons: Attribution 3.0 Hong Kong License"
+0b2277a0609565c30a8ee3e7e193ce7f79ab48b0,Cost-Sensitive Semi-Supervised Discriminant Analysis for Face Recognition,"Cost-Sensitive Semi-Supervised Discriminant
+Analysis for Face Recognition
+Jiwen Lu, Member, IEEE, Xiuzhuang Zhou, Member, IEEE, Yap-Peng Tan, Senior Member, IEEE,
+Yuanyuan Shang, Member, IEEE, and Jie Zhou, Senior Member, IEEE"
+0b9ce839b3c77762fff947e60a0eb7ebbf261e84,Logarithmic Fourier Pca: a New Approach to Face Recognition,"Proceedings of the IASTED International Conference
+Computer Vision (CV 2011)
+June 1 - 3, 2011  Vancouver, BC, Canada
+LOGARITHMIC FOURIER PCA: A NEW APPROACH TO FACE
+RECOGNITION
+Lakshmiprabha  Nattamai  Sekar,
+Jhilik Bhattacharya,
+omjyoti
+Majumder
+Surface Robotics Lab
+Central Mechanical Engineering Research Institute
+Mahatma Gandhi Avenue,
+Durgapur - 713209, West Bengal, India.
+email: 1 n prabha 2 3"
+0b6a5200c33434cbfa9bf24ba482f6e06bf5fff7,"The use of deep learning in image segmentation, classification and detection","The Use of Deep Learning in Image
+Segmentation, Classification and Detection
+Mihai-Sorin Badea, Iulian-Ionuț Felea, Laura Maria Florea, Constantin Vertan
+The Image Processing and Analysis Lab (LAPI), Politehnica University of Bucharest, Romania"
+0b605b40d4fef23baa5d21ead11f522d7af1df06,Label-Embedding for Attribute-Based Classification,"Label-Embedding for Attribute-Based Classiﬁcation
+Zeynep Akataa,b, Florent Perronnina, Zaid Harchaouib and Cordelia Schmidb
+Computer Vision Group∗, XRCE, France
+LEAR†, INRIA, France"
+0b0eb562d7341231c3f82a65cf51943194add0bb,Line with Your Paper Identification Number ( Double - Click Here to Edit,"> REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) <
+Facial Image Analysis Based on Local Binary
+Patterns: A Survey
+Di Huang, Caifeng Shan, Mohsen Ardebilian, Liming Chen"
+0b3a146c474166bba71e645452b3a8276ac05998,Whos In the Picture,"Who’s in the Picture?
+Tamara L. Berg, Alexander C. Berg, Jaety Edwards and D.A. Forsyth
+Berkeley, CA 94720
+Computer Science Division
+U.C. Berkeley"
+0b0958493e43ca9c131315bcfb9a171d52ecbb8a,A Unified Neural Based Model for Structured Output Problems,"A Uniﬁed Neural Based Model for Structured Output Problems
+Souﬁane Belharbi∗1, Cl´ement Chatelain∗1, Romain H´erault∗1, and S´ebastien Adam∗2
+LITIS EA 4108, INSA de Rouen, Saint ´Etienne du Rouvray 76800, France
+LITIS EA 4108, UFR des Sciences, Universit´e de Rouen, France.
+April 13, 2015"
+0bf3513d18ec37efb1d2c7934a837dabafe9d091,Robust Subspace Clustering via Thresholding Ridge Regression,"Robust Subspace Clustering via Thresholding Ridge Regression
+Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore 138632
+Xi Peng1, Zhang Yi2,∗, Huajin Tang1,∗
+College of Computer Science, Sichuan University, Chengdu 610065, P.R. China."
+0b20f75dbb0823766d8c7b04030670ef7147ccdd,Feature selection using nearest attributes,"Feature selection using nearest attributes
+Alex Pappachen James, Member, IEEE, and Sima Dimitrijev, Senior Member, IEEE"
+0b5a82f8c0ee3640503ba24ef73e672d93aeebbf,On Learning 3D Face Morphable Model from In-the-wild Images,"On Learning 3D Face Morphable Model
+from In-the-wild Images
+Luan Tran, and Xiaoming Liu, Member, IEEE"
+0b174d4a67805b8796bfe86cd69a967d357ba9b6,A Survey on Face Detection and Recognition Approaches,"Research Journal of Recent Sciences _________________________________________________ ISSN 2277-2502
+Vol. 3(4), 56-62, April (2014)
+Res.J.Recent Sci."
+0b87d91fbda61cdea79a4b4dcdcb6d579f063884,Research on Theory and Method for Facial Expression Recognition Sys- tem Based on Dynamic Image Sequence,"The Open Automation and Control Systems Journal, 2015, 7, 569-579
+Open Access
+Research  on  Theory  and  Method  for  Facial  Expression  Recognition  Sys-
+tem Based on Dynamic Image Sequence
+Send Orders for Reprints to
+Yang Xinfeng1,* and Jiang Shan2
+School  of  Computer  &  Information  Engineering,  Nanyang  Institute  of  Technology,  Henan,  Nanyang,  473000,  P.R.
+China
+Henan University of Traditional Chinese Medicine, Henan, Zhengzhou, 450000, P.R. China"
+0b79356e58a0df1d0efcf428d0c7c4651afa140d,Bayesian Modeling of Facial Similarity,"Appears In: Advances in Neural Information Processing Systems , MIT Press, 			.
+Bayesian Modeling of Facial Similarity
+Baback Moghaddam
+Mitsubishi Electric Research Laboratory
+
+Cambridge, MA 
+Tony Jebara and Alex Pentland
+Massachusettes Institute of Technology
+
+Cambridge, MA 
+0b572a2b7052b15c8599dbb17d59ff4f02838ff7,Automatic Subspace Learning via Principal Coefficients Embedding,"Automatic Subspace Learning via Principal
+Coefﬁcients Embedding
+Xi Peng, Jiwen Lu, Senior Member, IEEE, Zhang Yi, Fellow, IEEE and Rui Yan, Member, IEEE,"
+0b02bfa5f3a238716a83aebceb0e75d22c549975,Learning Probabilistic Models for Recognizing Faces under Pose Variations,"Learning Probabilistic Models for Recognizing Faces
+under Pose Variations
+M. Saquib Sarfraz and Olaf Hellwich
+Computer vision and Remote Sensing, Berlin university of Technology
+Sekr. FR-3-1, Franklinstr. 28/29, Berlin, Germany"
+0bce54bfbd8119c73eb431559fc6ffbba741e6aa,Recurrent Neural Networks,"Published as a conference paper at ICLR 2018
+SKIP RNN: LEARNING TO SKIP STATE UPDATES IN
+RECURRENT NEURAL NETWORKS
+V´ıctor Campos∗†, Brendan Jou‡, Xavier Gir´o-i-Nieto§, Jordi Torres†, Shih-Fu ChangΓ
+Barcelona Supercomputing Center, ‡Google Inc,
+§Universitat Polit`ecnica de Catalunya, ΓColumbia University
+{victor.campos,"
+0b4c4ea4a133b9eab46b217e22bda4d9d13559e6,MORF: Multi-Objective Random Forests for face characteristic estimation,"MORF: Multi-Objective Random Forests for Face Characteristic Estimation
+Dario Di Fina1
+MICC - University of Florence
+Svebor Karaman1,3
+Andrew D. Bagdanov2
+{dario.difina,
+CVC - Universitat Autonoma de Barcelona
+Alberto Del Bimbo1
+DVMM Lab - Columbia University"
+0b8c92463f8f5087696681fb62dad003c308ebe2,On matching sketches with digital face images,"On Matching Sketches with Digital Face Images
+Himanshu S. Bhatt, Samarth Bharadwaj, Richa Singh, and Mayank Vatsa
+in local"
+0bc0f9178999e5c2f23a45325fa50300961e0226,Recognizing facial expressions from videos using Deep Belief Networks,"Recognizing facial expressions from videos using Deep
+Belief Networks
+CS 229 Project
+Advisor: Prof. Andrew Ng
+Adithya Rao Narendran Thiagarajan"
+9391618c09a51f72a1c30b2e890f4fac1f595ebd,Globally Tuned Cascade Pose Regression via Back Propagation with Application in 2D Face Pose Estimation and Heart Segmentation in 3D CT Images,"Globally Tuned Cascade Pose Regression via
+Back Propagation with Application in 2D Face
+Pose Estimation and Heart Segmentation in 3D
+CT Images
+Peng Sun
+James K Min
+Guanglei Xiong
+Dalio Institute of Cardiovascular Imaging, Weill Cornell Medical College
+April 1, 2015
+This work was submitted to ICML 2015 but got rejected. We put the initial
+submission ”as is” in Page 2 - 11 and add updated contents at the tail. The
+ode of this work is available at https://github.com/pengsun/bpcpr5."
+93675f86d03256f9a010033d3c4c842a732bf661,Localized Growth and Characterization of Silicon Nanowires,Universit´edesSciencesetTechnologiesdeLilleEcoleDoctoraleSciencesPourl’ing´enieurUniversit´eLilleNord-de-FranceTHESEPr´esent´ee`al’Universit´edesSciencesetTechnologiesdeLillePourobtenirletitredeDOCTEURDEL’UNIVERSIT´ESp´ecialit´e:MicroetNanotechnologieParTaoXULocalizedgrowthandcharacterizationofsiliconnanowiresSoutenuele25Septembre2009Compositiondujury:Pr´esident:TuamiLASRIRapporteurs:ThierryBARONHenriMARIETTEExaminateurs:EricBAKKERSXavierWALLARTDirecteurdeth`ese:BrunoGRANDIDIER
+936c7406de1dfdd22493785fc5d1e5614c6c2882,Detecting Visual Text,"012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 762–772,
+Montr´eal, Canada, June 3-8, 2012. c(cid:13)2012 Association for Computational Linguistics"
+93721023dd6423ab06ff7a491d01bdfe83db7754,Robust Face Alignment Using Convolutional Neural Networks,"ROBUST FACE ALIGNMENT USING CONVOLUTIONAL NEURAL
+NETWORKS
+Stefan Duffner and Christophe Garcia
+Orange Labs, 4, Rue du Clos Courtel, 35512 Cesson-S´evign´e, France
+{stefan.duffner,
+Keywords:
+Face alignment, Face registration, Convolutional Neural Networks."
+93cbb3b3e40321c4990c36f89a63534b506b6daf,Learning from examples in the small sample case: face expression recognition,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 35, NO. 3, JUNE 2005
+Learning From Examples in the Small Sample Case:
+Face Expression Recognition
+Guodong Guo and Charles R. Dyer, Fellow, IEEE"
+94b9c0a6515913bad345f0940ee233cdf82fffe1,Face Recognition using Local Ternary Pattern for Low Resolution Image,"International Journal of Science and Research (IJSR)
+ISSN (Online): 2319-7064
+Impact Factor (2012): 3.358
+Face Recognition using Local Ternary Pattern for
+Low Resolution Image
+Vikas1, Amanpreet Kaur2
+Research Scholar, CGC Group of Colleges, Gharuan, Punjab, India
+Assistant Professor, Department of Computer Science Engineering, Chandigarh University, Gharuan, Punjab, India"
+944faf7f14f1bead911aeec30cc80c861442b610,Action Tubelet Detector for Spatio-Temporal Action Localization,"Action Tubelet Detector for Spatio-Temporal Action Localization
+Vicky Kalogeiton1,2
+Philippe Weinzaepfel3
+Vittorio Ferrari2
+Cordelia Schmid1"
+9458c518a6e2d40fb1d6ca1066d6a0c73e1d6b73,A Benchmark and Comparative Study of Video-Based Face Recognition on COX Face Database,"A Benchmark and Comparative Study of
+Video-Based Face Recognition
+on COX Face Database
+Zhiwu Huang, Student Member, IEEE, Shiguang Shan, Senior Member, IEEE,
+Ruiping Wang, Member, IEEE, Haihong Zhang, Member, IEEE,
+Shihong Lao, Member, IEEE, Alifu Kuerban,
+nd Xilin Chen, Senior Member, IEEE"
+948af4b04b4a9ae4bff2777ffbcb29d5bfeeb494,Face Recognition From Single Sample Per Person by Learning of Generic Discriminant Vectors,"Available online at www.sciencedirect.com
+Procedia Engineering   41  ( 2012 )  465 – 472
+International Symposium on Robotics and Intelligent Sensors 2012 (IRIS 2012)
+Face Recognition From Single Sample Per Person by Learning of
+Generic Discriminant Vectors
+Fadhlan Hafiza*, Amir A. Shafieb, Yasir Mohd Mustafahb
+Faculty of Electrical Engineering, University of Technology MARA, Shah Alam, 40450 Selangor, Malaysia
+Faculty of Engineering, International Islamic University, Jalan Gombak, 53100 Kuala Lumpur, Malaysia"
+9441253b638373a0027a5b4324b4ee5f0dffd670,A Novel Scheme for Generating Secure Face Templates Using BDA,"A Novel Scheme for Generating Secure Face
+Templates Using BDA
+Shraddha S. Shinde
+Prof. Anagha P. Khedkar
+P.G. Student, Department of Computer Engineering,
+Associate Professor, Department of Computer
+MCERC,
+Nashik (M.S.), India
+e-mail:"
+94a11b601af77f0ad46338afd0fa4ccbab909e82,"Title of dissertation : EFFICIENT SENSING , SUMMARIZATION AND CLASSIFICATION OF VIDEOS",
+0efdd82a4753a8309ff0a3c22106c570d8a84c20,Lda with Subgroup Pca Method for Facial Image Retrieval,"LDA WITH SUBGROUP PCA METHOD FOR FACIAL IMAGE RETRIEVAL
+Wonjun Hwang, Tae-Kyun Kim, Seokcheol Kee
+Human Computer Interaction Lab., Samsung Advanced Institute of Technology, Korea."
+0eac652139f7ab44ff1051584b59f2dc1757f53b,Efficient Branching Cascaded Regression for Face Alignment under Significant Head Rotation,"Efﬁcient Branching Cascaded Regression
+for Face Alignment under Signiﬁcant Head Rotation
+Brandon M. Smith
+Charles R. Dyer
+University of Wisconsin–Madison"
+0e50fe28229fea45527000b876eb4068abd6ed8c,Angle Principal Component Analysis,Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
+0eff410cd6a93d0e37048e236f62e209bc4383d1,Learning discriminative MspLBP features based on Ada-LDA for multi-class pattern classification,"Anchorage Convention District
+May 3-8, 2010, Anchorage, Alaska, USA
+978-1-4244-5040-4/10/$26.00 ©2010 IEEE"
+0ee737085af468f264f57f052ea9b9b1f58d7222,SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination,"SiGAN: Siamese Generative Adversarial Network
+for Identity-Preserving Face Hallucination
+Chih-Chung Hsu, Member, IEEE, Chia-Wen Lin, Fellow, IEEE, Weng-Tai Su, Student Member, IEEE,
+nd Gene Cheung, Senior Member, IEEE,"
+0ee661a1b6bbfadb5a482ec643573de53a9adf5e,On the Use of Discriminative Cohort Score Normalization for Unconstrained Face Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. X, NO. X, MONTH YEAR
+On the Use of Discriminative Cohort Score
+Normalization for Unconstrained Face Recognition
+Massimo Tistarelli, Senior Member, IEEE, Yunlian Sun, and Norman Poh, Member, IEEE"
+0e49a23fafa4b2e2ac097292acf00298458932b4,Unsupervised Detection of Outlier Images Using Multi-Order Image Transforms,"Theory and Applications of Mathematics & Computer Science 3 (1) (2013) 13–31
+Unsupervised Detection of Outlier Images Using Multi-Order
+Image Transforms
+Lior Shamira,∗
+Lawrence Technological University, 21000 W Ten Mile Rd., Southﬁeld, MI 48075, United States."
+0e78af9bd0f9a0ce4ceb5f09f24bc4e4823bd698,Spontaneous Subtle Expression Recognition: Imbalanced Databases & Solutions,"Spontaneous Subtle Expression Recognition:
+Imbalanced Databases & Solutions (cid:63)
+Anh Cat Le Ngo1, Raphael Chung-Wei Phan1, John See2
+Faculty of Engineering,
+Multimedia University (MMU), Cyberjaya, Malaysia
+Faculty of Computing & Informatics,
+Multimedia University (MMU), Cyberjaya, Malaysia"
+0e2ea7af369dbcaeb5e334b02dd9ba5271b10265,Multi-Level Feature Abstraction from Convolutional Neural Networks for Multimodal Biometric Identification,
+0e7c70321462694757511a1776f53d629a1b38f3,2012 Proceedings of the Performance Metrics for Intelligent Systems (PerMI'12) Workshop,"NIST Special Publication 1136
+012 Proceedings of the
+Performance Metrics for Intelligent
+Systems (PerMI ‘12) Workshop
+Rajmohan Madhavan
+Elena R. Messina
+Brian A. Weiss
+http://dx.doi.org/10.6028/NIST.SP.1136"
+600025c9a13ff09c6d8b606a286a79c823d89db8,A Review on Linear and Non-linear Dimensionality Reduction Techniques,"Machine Learning and Applications: An International Journal (MLAIJ) Vol.1, No.1, September 2014
+A REVIEW ON LINEAR AND NON-LINEAR
+DIMENSIONALITY REDUCTION
+TECHNIQUES
+Arunasakthi. K, 2KamatchiPriya. L
+Assistant Professor
+Department of Computer Science and Engineering
+Ultra College of Engineering and Technology for Women,India.
+Assistant Professor
+Department of Computer Science and Engineering
+Vickram College of Engineering, Enathi, Tamil Nadu, India."
+60c24e44fce158c217d25c1bae9f880a8bd19fc3,Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation,"Controllable Image-to-Video Translation:
+A Case Study on Facial Expression Generation
+Lijie Fan
+MIT CSAIL
+Wenbing Huang
+Tencent AI Lab
+Chuang Gan
+MIT-Waston Lab
+Junzhou Huang
+Tencent AI Lab
+Boqing Gong
+Tencent AI Lab"
+60e2b9b2e0db3089237d0208f57b22a3aac932c1,Frankenstein: Learning Deep Face Representations Using Small Data,"Frankenstein: Learning Deep Face Representations
+using Small Data
+Guosheng Hu, Member, IEEE, Xiaojiang Peng, Yongxin Yang, Timothy M. Hospedales, and Jakob Verbeek"
+60ce4a9602c27ad17a1366165033fe5e0cf68078,Combination of Face Regions in Forensic Scenarios.,"TECHNICAL NOTE
+DIGITAL & MULTIMEDIA SCIENCES
+J Forensic Sci, 2015
+doi: 10.1111/1556-4029.12800
+Available online at: onlinelibrary.wiley.com
+Pedro Tome,1 Ph.D.; Julian Fierrez,1 Ph.D.; Ruben Vera-Rodriguez,1 Ph.D.; and Javier Ortega-Garcia,1
+Ph.D.
+Combination of Face Regions in Forensic
+Scenarios*"
+60efdb2e204b2be6701a8e168983fa666feac1be,Transferring Deep Object and Scene Representations for Event Recognition in Still Images,"Int J Comput Vis
+DOI 10.1007/s11263-017-1043-5
+Transferring Deep Object and Scene Representations for Event
+Recognition in Still Images
+Limin Wang1
+· Zhe Wang2 · Yu Qiao3 · Luc Van Gool1
+Received: 31 March 2016 / Accepted: 1 September 2017
+© Springer Science+Business Media, LLC 2017"
+60824ee635777b4ee30fcc2485ef1e103b8e7af9,Cascaded Collaborative Regression for Robust Facial Landmark Detection Trained Using a Mixture of Synthetic and Real Images With Dynamic Weighting,"Cascaded Collaborative Regression for Robust Facial
+Landmark Detection Trained using a Mixture of Synthetic and
+Real Images with Dynamic Weighting
+Zhen-Hua Feng, Student Member, IEEE, Guosheng Hu, Student Member, IEEE, Josef Kittler,
+Life Member, IEEE, William Christmas, and Xiao-Jun Wu"
+60a20d5023f2bcc241eb9e187b4ddece695c2b9b,Invertible Nonlinear Dimensionality Reduction via Joint Dictionary Learning,"Invertible Nonlinear Dimensionality Reduction
+via Joint Dictionary Learning
+Xian Wei, Martin Kleinsteuber, and Hao Shen
+Department of Electrical and Computer Engineering
+Technische Universit¨at M¨unchen, Germany
+{xian.wei, kleinsteuber,"
+60cdcf75e97e88638ec973f468598ae7f75c59b4,Face Annotation Using Transductive Kernel Fisher Discriminant,"Face Annotation Using Transductive
+Kernel Fisher Discriminant
+Jianke Zhu, Steven C.H. Hoi, and Michael R. Lyu"
+60b3601d70f5cdcfef9934b24bcb3cc4dde663e7,Binary Gradient Correlation Patterns for Robust Face Recognition,"SUBMITTED TO IEEE TRANS. ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
+Binary Gradient Correlation Patterns
+for Robust Face Recognition
+Weilin Huang, Student Member, IEEE, and Hujun Yin, Senior Member, IEEE"
+60496b400e70acfbbf5f2f35b4a49de2a90701b5,Avoiding Boosting Overfitting by Removing Confusing Samples,"Avoiding Boosting Overfitting by Removing Confusing
+Samples
+Alexander Vezhnevets, Olga Barinova
+Moscow State University, dept. of Computational Mathematics and Cybernetics,
+Graphics and Media Lab
+{avezhnevets,
+19992 Moscow, Russia"
+60bffecd79193d05742e5ab8550a5f89accd8488,Proposal Classification using sparse representation and applications to skin lesion diagnosis,"PhD Thesis Proposal
+Classification using sparse representation and applications to skin
+lesion diagnosis
+I. Description
+In only a few decades, sparse representation modeling has undergone a tremendous expansion with
+successful applications in many fields including signal and image processing, computer science,
+machine  learning,  statistics.  Mathematically,  it  can  be  considered  as  the  problem  of  finding  the
+sparsest solution (the one with the fewest non-zeros entries) to an underdetermined linear system
+of equations [1]. Based on the observation for natural images (or images rich in textures) that small
+scale  structures  tend  to  repeat  themselves  in  an  image  or  in  a  group  of  similar  images,  a  signal
+source can be sparsely represented over some well-chosen redundant basis (a dictionary). In other
+words, it can be approximately representable by a linear combination of a few elements (also called
+toms or basis vectors) of a redundant/over-complete dictionary.
+Such models have been proven successful in many tasks including denoising [2]-[5], compression
+[6],[7], super-resolution [8],[9], classification and pattern recognition [10]-[16]. In the context of
+lassification, the objective is to find the class to which a test signal belongs, given training data
+from multiple classes. Sparse representation has become a powerful technique in classification and
+pplications, including texture classification [16], face recognition [12], object detection [10], and
+segmentation of medical images [17], [18]. In conventional Sparse Representation Classification
+(SRC) schemes, learned dictionaries and sparse representation are involved to classify image pixels"
+601834a4150e9af028df90535ab61d812c45082c,A short review and primer on using video for psychophysiological observations in human-computer interaction applications,"A short review and primer on using video for
+psychophysiological observations in
+human-computer interaction applications
+Teppo Valtonen1
+Quantiﬁed Employee unit, Finnish Institute of Occupational Health,
+teppo. valtonen fi,
+POBox 40, 00250, Helsinki, Finland"
+346dbc7484a1d930e7cc44276c29d134ad76dc3f,Artists portray human faces with the Fourier statistics of complex natural scenes.,"This article was downloaded by:[University of Toronto]
+On: 21 November 2007
+Access Details: [subscription number 785020433]
+Publisher: Informa Healthcare
+Informa Ltd Registered in England and Wales Registered Number: 1072954
+Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK
+Systems
+Publication details, including instructions for authors and subscription information:
+http://www.informaworld.com/smpp/title~content=t713663148
+Artists portray human faces with the Fourier statistics of
+omplex natural scenes
+Christoph Redies a; Jan Hänisch b; Marko Blickhan a; Joachim Denzler b
+Institute of Anatomy I, School of Medicine, Friedrich Schiller University, Germany
+Department of Computer Science, Friedrich Schiller University, D-07740 Jena,
+Germany
+First Published on: 28 August 2007
+To cite this Article: Redies, Christoph, Hänisch, Jan, Blickhan, Marko and Denzler,
+Joachim (2007) 'Artists portray human faces with the Fourier statistics of complex
+To link to this article: DOI: 10.1080/09548980701574496
+URL: http://dx.doi.org/10.1080/09548980701574496"
+34b3b14b4b7bfd149a0bd63749f416e1f2fc0c4c,The AXES submissions at TrecVid 2013,"The AXES submissions at TrecVid 2013
+Robin Aly1, Relja Arandjelovi´c3, Ken Chatﬁeld3, Matthijs Douze6, Basura Fernando4, Zaid Harchaoui6,
+Kevin McGuinness2, Noel E. O’Conner2, Dan Oneata6, Omkar M. Parkhi3, Danila Potapov6, Jérôme Revaud6,
+Cordelia Schmid6, Jochen Schwenninger5, David Scott2, Tinne Tuytelaars4, Jakob Verbeek6, Heng Wang6,
+Andrew Zisserman3
+University of Twente 2Dublin City University 3Oxford University
+KU Leuven 5Fraunhofer Sankt Augustin 6INRIA Grenoble"
+34d484b47af705e303fc6987413dc0180f5f04a9,RI:Medium: Unsupervised and Weakly-Supervised Discovery of Facial Events,"RI:Medium: Unsupervised and Weakly-Supervised
+Discovery of Facial Events
+Introduction
+The face is one of the most powerful channels of nonverbal communication. Facial expression has been a
+focus of emotion research for over a hundred years [11]. It is central to several leading theories of emotion
+[16, 28, 44] and has been the focus of at times heated debate about issues in emotion science [17, 23, 40].
+Facial expression ﬁgures prominently in research on almost every aspect of emotion, including psychophys-
+iology [30], neural correlates [18], development [31], perception [4], addiction [24], social processes [26],
+depression [39] and other emotion disorders [46], to name a few. In general, facial expression provides cues
+bout emotional response, regulates interpersonal behavior, and communicates aspects of psychopathology.
+While people have believed for centuries that facial expressions can reveal what people are thinking and
+feeling, it is relatively recently that the face has been studied scientiﬁcally for what it can tell us about
+internal states, social behavior, and psychopathology.
+Faces possess their own language. Beginning with Darwin and his contemporaries, extensive efforts
+have been made to manually describe this language. A leading approach, the Facial Action Coding System
+(FACS) [19] , segments the visible effects of facial muscle activation into ”action units.” Because of its
+descriptive power, FACS has become the state of the art in manual measurement of facial expression and is
+widely used in studies of spontaneous facial behavior. The FACS taxonomy was develop by manually ob-
+serving graylevel variation between expressions in images and to a lesser extent by recording the electrical
+ctivity of underlying facial muscles [9]. Because of its importance to human social dynamics, person per-"
+341002fac5ae6c193b78018a164d3c7295a495e4,von Mises-Fisher Mixture Model-based Deep learning: Application to Face Verification,"von Mises-Fisher Mixture Model-based Deep
+learning: Application to Face Veriﬁcation
+Md. Abul Hasnat, Julien Bohn´e, Jonathan Milgram, St´ephane Gentric and Liming Chen"
+34ec83c8ff214128e7a4a4763059eebac59268a6,Action Anticipation By Predicting Future Dynamic Images,"Action Anticipation By Predicting Future
+Dynamic Images
+Cristian Rodriguez, Basura Fernando and Hongdong Li
+Australian Centre for Robotic Vision, ANU, Canberra, Australia
+{cristian.rodriguez, basura.fernando,"
+34c594abba9bb7e5813cfae830e2c4db78cf138c,Transport-based single frame super resolution of very low resolution face images,"Transport-Based Single Frame Super Resolution of Very Low Resolution Face Images
+Soheil Kolouri1, Gustavo K. Rohde1,2
+Department of Biomedical Engineering, Carnegie Mellon University. 2Department of Electrical and Computer Engineering, Carnegie Mellon University.
+We describe a single-frame super-resolution method for reconstructing high-
+resolution (abbr. high-res) faces from very low-resolution (abbr. low-res)
+face images (e.g. smaller than 16× 16 pixels) by learning a nonlinear La-
+grangian model for the high-res face images. Our technique is based on the
+mathematics of optimal transport, and hence we denote it as transport-based
+SFSR (TB-SFSR). In the training phase, a nonlinear model of high-res fa-
+ial images is constructed based on transport maps that morph a reference
+image into the training face images. In the testing phase, the resolution of
+degraded image is enhanced by ﬁnding the model parameters that best ﬁt
+the given low resolution data.
+Generally speaking, most SFSR methods [2, 3, 4, 5] are based on a
+linear model for the high-res images. Hence, ultimately, the majority of
+SFSR models in the literature can be written as, Ih(x) = ∑i wiψi(x), where
+Ih is a high-res image or a high-res image patch, w’s are weight coefﬁcients,
+nd ψ’s are high-res images (or image patches), which are learned from the
+training images using a speciﬁc model. Here we propose a fundamentally
+different approach toward modeling high-res images. In our approach the"
+341ed69a6e5d7a89ff897c72c1456f50cfb23c96,"DAGER: Deep Age, Gender and Emotion Recognition Using Convolutional Neural Network","DAGER: Deep Age, Gender and Emotion
+Recognition Using Convolutional Neural
+Networks
+Afshin Dehghan
+Enrique G. Ortiz
+Guang Shu
+Syed Zain Masood
+{afshindehghan, egortiz, guangshu,
+Computer Vision Lab, Sighthound Inc., Winter Park, FL"
+340d1a9852747b03061e5358a8d12055136599b0,Audio-Visual Recognition System Insusceptible to Illumination Variation over Internet Protocol _ICIE_28_,"Audio-Visual Recognition System Insusceptible
+to Illumination Variation over Internet Protocol
+Yee Wan Wong, Kah Phooi Seng, and Li-Minn Ang"
+34ccdec6c3f1edeeecae6a8f92e8bdb290ce40fd,A Virtual Assistant to Help Dysphagia Patients Eat Safely at Home,"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16)
+A Virtual Assistant to Help Dysphagia Patients Eat Safely at Home
+Michael Freed, Brian Burns, Aaron Heller, Daniel Sanchez, *Sharon Beaumont-Bowman
+SRI International, Menlo Park California / *Brooklyn College, Brooklyn New York
+{first name, last"
+5a3da29970d0c3c75ef4cb372b336fc8b10381d7,CNN-based Real-time Dense Face Reconstruction with Inverse-rendered Photo-realistic Face Images.,"CNN-based Real-time Dense Face Reconstruction
+with Inverse-rendered Photo-realistic Face Images
+Yudong Guo, Juyong Zhang†, Jianfei Cai, Boyi Jiang and Jianmin Zheng"
+5a93f9084e59cb9730a498ff602a8c8703e5d8a5,Face Recognition using Local Quantized Patterns,"HUSSAIN ET. AL: FACE RECOGNITION USING LOCAL QUANTIZED PATTERNS
+Face Recognition using Local Quantized
+Patterns
+Sibt ul Hussain
+Thibault Napoléon
+Fréderic Jurie
+GREYC — CNRS UMR 6072,
+University of Caen Basse-Normandie,
+Caen, France"
+5a34a9bb264a2594c02b5f46b038aa1ec3389072,Label-Embedding for Image Classification,"Label-Embedding for Image Classiﬁcation
+Zeynep Akata, Member, IEEE, Florent Perronnin, Member, IEEE, Zaid Harchaoui, Member, IEEE,
+nd Cordelia Schmid, Fellow, IEEE"
+5a4c6246758c522f68e75491eb65eafda375b701,Contourlet structural similarity for facial expression recognition,"978-1-4244-4296-6/10/$25.00 ©2010 IEEE
+ICASSP 2010"
+5aad5e7390211267f3511ffa75c69febe3b84cc7,Driver Gaze Region Estimation Without Using Eye Movement,"Driver Gaze Estimation
+Without Using Eye Movement
+Lex Fridman, Philipp Langhans, Joonbum Lee, Bryan Reimer
+MIT AgeLab"
+5a86842ab586de9d62d5badb2ad8f4f01eada885,Facial Emotion Recognition and Classification Using Hybridization Method,"International Journal of Engineering Research and General Science Volume 3, Issue 3, May-June, 2015
+ISSN 2091-2730
+Facial Emotion Recognition and Classification Using Hybridization
+Method
+Anchal Garg , Dr. Rohit Bajaj
+Deptt. of CSE, Chandigarh Engg. College,  Mohali, Punjab, India.
+07696449500"
+5a4ec5c79f3699ba037a5f06d8ad309fb4ee682c,Automatic age and gender classification using supervised appearance model,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 12/17/2017 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use
+AutomaticageandgenderclassificationusingsupervisedappearancemodelAliMainaBukarHassanUgailDavidConnahAliMainaBukar,HassanUgail,DavidConnah,“Automaticageandgenderclassificationusingsupervisedappearancemodel,”J.Electron.Imaging25(6),061605(2016),doi:10.1117/1.JEI.25.6.061605."
+5aed0f26549c6e64c5199048c4fd5fdb3c5e69d6,Human Expression Recognition using Facial Features,"International Journal of Computer Applications® (IJCA) (0975 – 8887)
+International Conference on Knowledge Collaboration in Engineering, ICKCE-2014
+Human Expression Recognition using Facial Features
+G.Saranya
+Post graduate student, Dept. of ECE
+Parisutham Institute of Technology & Science
+Thanjavur.
+Affiliated to Anna university, Chennai
+recognition  can  be  used"
+5a7520380d9960ff3b4f5f0fe526a00f63791e99,The Indian Spontaneous Expression Database for Emotion Recognition,"The Indian Spontaneous Expression
+Database for Emotion Recognition
+S L Happy, Student Member, IEEE, Priyadarshi Patnaik, Aurobinda Routray, Member, IEEE,
+nd Rajlakshmi Guha"
+5fff61302adc65d554d5db3722b8a604e62a8377,Additive Margin Softmax for Face Verification,"Additive Margin Softmax for Face Veriﬁcation
+Feng Wang
+UESTC
+Weiyang Liu
+Georgia Tech
+Haijun Liu
+UESTC
+Jian Cheng
+UESTC
+haijun"
+5fa6e4a23da0b39e4b35ac73a15d55cee8608736,RED-Net: A Recurrent Encoder–Decoder Network for Video-Based Face Alignment,"IJCV special issue (Best papers of ECCV 2016) manuscript No.
+(will be inserted by the editor)
+RED-Net:
+A Recurrent Encoder-Decoder Network for Video-based Face Alignment
+Xi Peng · Rogerio S. Feris · Xiaoyu Wang · Dimitris N. Metaxas
+Submitted: April 19 2017 / Revised: December 12 2017"
+5f871838710a6b408cf647aacb3b198983719c31,Locally Linear Regression for Pose-Invariant Face Recognition,"Locally Linear Regression for Pose-Invariant
+Face Recognition
+Xiujuan Chai, Shiguang Shan, Member, IEEE, Xilin Chen, Member, IEEE, and Wen Gao, Senior Member, IEEE"
+5f344a4ef7edfd87c5c4bc531833774c3ed23542,Semisupervised Learning of Classifiers with Application to Human-computer Interaction,"
+5f758a29dae102511576c0a5c6beda264060a401,Fine-grained Video Attractiveness Prediction Using Multimodal Deep Learning on a Large Real-world Dataset,"Fine-grained Video Attractiveness Prediction Using Multimodal
+Deep Learning on a Large Real-world Dataset
+Xinpeng Chen†∗, Jingyuan Chen♭∗, Lin Ma‡♮, Jian Yao†, Wei Liu‡♮, Jiebo Luo§, Tong Zhang‡
+Wuhan University, ‡Tencent AI Lab, ♭National University of Singapore, §University of Rochester"
+5f5906168235613c81ad2129e2431a0e5ef2b6e4,A Unified Framework for Compositional Fitting of Active Appearance Models,"Noname manuscript No.
+(will be inserted by the editor)
+A Uniﬁed Framework for Compositional Fitting of
+Active Appearance Models
+Joan Alabort-i-Medina · Stefanos Zafeiriou
+Received: date / Accepted: date"
+5fb5d9389e2a2a4302c81bcfc068a4c8d4efe70c,Multiple Facial Attributes Estimation Based on Weighted Heterogeneous Learning,"Multiple Facial Attributes Estimation based on
+Weighted Heterogeneous Learning
+H.Fukui* T.Yamashita* Y.Kato* R.Matsui*
+T. Ogata** Y.Yamauchi* H.Fujiyoshi*
+*Chubu University
+**Abeja Inc.
+200, Matuoto-cho, Kasugai,
+-1-20, Toranomon, Minato-ku,
+Aichi, Japan
+Tokyo, Japan"
+5fc664202208aaf01c9b62da5dfdcd71fdadab29,Automatic Face Recognition from Video,rXiv:1504.05308v1  [cs.CV]  21 Apr 2015
+5fa1724a79a9f7090c54925f6ac52f1697d6b570,The Development of Multimodal Lexical Resources,"Proceedings of the Workshop on Grammar and Lexicon: Interactions and Interfaces,
+pages 41–47, Osaka, Japan, December 11 2016."
+33a1a049d15e22befc7ddefdd3ae719ced8394bf,An Efficient Approach to Facial Feature Detection for Expression Recognition,"FULL PAPER
+International Journal of Recent Trends in Engineering, Vol 2, No. 1, November 2009
+An Efficient Approach to Facial Feature Detection
+for Expression Recognition
+S.P. Khandait1, P.D. Khandait2 and Dr.R.C.Thool2
+Deptt. of Info.Tech., K.D.K.C.E., Nagpur, India
+2Deptt.of Electronics Engg., K.D.K.C.E., Nagpur, India, 2Deptt. of Info.Tech., SGGSIET, Nanded"
+3399f8f0dff8fcf001b711174d29c9d4fde89379,Face R-CNN,"Face R-CNN
+Hao Wang Zhifeng Li∗ Xing Ji Yitong Wang
+Tencent AI Lab, China"
+333aa36e80f1a7fa29cf069d81d4d2e12679bc67,Suggesting Sounds for Images from Video Collections,"Suggesting Sounds for Images
+from Video Collections
+Matthias Sol`er1, Jean-Charles Bazin2, Oliver Wang2, Andreas Krause1 and
+Alexander Sorkine-Hornung2
+Computer Science Department, ETH Z¨urich, Switzerland
+Disney Research, Switzerland"
+3312eb79e025b885afe986be8189446ba356a507,MOON: A Mixed Objective Optimization Network for the Recognition of Facial Attributes,"This is a post-print of the original paper published in ECCV 2016 (SpringerLink).
+MOON : A Mixed Objective Optimization
+Network for the Recognition of Facial Attributes
+Ethan M. Rudd, Manuel G¨unther, and Terrance E. Boult
+Vision and Security Technology (VAST) Lab,
+University of Colorado at Colorado Springs"
+33792bb27ef392973e951ca5a5a3be4a22a0d0c6,Two-Dimensional Whitening Reconstruction for Enhancing Robustness of Principal Component Analysis,"Two-dimensional Whitening Reconstruction for
+Enhancing Robustness of Principal Component
+Analysis
+Xiaoshuang Shi, Zhenhua Guo, Feiping Nie, Lin Yang, Jane You, and Dacheng Tao"
+3328674d71a18ed649e828963a0edb54348ee598,A face and palmprint recognition approach based on discriminant DCT feature extraction,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 34, NO. 6, DECEMBER 2004
+A Face and Palmprint Recognition Approach Based
+on Discriminant DCT Feature Extraction
+Xiao-Yuan Jing and David Zhang"
+339937141ffb547af8e746718fbf2365cc1570c8,Facial Emotion Recognition in Real Time,"Facial Emotion Recognition in Real Time
+Dan Duncan
+Gautam Shine
+Chris English"
+33ae696546eed070717192d393f75a1583cd8e2c,Subspace selection to suppress confounding source domain information in AAM transfer learning,
+3393459600368be2c4c9878a3f65a57dcc0c2cfa,Eigen-PEP for Video Face Recognition,"Eigen-PEP for Video Face Recognition
+Haoxiang Li†, Gang Hua†, Xiaohui Shen‡, Zhe Lin‡, Jonathan Brandt‡
+Stevens Institute of Technology ‡Adobe Systems Inc."
+3352426a67eabe3516812cb66a77aeb8b4df4d1b,Joint Multi-view Face Alignment in the Wild,"JOURNAL OF LATEX CLASS FILES, VOL. 4, NO. 5, APRIL 2015
+Joint Multi-view Face Alignment in the Wild
+Jiankang Deng, Student Member, IEEE, George Trigeorgis, Yuxiang Zhou, and Stefanos Zafeiriou, Member, IEEE"
+334d6c71b6bce8dfbd376c4203004bd4464c2099,Biconvex Relaxation for Semidefinite Programming in Computer Vision,"BICONVEX RELAXATION FOR SEMIDEFINITE PROGRAMMING IN
+COMPUTER VISION
+SOHIL SHAH*, ABHAY KUMAR*, DAVID JACOBS,
+CHRISTOPH STUDER, AND TOM GOLDSTEIN"
+33695e0779e67c7722449e9a3e2e55fde64cfd99,Riemannian coding and dictionary learning: Kernels to the rescue,"Riemannian Coding and Dictionary Learning: Kernels to the Rescue
+Mehrtash Harandi, Mathieu Salzmann
+Australian National University & NICTA
+While sparse coding on non-flat Riemannian manifolds has recently become
+increasingly popular, existing solutions either are dedicated to speciﬁc man-
+ifolds, or rely on optimization problems that are difﬁcult to solve, especially
+when it comes to dictionary learning. In this paper, we propose to make use
+of kernels to perform coding and dictionary learning on Riemannian man-
+ifolds. To this end, we introduce a general Riemannian coding framework
+with its kernel-based counterpart. This lets us (i) generalize beyond the spe-
+ial case of sparse coding; (ii) introduce efﬁcient solutions to two coding
+schemes; (iii) learn the kernel parameters; (iv) perform unsupervised and
+supervised dictionary learning in a much simpler manner than previous Rie-
+mannian coding approaches.
+i=1, di ∈ M, be a dictionary on a Rie-
+mannian manifold M, and x ∈ M be a query point on the manifold. We
+(cid:17)
+deﬁne a general Riemannian coding formulation as
+More speciﬁcally, let D = {di}N
+(cid:93)N"
+33e20449aa40488c6d4b430a48edf5c4b43afdab,The Faces of Engagement: Automatic Recognition of Student Engagementfrom Facial Expressions,"TRANSACTIONS ON AFFECTIVE COMPUTING
+The Faces of Engagement: Automatic
+Recognition of Student Engagement from Facial
+Expressions
+Jacob Whitehill, Zewelanji Serpell, Yi-Ching Lin, Aysha Foster, and Javier R. Movellan"
+333e7ad7f915d8ee3bb43a93ea167d6026aa3c22,3D Assisted Face Recognition: Dealing With Expression Variations,"This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.
+The final version of record is available at http://dx.doi.org/10.1109/TIFS.2014.2309851
+DRAFT
+D Assisted Face Recognition: Dealing With
+Expression Variations
+Nesli Erdogmus, Member, IEEE, Jean-Luc Dugelay, Fellow Member, IEEE"
+334166a942acb15ccc4517cefde751a381512605,Facial Expression Analysis using Deep Learning,"International Research Journal of Engineering and Technology (IRJET)       e-ISSN: 2395-0056
+Volume: 04 Issue: 10 | Oct -2017                     www.irjet.net                                                                 p-ISSN: 2395-0072
+Facial Expression Analysis using Deep Learning
+Hemanth Singh1, Raman Patel2
+,2 M.Tech Student, SSG Engineering College, Odisha, India
+---------------------------------------------------------------------***---------------------------------------------------------------------
+examination structures need to analyse the facial exercises"
+33ef419dffef85443ec9fe89a93f928bafdc922e,SelfKin: Self Adjusted Deep Model For Kinship Verification,"SelfKin: Self Adjusted Deep Model For
+Kinship Veriﬁcation
+Eran Dahan, Yosi Keller
+Faculty of Engineering, Bar-Ilan University, Israel."
+05b8673d810fadf888c62b7e6c7185355ffa4121,A Comprehensive Survey to Face Hallucination,"(will be inserted by the editor)
+A Comprehensive Survey to Face Hallucination
+Nannan Wang · Dacheng Tao · Xinbo Gao · Xuelong Li · Jie Li
+Received: date / Accepted: date"
+05e658fed4a1ce877199a4ce1a8f8cf6f449a890,Domain Transfer Learning for Object and Action Recognition,
+05ad478ca69b935c1bba755ac1a2a90be6679129,Attribute Dominance: What Pops Out?,"Attribute Dominance: What Pops Out?
+Naman Turakhia
+Georgia Tech"
+054738ce39920975b8dcc97e01b3b6cc0d0bdf32,Towards the design of an end-to-end automated system for image and video-based recognition,"Towards the Design of an End-to-End Automated
+System for Image and Video-based Recognition
+Rama Chellappa1, Jun-Cheng Chen3, Rajeev Ranjan1, Swami Sankaranarayanan1, Amit Kumar1,
+Vishal M. Patel2 and Carlos D. Castillo4"
+05e03c48f32bd89c8a15ba82891f40f1cfdc7562,Scalable Robust Principal Component Analysis Using Grassmann Averages,"Scalable Robust Principal Component
+Analysis using Grassmann Averages
+Søren Hauberg, Aasa Feragen, Rafﬁ Enﬁciaud, and Michael J. Black"
+056ba488898a1a1b32daec7a45e0d550e0c51ae4,Cascaded Continuous Regression for Real-Time Incremental Face Tracking,"Cascaded Continuous Regression for Real-time
+Incremental Face Tracking
+Enrique S´anchez-Lozano, Brais Martinez,
+Georgios Tzimiropoulos, and Michel Valstar
+Computer Vision Laboratory. University of Nottingham"
+050fdbd2e1aa8b1a09ed42b2e5cc24d4fe8c7371,Spatio-Temporal Scale Selection in Video Data,"Contents
+Scale Space and PDE Methods
+Spatio-Temporal Scale Selection in Video Data . . . . . . . . . . . . . . . . . . . . .
+Tony Lindeberg
+Dynamic Texture Recognition Using Time-Causal Spatio-Temporal
+Scale-Space Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
+Ylva Jansson and Tony Lindeberg
+Corner Detection Using the Affine Morphological Scale Space . . . . . . . . . . .
+Luis Alvarez
+Nonlinear Spectral Image Fusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
+Martin Benning, Michael Möller, Raz Z. Nossek, Martin Burger,
+Daniel Cremers, Guy Gilboa, and Carola-Bibiane Schönlieb
+Tubular Structure Segmentation Based on Heat Diffusion. . . . . . . . . . . . . . .
+Fang Yang and Laurent D. Cohen
+Analytic Existence and Uniqueness Results for PDE-Based Image
+Reconstruction with the Laplacian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
+Laurent Hoeltgen, Isaac Harris, Michael Breuß, and Andreas Kleefeld
+Combining Contrast Invariant L1 Data Fidelities with Nonlinear
+Spectral Image Decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
+Leonie Zeune, Stephan A. van Gils, Leon W.M.M. Terstappen,"
+052880031be0a760a5b606b2ad3d22f237e8af70,Datasets on object manipulation and interaction: a survey,"Datasets on object manipulation and interaction: a survey
+Yongqiang Huang and Yu Sun"
+053c2f592a7f153e5f3746aa5ab58b62f2cf1d21,Performance Evaluation of Illumination Normalization Techniques for Face Recognition,"International Journal of Research in
+Engineering & Technology (IJRET)
+ISSN 2321-8843
+Vol. 1, Issue 2, July 2013, 11-20
+© Impact Journals
+PERFORMANCE EVALUATION OF ILLUMINATION NORMALIZATION TECHNIQUES
+FOR FACE RECOGNITION
+A. P. C. SARATHA DEVI & V. MAHESH
+Department of Information Technology, PSG College of Technology, Coimbatore, Tamil Nadu, India"
+05ea7930ae26165e7e51ff11b91c7aa8d7722002,Learning And-Or Model to Represent Context and Occlusion for Car Detection and Viewpoint Estimation,"Learning And-Or Model to Represent Context and
+Occlusion for Car Detection and Viewpoint Estimation
+Tianfu Wu∗, Bo Li∗ and Song-Chun Zhu"
+051a84f0e39126c1ebeeb379a405816d5d06604d,Biometric Recognition Performing in a Bioinspired System,"Cogn Comput (2009) 1:257–267
+DOI 10.1007/s12559-009-9018-7
+Biometric Recognition Performing in a Bioinspired System
+Joan Fa`bregas Æ Marcos Faundez-Zanuy
+Published online: 20 May 2009
+Ó Springer Science+Business Media, LLC 2009"
+0559fb9f5e8627fecc026c8ee6f7ad30e54ee929,Facial Expression Recognition,"Facial Expression Recognition
+Bogdan J. Matuszewski, Wei Quan and Lik-Kwan Shark
+ADSIP Research Centre, University of Central Lancashire
+. Introduction
+Facial  expressions  are  visible  signs  of  a  person’s  affective  state,  cognitive  activity  and
+personality.  Humans  can  perform  expression  recognition  with  a  remarkable  robustness
+without  conscious  effort  even  under  a  variety  of  adverse  conditions  such  as  partially
+occluded faces, different appearances and poor illumination. Over the last two decades, the
+dvances in imaging technology and ever increasing computing power have opened up a
+possibility of automatic facial expression recognition and this has led to significant research
+efforts from the computer vision and pattern recognition communities. One reason for this
+growing interest is due to a wide spectrum of possible applications in diverse areas, such as
+more engaging human-computer interaction (HCI) systems, video conferencing, augmented
+reality.  Additionally  from  the  biometric  perspective,  automatic  recognition  of  facial
+expressions has been investigated in the context of monitoring patients in the intensive care
+nd neonatal units for signs of pain and anxiety, behavioural research, identifying level of
+oncentration, and improving face recognition.
+Automatic  facial  expression  recognition  is  a  difficult  task  due  to  its  inherent  subjective
+nature,  which  is  additionally  hampered  by  usual  difficulties  encountered  in  pattern
+recognition and computer vision research. The vast majority of the current state-of-the-art"
+05a7be10fa9af8fb33ae2b5b72d108415519a698,Multilayer and Multimodal Fusion of Deep Neural Networks for Video Classification,"Multilayer and Multimodal Fusion of Deep Neural Networks
+for Video Classiﬁcation
+Xiaodong Yang Pavlo Molchanov Jan Kautz
+{xiaodongy, pmolchanov,
+NVIDIA"
+050a149051a5d268fcc5539e8b654c2240070c82,Magisterské a doktorské studijnı́ programy,MAGISTERSKÉ A DOKTORSKÉSTUDIJNÍ PROGRAMY31. 5. 2018SBORNÍKSTUDENTSKÁ VĚDECKÁ KONFERENCE
+0580edbd7865414c62a36da9504d1169dea78d6f,Baseline CNN structure analysis for facial expression recognition,"Baseline CNN structure analysis for facial expression recognition
+Minchul Shin1, Munsang Kim2 and Dong-Soo Kwon1"
+9d58e8ab656772d2c8a99a9fb876d5611fe2fe20,Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video,"Beyond Temporal Pooling: Recurrence and Temporal
+Convolutions for Gesture Recognition in Video
+Lionel Pigou, A¨aron van den Oord∗ , Sander Dieleman∗ ,
+{lionel.pigou,aaron.vandenoord,sander.dieleman,
+Mieke Van Herreweghe & Joni Dambre
+mieke.vanherreweghe,
+Ghent University
+February 11, 2016"
+9d42df42132c3d76e3447ea61e900d3a6271f5fe,AutoCAP: An Automatic Caption Generation System based on the Text Knowledge Power Series Representation Model,"International Journal of Computer Applications (0975 – 8887)
+Advanced Computing and Communication Techniques for High Performance Applications (ICACCTHPA-2014)
+AutoCAP: An Automatic Caption Generation System
+ased on the Text Knowledge Power Series
+Representation Model
+Krishnapriya P S
+M.Tech Dept of CSE
+NSS College of Engineering
+Palakkad, Kerala"
+9d8fd639a7aeab0dd1bc6eef9d11540199fd6fe2,L Earning to C Luster,"Workshop track - ICLR 2018
+LEARNING TO CLUSTER
+Benjamin B. Meier, Thilo Stadelmann & Oliver D¨urr
+ZHAW Datalab, Zurich University of Applied Sciences
+Winterthur, Switzerland"
+9d357bbf014289fb5f64183c32aa64dc0bd9f454,Face Identification by Fitting a 3D Morphable Model Using Linear Shape and Texture Error Functions,"Face Identiﬁcation by Fitting a 3D Morphable Model
+using Linear Shape and Texture Error Functions
+Sami Romdhani, Volker Blanz, and Thomas Vetter
+University of Freiburg, Instit¨ut f¨ur Informatik,
+Georges-K¨ohler-Allee 52, 79110 Freiburg, Germany,
+fromdhani, volker,"
+9d839dfc9b6a274e7c193039dfa7166d3c07040b,Augmented faces,"Augmented Faces
+Matthias Dantone1
+Lukas Bossard1
+Till Quack1,2
+Luc van Gool1,3
+ETH Z¨urich
+Kooaba AG
+K.U. Leuven"
+9d36c81b27e67c515df661913a54a797cd1260bb,3d Face Recognition Techniques - a Review,"Preeti.B.Sharma, Mahesh M. Goyani / International Journal of Engineering Research and
+Applications (IJERA)      ISSN: 2248-9622                           www.ijera.com
+Vol. 2, Issue 1,Jan-Feb 2012, pp.787-793
+3D FACE RECOGNITION TECHNIQUES - A REVIEW
+Preeti B. Sharma*, Mahesh M. Goyani**
+*(Department of Information Technology, Gujarat Technological University, India)
+**( Department of Computer Engineering, Gujarat Technological University, India)
+security  at  many  places"
+9d757c0fede931b1c6ac344f67767533043cba14,Search Based Face Annotation Using PCA and Unsupervised Label Refinement Algorithms,"Search Based Face Annotation Using PCA and
+Unsupervised Label Refinement Algorithms
+Shital Shinde1, Archana Chaugule2
+Computer Department, Savitribai Phule Pune University
+D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune-18
+Mahatma Phulenagar, 120/2 Mahaganpati soc, Chinchwad, Pune-19, MH, India
+D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune-18
+Computer Department, D.Y.PIET, Pimpri, Pune-18, MH, India
+presents"
+9d60ad72bde7b62be3be0c30c09b7d03f9710c5f,A Survey: Face Recognition Techniques,"A Survey: Face Recognition Techniques
+Arun Agrawal
+Assistant Professor, ITM GOI
+Ranjana Sikarwar
+M Tech, ITM GOI
+video
+(Eigen
+passport-verification,"
+9c1305383ce2c108421e9f5e75f092eaa4a5aa3c,Speaker Retrieval for Tv Show Videos by Associating Audio Speaker Recognition Result to Visual Faces∗,"SPEAKER RETRIEVAL FOR TV SHOW VIDEOS BY ASSOCIATING AUDIO SPEAKER
+RECOGNITION RESULT TO VISUAL FACES∗
+Yina Han*’, Joseph Razik’, Gerard Chollet’, and Guizhong Liu*
+*School of Electrical and Information Engineering, Xi’an Jiaotong University, Xi’an, China
+’CNRS-LTCI, TELECOM-ParisTech, Paris, France"
+9c1860de6d6e991a45325c997bf9651c8a9d716f,3D reconstruction and face recognition using kernel-based ICA and neural networks,"D Reconstruction and Face Recognition Using Kernel-Based
+ICA and Neural Networks
+Cheng-Jian Lin                  Ya-Tzu Huang
+Chi-Yung Lee
+Dept. of Electrical                Dept. of CSIE                    Dept. of CSIE
+Engineering              Chaoyang University              Nankai Institute of
+National University            of Technology                        Technology
+of Kaohsiung"
+9ca7899338129f4ba6744f801e722d53a44e4622,Deep neural networks regularization for structured output prediction,"Deep Neural Networks Regularization for Structured
+Output Prediction
+Souﬁane Belharbi∗
+INSA Rouen, LITIS
+76000 Rouen, France
+Clément Chatelain
+INSA Rouen, LITIS
+76000 Rouen, France
+Romain Hérault
+INSA Rouen, LITIS
+76000 Rouen, France
+Sébastien Adam
+INSA Rouen, LITIS
+76000 Rouen, France
+Normandie Univ, UNIROUEN, UNIHAVRE,
+Normandie Univ, UNIROUEN, UNIHAVRE,
+Normandie Univ, UNIROUEN, UNIHAVRE,
+Normandie Univ, UNIROUEN, UNIHAVRE,"
+9c1664f69d0d832e05759e8f2f001774fad354d6,Action Representations in Robotics: A Taxonomy and Systematic Classification,"Action representations in robotics: A
+taxonomy and systematic classiﬁcation
+Journal Title
+XX(X):1–32
+(cid:13)The Author(s) 2016
+Reprints and permission:
+sagepub.co.uk/journalsPermissions.nav
+DOI: 10.1177/ToBeAssigned
+www.sagepub.com/
+Philipp Zech, Erwan Renaudo, Simon Haller, Xiang Zhang and Justus Piater"
+9c065dfb26ce280610a492c887b7f6beccf27319,Learning from Video and Text via Large-Scale Discriminative Clustering,"Learning from Video and Text via Large-Scale Discriminative Clustering
+Antoine Miech1,2
+Jean-Baptiste Alayrac1,2
+Piotr Bojanowski2
+Ivan Laptev 1,2
+Josef Sivic1,2,3
+´Ecole Normale Sup´erieure
+Inria
+CIIRC"
+9c781f7fd5d8168ddae1ce5bb4a77e3ca12b40b6,Attribute Based Face Classification Using Support Vector Machine,"International Research Journal of Engineering and Technology (IRJET)      e-ISSN: 2395 -0056
+Volume: 03 Issue: 07 | July-2016                       www.irjet.net                                                               p-ISSN: 2395-0072
+Attribute Based Face Classification Using Support Vector Machine
+Brindha.M1, Amsaveni.R2
+Research Scholar, Dept. of Computer Science, PSGR Krishnammal College for Women, Coimbatore
+Assistant Professor, Dept. of Information Technology, PSGR Krishnammal College for Women, Coimbatore."
+9ce0d64125fbaf625c466d86221505ad2aced7b1,Recognizing expressions of children in real life scenarios View project PhD ( Doctor of Philosophy ) View project,"Saliency Based Framework for Facial Expression
+Recognition
+Rizwan Ahmed Khan, Alexandre Meyer, Hubert Konik, Saïda Bouakaz
+To cite this version:
+Rizwan Ahmed Khan, Alexandre Meyer, Hubert Konik, Saïda Bouakaz. Saliency Based Framework for
+Facial Expression Recognition. Frontiers of Computer Science, 2017, <10.1007/s11704-017-6114-9>.
+<hal-01546192>
+HAL Id: hal-01546192
+https://hal.archives-ouvertes.fr/hal-01546192
+Submitted on 23 Jun 2017
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entific research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destinée au dépôt et à la diffusion de documents
+scientifiques de niveau recherche, publiés ou non,
+émanant des établissements d’enseignement et de"
+02601d184d79742c7cd0c0ed80e846d95def052e,Graphical Representation for Heterogeneous Face Recognition,"Graphical Representation for Heterogeneous
+Face Recognition
+Chunlei Peng, Xinbo Gao, Senior Member, IEEE, Nannan Wang, Member, IEEE, and Jie Li"
+02e43d9ca736802d72824892c864e8cfde13718e,Transferring a semantic representation for person re-identification and search,"Transferring a Semantic Representation for Person Re-Identification and
+Search
+Shi, Z; Yang, Y; Hospedales, T; XIANG, T; IEEE Conference on Computer Vision and
+Pattern Recognition
+© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be
+obtained for all other uses, in any current or future media, including reprinting/republishing
+this material for advertising or promotional purposes, creating new collective works, for resale
+or redistribution to servers or lists, or reuse of any copyrighted component of this work in
+other works.
+For additional information about this publication click this link.
+http://qmro.qmul.ac.uk/xmlui/handle/123456789/10075
+Information about this research object was correct at the time of download; we occasionally
+make corrections to records, please therefore check the published record when citing. For
+more information contact"
+02fda07735bdf84554c193811ba4267c24fe2e4a,Illumination Invariant Face Recognition Using Near-Infrared Images,"Illumination Invariant Face Recognition
+Using Near-Infrared Images
+Stan Z. Li, Senior Member, IEEE, RuFeng Chu, ShengCai Liao, and Lun Zhang"
+0241513eeb4320d7848364e9a7ef134a69cbfd55,Supervised translation-invariant sparse coding,"Supervised Translation-Invariant Sparse
+Coding
+¹Jianchao Yang, ²Kai Yu, and ¹Thomas Huang
+¹University of Illinois at Urbana Champaign
+²NEC Laboratories America at Cupertino"
+02dd0af998c3473d85bdd1f77254ebd71e6158c6,PPP: Joint Pointwise and Pairwise Image Label Prediction,"PPP: Joint Pointwise and Pairwise Image Label Prediction
+Yilin Wang1 Suhang Wang1
+Jiliang Tang2 Huan Liu1 Baoxin Li1
+Department of Computer Science, Arizona State Univerity
+Yahoo Research"
+029317f260b3303c20dd58e8404a665c7c5e7339,Character Identification in Feature-Length Films Using Global Face-Name Matching,"Character Identiﬁcation in Feature-Length Films
+Using Global Face-Name Matching
+Yi-Fan Zhang, Student Member, IEEE, Changsheng Xu, Senior Member, IEEE, Hanqing Lu, Senior Member, IEEE,
+nd Yeh-Min Huang, Member, IEEE"
+0273414ba7d56ab9ff894959b9d46e4b2fef7fd0,Photographic home styles in Congress: a computer vision approach,"Photographic home styles in Congress: a
+omputer vision approach∗
+L. Jason Anastasopoulos†.
+Dhruvil Badani‡
+Crystal Lee§
+Shiry Ginosar¶
+Jake Williams(cid:107)
+December 1, 2016"
+02e133aacde6d0977bca01ffe971c79097097b7f,Convolutional Neural Fabrics,
+02567fd428a675ca91a0c6786f47f3e35881bcbd,Deep Label Distribution Learning With Label Ambiguity,"ACCEPTED BY IEEE TIP
+Deep Label Distribution Learning
+With Label Ambiguity
+Bin-Bin Gao, Chao Xing, Chen-Wei Xie, Jianxin Wu, Member, IEEE, and Xin Geng, Member, IEEE"
+0278acdc8632f463232e961563e177aa8c6d6833,Selective Transfer Machine for Personalized Facial Expression Analysis,"Selective Transfer Machine for Personalized
+Facial Expression Analysis
+Wen-Sheng Chu, Fernando De la Torre, and Jeffrey F. Cohn
+INTRODUCTION
+Index Terms—Facial expression analysis, personalization, domain adaptation, transfer learning, support vector machine (SVM)
+A UTOMATIC facial AU detection confronts a number of"
+a4a5ad6f1cc489427ac1021da7d7b70fa9a770f2,Gated spatio and temporal convolutional neural network for activity recognition: towards gated multimodal deep learning,"Yudistira and Kurita EURASIP Journal on Image and Video
+Processing  (2017) 2017:85
+DOI 10.1186/s13640-017-0235-9
+EURASIP Journal on Image
+nd Video Processing
+RESEARCH
+Open Access
+Gated spatio and temporal convolutional
+neural network for activity recognition:
+towards gated multimodal deep learning
+Novanto Yudistira1* and Takio Kurita2"
+a40f8881a36bc01f3ae356b3e57eac84e989eef0,"End-to-end semantic face segmentation with conditional random fields as convolutional, recurrent and adversarial networks","End-to-end semantic face segmentation with conditional
+random ﬁelds as convolutional, recurrent and adversarial
+networks
+Umut Güçlü*, 1, Yağmur Güçlütürk*, 1,
+Meysam Madadi2, Sergio Escalera3, Xavier Baró4, Jordi González2,
+Rob van Lier1, Marcel van Gerven1"
+a4a0b5f08198f6d7ea2d1e81bd97fea21afe3fc3,Efficient Recurrent Residual Networks Improved by Feature Transfer,"E
+Feature Transfer
+MSc Thesis
+written by
+Yue Liu
+under the supervision of Dr. Silvia-Laura Pintea, Dr. Jan van Gemert,
+nd Dr. Ildiko Suveg and submitted to the Board of Examiners for the
+degree of
+Master of Science
+t the Delft University of Technology.
+Date of the public defense: Members of the Thesis Committee:
+August 31, 2017
+Prof. Marcel Reinders
+Dr. Jan van Gemert
+Dr. Julian Urbano Merino
+Dr. Silvia-Laura Pintea
+Dr. Ildiko Suveg (Bosch)
+Dr. Gonzalez Adrlana (Bosch)"
+a44590528b18059b00d24ece4670668e86378a79,Learning the Hierarchical Parts of Objects by Deep Non-Smooth Nonnegative Matrix Factorization,"Learning the Hierarchical Parts of Objects by Deep
+Non-Smooth Nonnegative Matrix Factorization
+Jinshi Yu, Guoxu Zhou, Andrzej Cichocki
+IEEE Fellow, and Shengli Xie IEEE Senior Member"
+a4c430b7d849a8f23713dc283794d8c1782198b2,Video Concept Embedding,"Video Concept Embedding
+Anirudh Vemula
+Rahul Nallamothu
+Syed Zahir Bokhari
+. Introduction
+In the area of natural language processing, there has been
+much success in learning distributed representations for
+words as vectors. Doing so has an advantage over using
+simple labels, or a one-hot coding scheme for representing
+individual words. In learning distributed vector representa-
+tions for words, we manage to capture semantic relatedness
+of words in vector distance. For example, the word vector
+for ”car” and ”road” should end up being closer together in
+the vector space representation than ”car” and ”penguin”.
+This has been very useful in NLP areas of machine transla-
+tion and semantic understanding.
+In the computer vision domain, video understanding is a
+very important topic.
+It is made hard due to the large
+mount of high dimensional data in videos. One strategy"
+a4f37cfdde3af723336205b361aefc9eca688f5c,Recent Advances in Face Recognition,"Recent Advances
+in Face Recognition"
+a30869c5d4052ed1da8675128651e17f97b87918,Fine-Grained Comparisons with Attributes,"Fine-Grained Comparisons with Attributes
+Aron Yu and Kristen Grauman"
+a3ebacd8bcbc7ddbd5753935496e22a0f74dcf7b,"First International Workshop on Adaptive Shot Learning for Gesture Understanding and Production ASL4GUP 2017 Held in conjunction with IEEE FG 2017, in May 30, 2017, Washington DC, USA","First International Workshop on Adaptive Shot Learning
+for Gesture Understanding and Production
+ASL4GUP 2017
+Held in conjunction with IEEE FG 2017, in May 30, 2017,
+Washington DC, USA"
+a3d8b5622c4b9af1f753aade57e4774730787a00,Pose-Aware Person Recognition,"Pose-Aware Person Recognition
+Vijay Kumar (cid:63)
+Anoop Namboodiri (cid:63)
+(cid:63) CVIT, IIIT Hyderabad, India
+Manohar Paluri †
+Facebook AI Research
+C. V. Jawahar (cid:63)"
+a3017bb14a507abcf8446b56243cfddd6cdb542b,Face Localization and Recognition in Varied Expressions and Illumination,"Face Localization and Recognition in Varied
+Expressions and Illumination
+Hui-Yu Huang, Shih-Hang Hsu"
+a3c8c7da177cd08978b2ad613c1d5cb89e0de741,A Spatio-temporal Approach for Multiple Object Detection in Videos Using Graphs and Probability Maps,"A Spatio-temporal Approach for Multiple
+Object Detection in Videos Using Graphs
+nd Probability Maps
+Henrique Morimitsu1(B), Roberto M. Cesar Jr.1, and Isabelle Bloch2
+University of S˜ao Paulo, S˜ao Paulo, Brazil
+Institut Mines T´el´ecom, T´el´ecom ParisTech, CNRS LTCI, Paris, France"
+a378fc39128107815a9a68b0b07cffaa1ed32d1f,Determining a Suitable Metric when Using Non-Negative Matrix Factorization,"Determining a Suitable Metric When using Non-negative Matrix Factorization∗
+David Guillamet and Jordi Vitri`a
+Computer Vision Center, Dept. Inform`atica
+Universitat Aut`onoma de Barcelona
+08193 Bellaterra, Barcelona, Spain"
+a34d75da87525d1192bda240b7675349ee85c123,Naive-Deep Face Recognition: Touching the Limit of LFW Benchmark or Not?,"Naive-Deep Face Recognition: Touching the Limit of LFW Benchmark or Not?
+Erjin Zhou
+Face++, Megvii Inc.
+Zhimin Cao
+Face++, Megvii Inc.
+Qi Yin
+Face++, Megvii Inc."
+a3dc109b1dff3846f5a2cc1fe2448230a76ad83f,Active Appearance Model and Pca Based Face Recognition System,"J.Savitha et al, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.4, April- 2015, pg. 722-731
+Available Online at www.ijcsmc.com
+International Journal of Computer Science and Mobile Computing
+A Monthly Journal of Computer Science and Information Technology
+ISSN 2320–088X
+IJCSMC, Vol. 4, Issue. 4, April 2015, pg.722 – 731
+RESEARCH ARTICLE
+ACTIVE APPEARANCE MODEL AND PCA
+BASED FACE RECOGNITION SYSTEM
+Mrs. J.Savitha M.Sc., M.Phil.
+Ph.D Research Scholar, Karpagam University, Coimbatore, Tamil Nadu, India
+Email:
+Dr. A.V.Senthil Kumar
+Director, Hindustan College of Arts and Science, Coimbatore, Tamil Nadu, India
+Email:"
+a3f69a073dcfb6da8038607a9f14eb28b5dab2db,3D-Aided Deep Pose-Invariant Face Recognition,Proceedings of the Twenty-Seventh International Joint Conference on Artiﬁcial Intelligence (IJCAI-18)
+a38045ed82d6800cbc7a4feb498e694740568258,African American and Caucasian males ' evaluation of racialized female facial averages,"UNLV Theses, Dissertations, Professional Papers, and Capstones
+5-2010
+African American and Caucasian males' evaluation
+of racialized female facial averages
+Rhea M. Watson
+University of Nevada Las Vegas
+Follow this and additional works at: http://digitalscholarship.unlv.edu/thesesdissertations
+Part of the Cognition and Perception Commons, Race and Ethnicity Commons, and the Social
+Psychology Commons
+Repository Citation
+Watson, Rhea M., ""African American and Caucasian males' evaluation of racialized female facial averages"" (2010). UNLV Theses,
+Dissertations, Professional Papers, and Capstones. 366.
+http://digitalscholarship.unlv.edu/thesesdissertations/366
+This Thesis is brought to you for free and open access by Digital It has been accepted for inclusion in UNLV Theses, Dissertations,
+Professional Papers, and Capstones by an authorized administrator of Digital For more information, please contact"
+a3f78cc944ac189632f25925ba807a0e0678c4d5,Action Recognition in Realistic Sports Videos,"Action Recognition in Realistic Sports Videos
+Khurram Soomro and Amir Roshan Zamir"
+a3a6a6a2eb1d32b4dead9e702824375ee76e3ce7,Multiple Local Curvature Gabor Binary Patterns for Facial Action Recognition,"Multiple Local Curvature Gabor Binary
+Patterns for Facial Action Recognition
+Anıl Y¨uce, Nuri Murat Arar and Jean-Philippe Thiran
+Signal Processing Laboratory (LTS5),
+´Ecole Polytechnique F´ed´erale de Lausanne, Switzerland"
+a32c5138c6a0b3d3aff69bcab1015d8b043c91fb,Video redaction: a survey and comparison of enabling technologies,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 9/19/2018
+Terms of Use: https://www.spiedigitallibrary.org/terms-of-use
+Videoredaction:asurveyandcomparisonofenablingtechnologiesShaganSahAmeyaShringiRaymondPtuchaAaronBurryRobertLoceShaganSah,AmeyaShringi,RaymondPtucha,AaronBurry,RobertLoce,“Videoredaction:asurveyandcomparisonofenablingtechnologies,”J.Electron.Imaging26(5),051406(2017),doi:10.1117/1.JEI.26.5.051406."
+a3d78bc94d99fdec9f44a7aa40c175d5a106f0b9,Recognizing Violence in Movies,"Recognizing Violence in Movies
+CIS400/401 Project Final Report
+Lei Kang
+Univ. of Pennsylvania
+Philadelphia, PA
+Matteus Pan
+Univ. of Pennsylvania
+Philadelphia, PA
+Ben Sapp
+Univ. of Pennsylvania
+Philadelphia, PA
+Ben Taskar
+Univ. of Pennsylvania
+Philadelphia, PA"
+a3eab933e1b3db1a7377a119573ff38e780ea6a3,Sparse Representation for accurate classification of corrupted and occluded facial expressions,"978-1-4244-4296-6/10/$25.00 ©2010 IEEE
+ICASSP 2010"
+a3a34c1b876002e0393038fcf2bcb00821737105,Face Identification across Different Poses and Illuminations with a 3D Morphable Model,"Face Identiﬁcation across Different Poses and Illuminations
+with a 3D Morphable Model
+V. Blanz, S. Romdhani, and T. Vetter
+University of Freiburg
+Georges-K¨ohler-Allee 52, 79110 Freiburg, Germany
+fvolker, romdhani,"
+a3f1db123ce1818971a57330d82901683d7c2b67,Poselets and Their Applications in High-Level Computer Vision,"Poselets and Their Applications in High-Level
+Computer Vision
+Lubomir Bourdev
+Electrical Engineering and Computer Sciences
+University of California at Berkeley
+Technical Report No. UCB/EECS-2012-52
+http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-52.html
+May 1, 2012"
+a3a97bb5131e7e67316b649bbc2432aaa1a6556e,Role of the hippocampus and orbitofrontal cortex during the disambiguation of social cues in working memory.,"Cogn Affect Behav Neurosci
+DOI 10.3758/s13415-013-0170-x
+Role of the hippocampus and orbitofrontal cortex
+during the disambiguation of social cues in working memory
+Robert S. Ross & Matthew L. LoPresti & Karin Schon &
+Chantal E. Stern
+# Psychonomic Society, Inc. 2013"
+a35d3ba191137224576f312353e1e0267e6699a1,Increasing security in DRM systems through biometric authentication,"Javier Ortega-Garcia, Josef Bigun, Douglas Reynolds,
+nd Joaquin Gonzalez-Rodriguez
+Increasing security in DRM systems
+through biometric authentication.
+ecuring  the  exchange
+of  intellectual  property
+nd  providing  protection
+to  multimedia  contents  in
+distribution systems have enabled the
+dvent  of  digital  rights  management
+(DRM)  systems  [5],  [14],  [21],  [47],
+[51], [53]. Rights holders should be able to
+license, monitor, and track the usage of rights
+in  a  dynamic  digital  trading  environment,  espe-
+ially in the near future when universal multimedia
+ccess (UMA) becomes a reality, and any multimedia
+ontent  will  be  available  anytime,  anywhere.  In  such
+DRM  systems,  encryption  algorithms,  access  control,
+key  management  strategies,  identification  and  tracing
+of contents, or copy control will play a prominent role"
+b558be7e182809f5404ea0fcf8a1d1d9498dc01a,Bottom-up and top-down reasoning with convolutional latent-variable models,"Bottom-up and top-down reasoning with convolutional latent-variable models
+Peiyun Hu
+UC Irvine
+Deva Ramanan
+UC Irvine"
+b5cd8151f9354ee38b73be1d1457d28e39d3c2c6,Finding Celebrities in Video,"Finding Celebrities in Video
+Nazli Ikizler
+Jai Vasanth
+Linus Wong
+David Forsyth
+Electrical Engineering and Computer Sciences
+University of California at Berkeley
+Technical Report No. UCB/EECS-2006-77
+http://www.eecs.berkeley.edu/Pubs/TechRpts/2006/EECS-2006-77.html
+May 23, 2006"
+b5fc4f9ad751c3784eaf740880a1db14843a85ba,Significance of image representation for face verification,"SIViP (2007) 1:225–237
+DOI 10.1007/s11760-007-0016-5
+ORIGINAL PAPER
+Signiﬁcance of image representation for face veriﬁcation
+Anil Kumar Sao · B. Yegnanarayana ·
+B. V. K. Vijaya Kumar
+Received: 29 August 2006 / Revised: 28 March 2007 / Accepted: 28 March 2007 / Published online: 1 May 2007
+© Springer-Verlag London Limited 2007"
+b599f323ee17f12bf251aba928b19a09bfbb13bb,Autonomous Quadcopter Videographer,"AUTONOMOUS QUADCOPTER VIDEOGRAPHER
+REY R. COAGUILA
+B.S. Universidad Peruana de Ciencias Aplicadas, 2009
+A thesis submitted in partial fulﬁllment of the requirements
+for the degree of Master of Science in Computer Science
+in the Department of Electrical Engineering and Computer Science
+in the College of Engineering and Computer Science
+t the University of Central Florida
+Orlando, Florida
+Spring Term
+Major Professor: Gita R. Sukthankar"
+b5160e95192340c848370f5092602cad8a4050cd,Video Classification With CNNs: Using The Codec As A Spatio-Temporal Activity Sensor,"IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, TO APPEAR
+Video Classiﬁcation With CNNs: Using The Codec
+As A Spatio-Temporal Activity Sensor
+Aaron Chadha, Alhabib Abbas and Yiannis Andreopoulos, Senior Member, IEEE"
+b52c0faba5e1dc578a3c32a7f5cfb6fb87be06ad,Robust Face Recognition Technique under Varying Illumination,"Journal of Applied Research and
+Technology
+ISSN: 1665-6423
+Centro de Ciencias Aplicadas y
+Desarrollo Tecnológico
+México
+Hussain Shah, Jamal; Sharif, Muhammad; Raza, Mudassar; Murtaza, Marryam; Ur-Rehman, Saeed
+Robust Face Recognition Technique under Varying Illumination
+Journal of Applied Research and Technology, vol. 13, núm. 1, febrero, 2015, pp. 97-105
+Centro de Ciencias Aplicadas y Desarrollo Tecnológico
+Distrito Federal, México
+Available in: http://www.redalyc.org/articulo.oa?id=47436895009
+How to cite
+Complete issue
+More information about this article
+Journal's homepage in redalyc.org
+Scientific Information System
+Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal
+Non-profit academic project, developed under the open access initiative"
+b52886610eda6265a2c1aaf04ce209c047432b6d,Microexpression Identification and Categorization Using a Facial Dynamics Map,"Microexpression Identiﬁcation and Categorization
+using a Facial Dynamics Map
+Feng Xu, Junping Zhang, James Z. Wang"
+b5857b5bd6cb72508a166304f909ddc94afe53e3,SSIG and IRISA at Multimodal Person Discovery,"SSIG and IRISA at Multimodal Person Discovery
+Cassio E. dos Santos Jr1, Guillaume Gravier2, William Robson Schwartz1
+Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
+IRISA & Inria Rennes , CNRS, Rennes, France"
+b51e3d59d1bcbc023f39cec233f38510819a2cf9,"Can a biologically-plausible hierarchy effectively replace face detection, alignment, and recognition pipelines?","CBMM Memo No. 003
+March 27, 2014
+Can a biologically-plausible hierarchy effectively
+replace face detection, alignment, and
+recognition pipelines?
+Qianli Liao1, Joel Z Leibo1, Youssef Mroueh1, Tomaso Poggio1"
+b54c477885d53a27039c81f028e710ca54c83f11,Semi-Supervised Kernel Mean Shift Clustering,"Semi-Supervised Kernel Mean Shift Clustering
+Saket Anand, Member, IEEE, Sushil Mittal, Member, IEEE, Oncel Tuzel, Member, IEEE,
+nd Peter Meer, Fellow, IEEE"
+b55d0c9a022874fb78653a0004998a66f8242cad,Hybrid Facial Representations for Emotion Recognition Woo,"Hybrid Facial Representations
+for Emotion Recognition
+Woo-han Yun, DoHyung Kim, Chankyu Park, and Jaehong Kim
+Automatic  facial  expression  recognition  is  a  widely
+studied  problem  in  computer  vision  and  human-robot
+interaction.  There  has  been  a  range  of  studies  for
+representing  facial  descriptors  for  facial  expression
+recognition. Some prominent descriptors were presented
+in  the  first  facial  expression  recognition  and  analysis
+hallenge  (FERA2011).  In  that  competition,  the  Local
+Gabor  Binary  Pattern  Histogram  Sequence  descriptor
+showed the most powerful description capability. In this
+paper, we introduce hybrid facial representations for facial
+expression  recognition,  which  have  more  powerful
+description  capability  with  lower  dimensionality.  Our
+descriptors consist of a block-based descriptor and a pixel-
+ased  descriptor.  The  block-based  descriptor  represents
+the  micro-orientation  and  micro-geometric  structure
+information. The pixel-based descriptor represents texture
+information.  We  validate  our  descriptors  on  two  public"
+b261439b5cde39ec52d932a222450df085eb5a91,Facial Expression Recognition using Analytical Hierarchy Process,"International Journal of Computer Trends and Technology (IJCTT) – volume 24 Number 2 – June 2015
+Facial Expression Recognition using Analytical Hierarchy
+Process
+MTech Student 1 , Assistant Professor 2  , Department of Computer Science and Engineeringt1, 2, Disha Institute of
+Management and Technology, Raipur Chhattisgarh, India1, 2
+Vinita Phatnani1, Akash Wanjari2,
+its  significant  contribution"
+b2b535118c5c4dfcc96f547274cdc05dde629976,Automatic Recognition of Facial Displays of Unfelt Emotions,"JOURNAL OF IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, VOL. XX, NO. X, XXX 2017
+Automatic Recognition of Facial Displays of
+Unfelt Emotions
+Kaustubh Kulkarni*, Ciprian Adrian Corneanu*, Ikechukwu Ofodile*, Student Member, IEEE, Sergio
+Escalera, Xavier Bar´o, Sylwia Hyniewska, Member, IEEE, J¨uri Allik,
+nd Gholamreza Anbarjafari, Senior Member, IEEE"
+b235b4ccd01a204b95f7408bed7a10e080623d2e,Regularizing Flat Latent Variables with Hierarchical Structures,"Regularizing Flat Latent Variables with Hierarchical Structures
+Rongcheng Lin(cid:117) , Huayu Li(cid:117) , Xiaojun Quan† , Richang Hong(cid:63) , Zhiang Wu∓ , Yong Ge(cid:117)
+(cid:117)UNC Charlotte. Email: {rlin4, hli38,
+(cid:63) Hefei University of Technology. Email:
+Institute for Infocomm Research. Email:
+∓ Nanjing University of Finance and Economics. Email:"
+b29b42f7ab8d25d244bfc1413a8d608cbdc51855,Effective face landmark localization via single deep network,"EFFECTIVE FACE LANDMARK LOCALIZATION VIA SINGLE DEEP NETWORK
+Zongping Deng1,2, Ke Li1, Qijun Zhao1,2, Yi Zhang2 and Hu Chen1,2,3
+National Key Laboratory of Fundamental Science on Synthetic Vision
+School of Computer Science, Sichuan University, Chengdu, China, 610065"
+b2c25af8a8e191c000f6a55d5f85cf60794c2709,A novel dimensionality reduction technique based on kernel optimization through graph embedding,"Noname manuscript No.
+(will be inserted by the editor)
+A Novel Dimensionality Reduction Technique based on
+Kernel Optimization Through Graph Embedding
+N. Vretos, A. Tefas and I. Pitas
+the date of receipt and acceptance should be inserted later"
+d904f945c1506e7b51b19c99c632ef13f340ef4c,0 ° 15 ° 30 ° 45 ° 60 ° 75 ° 90 °,"A scalable 3D HOG model for fast object detection and viewpoint estimation
+Marco Pedersoli
+Tinne Tuytelaars
+KU Leuven, ESAT/PSI - iMinds
+Kasteelpark Arenberg 10 B-3001 Leuven, Belgium"
+d9810786fccee5f5affaef59bc58d2282718af9b,Adaptive Frame Selection for Enhanced Face Recognition in Low-Resolution Videos,"Adaptive Frame Selection for
+Enhanced Face Recognition in
+Low-Resolution Videos
+Raghavender Reddy Jillela
+Thesis submitted to the
+College of Engineering and Mineral Resources
+t West Virginia University
+in partial fulﬁllment of the requirements
+for the degree of
+Master of Science
+Electrical Engineering
+Arun Ross, PhD., Chair
+Xin Li, PhD.
+Donald Adjeroh, PhD.
+Lane Department of Computer Science and Electrical Engineering
+Morgantown, West Virginia
+Keywords: Face Biometrics, Super-Resolution, Optical Flow, Super-Resolution using
+Optical Flow, Adaptive Frame Selection, Inter-Frame Motion Parameter, Image Quality,
+Image-Level Fusion, Score-Level Fusion
+Copyright 2008 Raghavender Reddy Jillela"
+d94d7ff6f46ad5cab5c20e6ac14c1de333711a0c,Face Album: Towards automatic photo management based on person identity on mobile phones,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE
+ICASSP 2017"
+d930ec59b87004fd172721f6684963e00137745f,Face Pose Estimation using a Tree of Boosted Classifiers,"Face Pose Estimation using a
+Tree of Boosted Classifiers
+Javier Cruz Mota
+Project Assistant: Julien Meynet
+Professor: Jean-Philippe Thiran
+Signal Processing Institute,
+´Ecole Polytechnique F´ed´erale de Lausanne (EPFL)
+September 11, 2006"
+d9318c7259e394b3060b424eb6feca0f71219179,Face Matching and Retrieval Using Soft Biometrics,"Face Matching and Retrieval Using Soft Biometrics
+Unsang Park, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
+d9ef1a80738bbdd35655c320761f95ee609b8f49,A Research - Face Recognition by Using Near Set Theory,"Volume 5, Issue 4, 2015                                     ISSN: 2277 128X
+International Journal of Advanced Research in
+Computer Science and Software Engineering
+Research Paper
+Available online at: www.ijarcsse.com
+A Research - Face Recognition by Using Near Set Theory
+Manisha V. Borkar, Bhakti Kurhade
+Department of Computer Science and  Engineering
+Abha Gaikwad -Patil College of  Engineering, Nagpur, Maharashtra, India"
+d9c4b1ca997583047a8721b7dfd9f0ea2efdc42c,Learning Inference Models for Computer Vision,Learning Inference Models for Computer Vision
+d9bad7c3c874169e3e0b66a031c8199ec0bc2c1f,"It All Matters: Reporting Accuracy, Inference Time and Power Consumption for Face Emotion Recognition on Embedded Systems","It All Matters:
+Reporting Accuracy, Inference Time and Power Consumption
+for Face Emotion Recognition on Embedded Systems
+Jelena Milosevic
+Institute of Telecommunications, TU Wien
+Andrew Forembsky
+Movidius an Intel Company
+Dexmont Pe˜na
+Movidius an Intel Company
+David Moloney
+Movidius an Intel Company
+Miroslaw Malek
+ALaRI, Faculty of Informatics, USI"
+d9327b9621a97244d351b5b93e057f159f24a21e,Laplacian smoothing transform for face recognition,"SCIENCE CHINA
+Information Sciences
+. RESEARCH PAPERS .
+December 2010 Vol. 53 No. 12: 2415–2428
+doi: 10.1007/s11432-010-4099-1
+Laplacian smoothing transform for face recognition
+GU SuiCheng, TAN Ying
+& HE XinGui
+Key Laboratory of Machine Perception (MOE); Department of Machine Intelligence,
+School of Electronics Engineering and Computer Science; Peking University, Beijing 100871, China
+Received March 16, 2009; accepted April 1, 2010"
+aca232de87c4c61537c730ee59a8f7ebf5ecb14f,Ebgm Vs Subspace Projection for Face Recognition,"EBGM VS SUBSPACE PROJECTION FOR FACE RECOGNITION
+Andreas Stergiou, Aristodemos Pnevmatikakis, Lazaros Polymenakos
+9.5 Km Markopoulou Avenue, P.O. Box 68, Peania, Athens, Greece
+Athens Information Technology
+Keywords:
+Human-Machine Interfaces, Computer Vision, Face Recognition."
+ac6a9f80d850b544a2cbfdde7002ad5e25c05ac6,Privacy-Protected Facial Biometric Verification Using Fuzzy Forest Learning,"Privacy-Protected Facial Biometric Veriﬁcation
+Using Fuzzy Forest Learning
+Richard Jiang, Ahmed Bouridane, Senior Member, IEEE, Danny Crookes, Senior Member, IEEE,
+M. Emre Celebi, Senior Member, IEEE, and Hua-Liang Wei"
+accbd6cd5dd649137a7c57ad6ef99232759f7544,Facial Expression Recognition with Local Binary Patterns and Linear Programming,"FACIAL EXPRESSION RECOGNITION WITH LOCAL BINARY PATTERNS
+AND LINEAR PROGRAMMING
+Xiaoyi Feng1, 2, Matti Pietikäinen1, Abdenour Hadid1
+Machine Vision Group, Infotech Oulu and Dept. of Electrical and Information Engineering
+P. O. Box 4500 Fin-90014 University of Oulu, Finland
+2 College of Electronics and Information, Northwestern Polytechnic University
+710072 Xi’an, China
+In  this  work,  we  propose  a  novel  approach  to  recognize  facial  expressions  from  static
+images. First, the Local Binary Patterns (LBP) are used to efficiently represent the facial
+images and then the Linear Programming (LP) technique is adopted to classify the seven
+facial  expressions  anger,  disgust,  fear,  happiness,  sadness,  surprise  and  neutral.
+Experimental results demonstrate an average recognition accuracy of 93.8% on the JAFFE
+database, which outperforms the rates of all other reported methods on the same database.
+Introduction
+Facial  expression  recognition  from  static
+images  is  a  more  challenging  problem
+than  from  image  sequences  because  less
+information  for  expression  actions
+vailable.  However,  information  in  a
+single  image  is  sometimes  enough  for"
+ac26166857e55fd5c64ae7194a169ff4e473eb8b,Personalized Age Progression with Bi-Level Aging Dictionary Learning,"Personalized Age Progression with Bi-level
+Aging Dictionary Learning
+Xiangbo Shu, Jinhui Tang, Senior Member, IEEE, Zechao Li, Hanjiang Lai, Liyan Zhang
+nd Shuicheng Yan, Fellow, IEEE"
+ac559873b288f3ac28ee8a38c0f3710ea3f986d9,Team DEEP-HRI Moments in Time Challenge 2018 Technical Report,"Team DEEP-HRI Moments in Time Challenge 2018 Technical Report
+Chao Li, Zhi Hou, Jiaxu Chen, Yingjia Bu, Jiqiang Zhou, Qiaoyong Zhong, Di Xie and Shiliang Pu
+Hikvision Research Institute"
+ac8e09128e1e48a2eae5fa90f252ada689f6eae7,Leolani: A Reference Machine with a Theory of Mind for Social Communication,"Leolani: a reference machine with a theory of
+mind for social communication
+Piek Vossen, Selene Baez, Lenka Baj˘ceti´c, and Bram Kraaijeveld
+VU University Amsterdam, Computational Lexicology and Terminology Lab, De
+Boelelaan 1105, 1081HV Amsterdam, The Netherlands
+www.cltl.nl"
+ac8441e30833a8e2a96a57c5e6fede5df81794af,Hierarchical Representation Learning for Kinship Verification,"IEEE TRANSACTIONS ON IMAGE PROCESSING
+Hierarchical Representation Learning for Kinship
+Veriﬁcation
+Naman Kohli, Student Member, IEEE, Mayank Vatsa, Senior Member, IEEE, Richa Singh, Senior Member, IEEE,
+Afzel Noore, Senior Member, IEEE, and Angshul Majumdar, Senior Member, IEEE"
+ac12ba5bf81de83991210b4cd95b4ad048317681,Combining Deep Facial and Ambient Features for First Impression Estimation,"Combining Deep Facial and Ambient Features
+for First Impression Estimation
+Furkan G¨urpınar1, Heysem Kaya2, Albert Ali Salah3
+Program of Computational Science and Engineering, Bo˘gazi¸ci University,
+Bebek, Istanbul, Turkey
+Department of Computer Engineering, Namık Kemal University,
+C¸ orlu, Tekirda˘g, Turkey
+Department of Computer Engineering, Bo˘gazi¸ci University,
+Bebek, Istanbul, Turkey"
+acb83d68345fe9a6eb9840c6e1ff0e41fa373229,"Kernel methods in computer vision: object localization, clustering, and taxonomy discovery","Kernel Methods in Computer Vision:
+Object Localization, Clustering,
+nd Taxonomy Discovery
+vorgelegt von
+Matthew Brian Blaschko, M.S.
+us La Jolla
+Von der Fakult¨at IV - Elektrotechnik und Informatik
+der Technischen Universit¨at Berlin
+zur Erlangung des akademischen Grades
+Doktor der Naturwissenschaften
+Dr. rer. nat.
+genehmigte Dissertation
+Promotionsausschuß:
+Vorsitzender: Prof. Dr. O. Hellwich
+Berichter: Prof. Dr. T. Hofmann
+Berichter: Prof. Dr. K.-R. M¨uller
+Berichter: Prof. Dr. B. Sch¨olkopf
+Tag der wissenschaftlichen Aussprache: 23.03.2009
+Berlin 2009"
+ade1034d5daec9e3eba1d39ae3f33ebbe3e8e9a7,Multimodal Caricatural Mirror,"Multimodal Caricatural Mirror
+Martin O.(1), Adell J.(2), Huerta A.(3), Kotsia I.(4), Savran A.(5), Sebbe R.(6)
+(1)  : Université catholique de Louvain, Belgium
+(2)  Universitat Polytecnica de Barcelona, Spain
+(3)  Universidad Polytècnica de Madrid, Spain
+(4)  Aristotle University of Thessaloniki, Greece
+(5)  Bogazici University, Turkey
+(6)  Faculté Polytechnique de Mons, Belgium"
+adf7ccb81b8515a2d05fd3b4c7ce5adf5377d9be,Apprentissage de métrique appliqué à la détection de changement de page Web et aux attributs relatifs,"Apprentissage de métrique appliqué à la
+détection de changement de page Web et
+ux attributs relatifs
+Marc T. Law* — Nicolas Thome* — Stéphane Gançarski* — Mat-
+thieu Cord*
+* Sorbonne Universités, UPMC Univ Paris 06, UMR 7606, LIP6, F-75005, Paris,
+France
+RÉSUMÉ. Nous proposons dans cet article un nouveau schéma d’apprentissage de métrique.
+Basé sur l’exploitation de contraintes qui impliquent des quadruplets d’images, notre approche
+vise à modéliser des relations sémantiques de similarités riches ou complexes. Nous étudions
+omment ce schéma peut être utilisé dans des contextes tels que la détection de régions impor-
+tantes dans des pages Web ou la reconnaissance à partir d’attributs relatifs."
+ada73060c0813d957576be471756fa7190d1e72d,VRPBench: A Vehicle Routing Benchmark Tool,"VRPBench: A Vehicle Routing Benchmark Tool
+October 19, 2016
+Guilherme A. Zeni1 , Mauro Menzori1, P. S. Martins1, Luis A. A. Meira1"
+adf5caca605e07ee40a3b3408f7c7c92a09b0f70,Line-Based PCA and LDA Approaches for Face Recognition,"Line-based PCA and LDA approaches for Face Recognition
+Vo Dinh Minh Nhat, and Sungyoung Lee
+Kyung Hee University – South of Korea
+{vdmnhat,"
+adaf2b138094981edd615dbfc4b7787693dbc396,Statistical methods for facial shape-from-shading and recognition,"Statistical Methods For Facial
+Shape-from-shading and Recognition
+William A. P. Smith
+Submitted for the degree of Doctor of Philosophy
+Department of Computer Science
+0th February 2007"
+adf62dfa00748381ac21634ae97710bb80fc2922,ViFaI : A trained video face indexing scheme Harsh,"ViFaI: A trained video face indexing scheme
+Harsh Nayyar
+Audrey Wei
+. Introduction
+With the increasing prominence of inexpensive
+video recording devices (e.g., digital camcorders and
+video recording smartphones),
+the average user’s
+video collection today is increasing rapidly. With this
+development, there arises a natural desire to rapidly
+ccess a subset of one’s collection of videos. The solu-
+tion to this problem requires an effective video index-
+ing scheme. In particular, we must be able to easily
+process a video to extract such indexes.
+Today, there also exist large sets of labeled (tagged)
+face images. One important example is an individual’s
+Facebook proﬁle. Such a set of of tagged images of
+one’s self, family, friends, and colleagues represents
+n extremely valuable potential training set.
+In this work, we explore how to leverage the afore-"
+bb489e4de6f9b835d70ab46217f11e32887931a2,Everything You Wanted to Know about Deep Learning for Computer Vision but Were Afraid to Ask,"Everything you wanted to know about Deep Learning for Computer Vision but were
+fraid to ask
+Moacir A. Ponti, Leonardo S. F. Ribeiro, Tiago S. Nazare
+ICMC – University of S˜ao Paulo
+S˜ao Carlos/SP, 13566-590, Brazil
+Tu Bui, John Collomosse
+CVSSP – University of Surrey
+Guildford, GU2 7XH, UK
+Email: [ponti, leonardo.sampaio.ribeiro,
+Email: [t.bui,
+tools,"
+bba281fe9c309afe4e5cc7d61d7cff1413b29558,An unpleasant emotional state reduces working memory capacity: electrophysiological evidence,"Social Cognitive and Affective Neuroscience, 2017, 984–992
+doi: 10.1093/scan/nsx030
+Advance Access Publication Date: 11 April 2017
+Original article
+An unpleasant emotional state reduces working
+memory capacity: electrophysiological evidence
+Jessica S. B. Figueira,1 Leticia Oliveira,1 Mirtes G. Pereira,1 Luiza B. Pacheco,1
+Isabela Lobo,1,2 Gabriel C. Motta-Ribeiro,3 and Isabel A. David1
+Laboratorio de Neuroﬁsiologia do Comportamento, Departamento de Fisiologia e Farmacologia, Instituto
+Biome´dico, Universidade Federal Fluminense, Niteroi, Brazil, 2MograbiLab, Departamento de Psicologia,
+Pontifıcia Universidade Catolica do Rio de Janeiro, Rio de Janeiro, Brazil, and 3Laboratorio de Engenharia
+Pulmonar, Programa de Engenharia Biome´dica, COPPE, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
+Correspondence should be addressed to Isabel A. David, Departamento de Fisiologia e Farmacologia, Instituto Biome´dico, Universidade Federal
+Fluminense, Rua Hernani Pires de Mello, 101, Niteroi, RJ 24210-130, Brazil. E-mail:"
+bb06ef67a49849c169781657be0bb717587990e0,Impact of temporal subsampling on accuracy and performance in practical video classification,"Impact of Temporal Subsampling on Accuracy and
+Performance in Practical Video Classiﬁcation
+F. Scheidegger∗†, L. Cavigelli∗, M. Schaffner∗, A. C. I. Malossi†, C. Bekas†, L. Benini∗‡
+ETH Zürich, 8092 Zürich, Switzerland
+IBM Research - Zürich, 8803 Rüschlikon, Switzerland
+Università di Bologna, Italy"
+bb22104d2128e323051fb58a6fe1b3d24a9e9a46,Analyzing Facial Expression by Fusing Manifolds,")=OEC .=?E= -NFHAIIE >O .KIEC
+9A;= +D=C1,2 +DK5C +DA1,3 ;E2EC 0KC1,2,3
+1IJEJKJA B 1BH=JE 5?EA?A 5EE?= 6=EM=
+,AFJ B +FKJAH 5?EA?A 1BH=JE -CEAAHEC =JE= 6=EM= 7ELAHIEJO
+IJEJKJA B AJMHEC =JE= 6=EM= 7ELAHIEJO
+{wychang,
+)>IJH=?J .A=JKHA HAFHAIAJ=JE ?=IIE?=JE =HA JM =H EIIKAI E B=?E=
+ANFHAIIE ==OIEI 1 JDA F=IJ IJ AEJDAH DEIJE? H ?= HAFHA
+IAJ=JE BH ==OIEI 1 AIIA?A ?= EBH=JE =EO B?KIAI  JDA IK>JA
+L=HE=JEI B ANFHAIIEI DEIJE? HAFHAIAJ=JE IJHAIIAI  C>=
+JEAI 6 J=A JDA B >JD = HAFHAIAJ=JE EI E JDEI
+F=FAH A=HEC EI J ?D=H=?JAHEA C>= ?= EBH=
+JE 7EA IA KIEC A=H
+EC =FFH=?DAI B JDA HAFHAIAJ=JE =HA >O
+= A=HEC JA?DEGKA 6 EJACH=JA JDAIA
+ABBA?JELAO = BKIE ?=IIEAH EI MDE?D ?= DAF J AFO IKEJ=>A
+?>E=JE MAECDJI B B=?E= ?FAJI J = ANFHAIIE +FHADA
+IELA ?F=HEII  B=?E= ANFHAIIE HA?CEJE =HA J JDA
+ABBA?JELAAII B KH =CHEJD
+A=EEC DK= AJEI F=OI = EFHJ=J HA E DK= ?KE?=JE 6"
+bb7f2c5d84797742f1d819ea34d1f4b4f8d7c197,From Images to 3D Shape Attributes.,"TO APPEAR IN TPAMI
+From Images to 3D Shape Attributes
+David F. Fouhey, Abhinav Gupta, Andrew Zisserman"
+bbd1eb87c0686fddb838421050007e934b2d74ab,Look at Boundary: A Boundary-Aware Face Alignment Algorithm,"(68	points)	COFW	(29	points)	AFLW	(19	points)	Figure1:Theﬁrstcolumnshowsthefaceimagesfromdifferentdatasetswithdifferentnumberoflandmarks.Thesecondcolumnillustratestheuniversallydeﬁnedfacialboundariesestimatedbyourmethods.Withthehelpofboundaryinformation,ourapproachachieveshighaccuracylocalisationresultsacrossmultipledatasetsandannotationprotocols,asshowninthethirdcolumn.Differenttofacedetection[45]andrecognition[75],facealignmentidentiﬁesgeometrystructureofhumanfacewhichcanbeviewedasmodelinghighlystructuredout-put.Eachfaciallandmarkisstronglyassociatedwithawell-deﬁnedfacialboundary,e.g.,eyelidandnosebridge.However,comparedtoboundaries,faciallandmarksarenotsowell-deﬁned.Faciallandmarksotherthancornerscanhardlyremainthesamesemanticallocationswithlargeposevariationandocclusion.Besides,differentannotationschemesofexistingdatasetsleadtoadifferentnumberoflandmarks[28,5,66,30](19/29/68/194points)andanno-tationschemeoffuturefacealignmentdatasetscanhardlybedetermined.Webelievethereasoningofauniquefacial"
+d73d2c9a6cef79052f9236e825058d5d9cdc1321,Cutting the visual world into bigger slices for improved video concept detection. (Amélioration de la détection des concepts dans les vidéos en coupant de plus grandes tranches du monde visuel),"014-ENST-0040
+EDITE - ED 130
+Doctorat ParisTech
+T H È S E
+pour obtenir le grade de docteur délivré par
+TELECOM ParisTech
+Spécialité « Signal et Images »
+présentée et soutenue publiquement par
+Usman Farrokh NIAZ
+le 08 juillet 2014
+Cutting the Visual World into Bigger Slices for Improved Video
+Concept Detection
+Amélioration de la détection des concepts dans les vidéos par de plus grandes tranches du Monde
+Visuel
+Directeur de thèse : Bernard Mérialdo
+M. Philippe-Henri Gosselin, Professeur, INRIA
+M. Georges Quénot, Directeur de recherche CNRS, LIG
+M. Georges Linares, Professeur, LIA
+M. François Brémond, Professeur, INRIA
+M. Bernard Mérialdo, Professeur, EURECOM"
+d7fe2a52d0ad915b78330340a8111e0b5a66513a,Photo-to-Caricature Translation on Faces in the Wild,"Unpaired Photo-to-Caricature Translation on Faces in
+the Wild
+Ziqiang Zhenga, Chao Wanga, Zhibin Yua, Nan Wanga, Haiyong Zhenga,∗,
+Bing Zhenga
+No. 238 Songling Road, Department of Electronic Engineering, Ocean University of
+China, Qingdao, China"
+d708ce7103a992634b1b4e87612815f03ba3ab24,FCVID: Fudan-Columbia Video Dataset,"FCVID: Fudan-Columbia Video Dataset
+Yu-Gang Jiang, Zuxuan Wu, Jun Wang, Xiangyang Xue, Shih-Fu Chang
+Available at: http://bigvid.fudan.edu.cn/FCVID/
+OVERVIEW
+Recognizing visual contents in unconstrained videos
+has become a very important problem for many ap-
+plications, such as Web video search and recommen-
+dation, smart content-aware advertising, robotics, etc.
+Existing datasets for video content recognition are
+either small or do not have reliable manual labels.
+In this work, we construct and release a new Inter-
+net video dataset called Fudan-Columbia Video Dataset
+(FCVID), containing 91,223 Web videos (total duration
+,232 hours) annotated manually according to 239
+ategories. We believe that the release of FCVID can
+stimulate innovative research on this challenging and
+important problem.
+COLLECTION AND ANNOTATION
+The categories in FCVID cover a wide range of topics
+like social events (e.g., “tailgate party”), procedural"
+d7b6bbb94ac20f5e75893f140ef7e207db7cd483,griffith . edu . au Face Recognition across Pose : A Review,"Griffith Research Online
+https://research-repository.griffith.edu.au
+Face Recognition across Pose: A
+Review
+Author
+Zhang, Paul, Gao, Yongsheng
+Published
+Journal Title
+Pattern Recognition
+https://doi.org/10.1016/j.patcog.2009.04.017
+Copyright Statement
+Copyright 2009 Elsevier. This is the author-manuscript version of this paper. Reproduced in accordance
+with the copyright policy of the publisher. Please refer to the journal's website for access to the
+definitive, published version.
+Downloaded from
+http://hdl.handle.net/10072/30193"
+d7d166aee5369b79ea2d71a6edd73b7599597aaa,Fast Subspace Clustering Based on the Kronecker Product,"Fast Subspace Clustering Based on the
+Kronecker Product
+Lei Zhou1, Xiao Bai1, Xianglong Liu1, Jun Zhou2, and Hancock Edwin3
+Beihang University 2Grif‌f‌ith University 3University of York, UK"
+d79f9ada35e4410cd255db39d7cc557017f8111a,Evaluation of accurate eye corner detection methods for gaze estimation,"Journal of Eye Movement Research
+7(3):3, 1-8
+Evaluation of accurate eye corner detection methods for gaze
+estimation
+Jose Javier Bengoechea
+Public University of Navarra, Spain
+Juan J. Cerrolaza
+Childrens National Medical Center, USA
+Arantxa Villanueva
+Public University of Navarra, Spain
+Rafael Cabeza
+Public University of Navarra, Spain
+Accurate detection of iris center and eye corners appears to be a promising
+pproach for low cost gaze estimation.
+In this paper we propose novel eye
+inner corner detection methods. Appearance and feature based segmentation
+pproaches are suggested. All these methods are exhaustively tested on a realistic
+dataset containing images of subjects gazing at different points on a screen.
+We have demonstrated that a method based on a neural network presents the
+est performance even in light changing scenarios."
+d03265ea9200a993af857b473c6bf12a095ca178,Multiple deep convolutional neural networks averaging for face alignment,"Multiple deep convolutional neural
+networks averaging for face
+lignment
+Shaohua Zhang
+Hua Yang
+Zhouping Yin
+Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 05/28/2015 Terms of Use: http://spiedl.org/terms"
+d00c335fbb542bc628642c1db36791eae24e02b7,Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor,"Article
+Deep Learning-Based Gaze Detection System for
+Automobile Drivers Using a NIR Camera Sensor
+Rizwan Ali Naqvi, Muhammad Arsalan, Ganbayar Batchuluun, Hyo Sik Yoon and
+Kang Ryoung Park *
+Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro, 1-gil, Jung-gu,
+Seoul 100-715, Korea; (R.A.N.); (M.A.);
+(G.B.); (H.S.Y.)
+* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735
+Received: 5 January 2018; Accepted: 1 February 2018; Published: 3 February 2018"
+d074b33afd95074d90360095b6ecd8bc4e5bb6a2,Human-Robot Collaboration: a Survey,"December 11, 2007
+2:8 WSPC/INSTRUCTION FILE
+auer-2007-ijhr
+International Journal of Humanoid Robotics
+(cid:13) World Scientiﬁc Publishing Company
+Human-Robot Collaboration: A Survey
+Andrea Bauer, Dirk Wollherr, Martin Buss
+Institute of Automatic Control Engineering (LSR)
+Technische Universit¨at M¨unchen
+80290 Munich
+Germany
+Received 01.05.2007
+Revised 29.09.2007
+Accepted Day Month Year
+As robots are gradually leaving highly structured factory environments and moving into
+human populated environments, they need to possess more complex cognitive abilities.
+They do not only have to operate ef‌f‌iciently and safely in natural, populated environ-
+ments, but also be able to achieve higher levels of cooperation and communication with
+humans. Human-robot collaboration (HRC) is a research ﬁeld with a wide range of ap-
+plications, future scenarios, and potentially a high economic impact. HRC is an interdis-"
+d0144d76b8b926d22411d388e7a26506519372eb,Improving Regression Performance with Distributional Losses,"Improving Regression Performance with Distributional Losses
+Ehsan Imani 1 Martha White 1"
+d0a21f94de312a0ff31657fd103d6b29db823caa,Facial Expression Analysis,"Facial Expression Analysis
+Fernando De la Torre and Jeffrey F. Cohn"
+d03e4e938bcbc25aa0feb83d8a0830f9cd3eb3ea,Face Recognition with Patterns of Oriented Edge Magnitudes,"Face Recognition with Patterns of Oriented
+Edge Magnitudes
+Ngoc-Son Vu1,2 and Alice Caplier2
+Vesalis Sarl, Clermont Ferrand, France
+Gipsa-lab, Grenoble INP, France"
+d02c54192dbd0798b43231efe1159d6b4375ad36,3 D Reconstruction and Face Recognition Using Kernel-Based ICA and Neural Networks,"D Reconstruction and Face Recognition Using Kernel-Based
+ICA and Neural Networks
+Cheng-Jian Lin                  Ya-Tzu Huang
+Chi-Yung Lee
+Dept. of Electrical                Dept. of CSIE                    Dept. of CSIE
+Engineering              Chaoyang University              Nankai Institute of
+National University            of Technology                        Technology
+of Kaohsiung"
+d00787e215bd74d32d80a6c115c4789214da5edb,Faster and Lighter Online Sparse Dictionary Learning,"Faster and Lighter Online
+Sparse Dictionary Learning
+Project report
+By: Shay Ben-Assayag, Omer Dahary
+Supervisor: Jeremias Sulam"
+be8c517406528edc47c4ec0222e2a603950c2762,Measuring Facial Action,"Harrigan / The new handbook of methods in nonverbal behaviour research 02-harrigan-chap02 Page Proof page 7
+7.6.2005
+5:45pm
+B A S I C R E S E A RC H
+M E T H O D S A N D
+P RO C E D U R E S"
+beb3fd2da7f8f3b0c3ebceaa2150a0e65736d1a2,Adaptive Histogram Equalization and Logarithm Transform with Rescaled Low Frequency DCT Coefficients for Illumination Normalization,"RESEARCH PAPER
+International Journal of Recent Trends in Engineering Vol 1, No. 1, May 2009,
+Adaptive Histogram Equalization and Logarithm
+Transform with Rescaled Low Frequency DCT
+Coefficients for Illumination Normalization
+Virendra P. Vishwakarma, Sujata Pandey and M. N. Gupta
+Department of Computer Science and Engineering
+Amity School of Engineering Technology, 580, Bijwasan, New Delhi-110061, India
+(Affiliated to Guru Gobind Singh Indraprastha University, Delhi, India)
+Email:
+illumination  normalization.  The
+lighting  conditions.  Most  of  the"
+be48b5dcd10ab834cd68d5b2a24187180e2b408f,Constrained Low-Rank Learning Using Least Squares-Based Regularization,"FOR PERSONAL USE ONLY
+Constrained Low-rank Learning Using Least
+Squares Based Regularization
+Ping Li, Member, IEEE, Jun Yu, Member, IEEE, Meng Wang, Member, IEEE,
+Luming Zhang, Member, IEEE, Deng Cai, Member, IEEE, and Xuelong Li, Fellow, IEEE,"
+be437b53a376085b01ebd0f4c7c6c9e40a4b1a75,Face Recognition and Retrieval Using Cross Age Reference Coding,"ISSN (Online) 2321 – 2004
+ISSN (Print) 2321 – 5526
+INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN ELECTRICAL, ELECTRONICS, INSTRUMENTATION AND CONTROL ENGINEERING
+Vol. 4, Issue 5, May 2016
+IJIREEICE
+Face Recognition and Retrieval Using Cross
+Age Reference Coding
+Sricharan H S1, Srinidhi K S1, Rajath D N1, Tejas J N1, Chandrakala B M2
+BE, DSCE, Bangalore1
+Assistant Professor, DSCE, Bangalore2"
+be07f2950771d318a78d2b64de340394f7d6b717,3D HMM-based Facial Expression Recognition using Histogram of Oriented Optical Flow,"See	discussions,	stats,	and	author	profiles	for	this	publication	at:	https://www.researchgate.net/publication/290192867
+D	HMM-based	Facial	Expression	Recognition
+using	Histogram	of	Oriented	Optical	Flow
+ARTICLE		in		SYNTHESIS	LECTURES	ON	ARTIFICIAL	INTELLIGENCE	AND	MACHINE	LEARNING	·	DECEMBER	2015
+DOI:	10.14738/tmlai.36.1661
+READS
+AUTHORS,	INCLUDING:
+Sheng	Kung
+Oakland	University
+Djamel	Bouchaffra
+Institute	of	Electrical	and	Electronics	Engineers
+PUBLICATION			0	CITATIONS
+57	PUBLICATIONS			402	CITATIONS
+SEE	PROFILE
+SEE	PROFILE
+All	in-text	references	underlined	in	blue	are	linked	to	publications	on	ResearchGate,
+letting	you	access	and	read	them	immediately.
+Available	from:	Djamel	Bouchaffra
+Retrieved	on:	11	February	2016"
+beb4546ae95f79235c5f3c0e9cc301b5d6fc9374,A Modular Approach to Facial Expression Recognition,"A Modular Approach to Facial Expression Recognition
+Michal Sindlar
+Cognitive Artiﬁcial Intelligence, Utrecht University, Heidelberglaan 6, 3584 CD, Utrecht
+Marco Wiering
+Intelligent Systems Group, Utrecht University, Padualaan 14, 3508 TB, Utrecht"
+bebea83479a8e1988a7da32584e37bfc463d32d4,Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning,"Discovery of Latent 3D Keypoints via
+End-to-end Geometric Reasoning
+Supasorn Suwajanakorn∗ Noah Snavely
+Jonathan Tompson Mohammad Norouzi
+{supasorn, snavely, tompson,
+Google AI"
+beab10d1bdb0c95b2f880a81a747f6dd17caa9c2,DeepDeblur: Fast one-step blurry face images restoration,"DeepDeblur: Fast one-step blurry face images restoration
+Lingxiao Wang, Yali Li, Shengjin Wang
+Tsinghua Unversity"
+b331ca23aed90394c05f06701f90afd550131fe3,Double regularized matrix factorization for image classification and clustering,"Zhou et al. EURASIP Journal on Image and Video Processing  (2018) 2018:49
+https://doi.org/10.1186/s13640-018-0287-5
+EURASIP Journal on Image
+nd Video Processing
+R ES EAR CH
+Double regularized matrix factorization for
+image classification and clustering
+Wei Zhou1*
+, Chengdong Wu2, Jianzhong Wang3,4, Xiaosheng Yu2 and Yugen Yi5
+Open Access"
+b37f57edab685dba5c23de00e4fa032a3a6e8841,Towards social interaction detection in egocentric photo-streams,"Towards Social Interaction Detection in Egocentric Photo-streams
+Maedeh Aghaei, Mariella Dimiccoli, Petia Radeva
+University of Barcelona and Computer Vision Centre, Barcelona, Spain
+Recent advances in wearable camera technology have
+led to novel applications in the ﬁeld of Preventive Medicine.
+For some of them, such as cognitive training of elderly peo-
+ple by digital memories and detection of unhealthy social
+trends associated to neuropsychological disorders, social in-
+teraction are of special interest. Our purpose is to address
+this problem in the domain of egocentric photo-streams cap-
+tured by a low temporal resolution wearable camera (2fpm).
+These cameras are suited for collecting visual information
+for long period of time, as required by the aforementioned
+pplications. The major difﬁculties to be handled in this
+ontext are the sparsity of observations as well as the unpre-
+dictability of camera motion and attention orientation due
+to the fact that the camera is worn as part of clothing (see
+Fig. 1). Inspired by the theory of F-formation which is a
+pattern that people tend to follow when interacting [5], our
+proposed approach consists of three steps: multi-faces as-"
+b3cb91a08be4117d6efe57251061b62417867de9,Label propagation approach for predicting missing biographic labels in face-based biometric records,"T. Swearingen and A. Ross. ""A label propagation approach for predicting missing biographic labels in
+A Label Propagation Approach for
+Predicting Missing Biographic Labels
+in Face-Based Biometric Records
+Thomas Swearingen and Arun Ross"
+b340f275518aa5dd2c3663eed951045a5b8b0ab1,Visual inference of human emotion and behaviour,"Visual Inference of Human Emotion and Behaviour
+Shaogang Gong
+Caifeng Shan
+Tao Xiang
+Dept of Computer Science
+Queen Mary College, London
+Dept of Computer Science
+Queen Mary College, London
+Dept of Computer Science
+Queen Mary College, London
+England, UK
+England, UK
+England, UK"
+b375db63742f8a67c2a7d663f23774aedccc84e5,Brain-Inspired Classroom Occupancy Monitoring on a Low-Power Mobile Platform,"Brain-inspired Classroom Occupancy
+Monitoring on a Low-Power Mobile Platform
+Department of Electrical, Electronic and Information Engineering, University of Bologna, Italy
+Francesco Conti∗, Antonio Pullini† and Luca Benini∗†
+Integrated Systems Laboratory, ETH Zurich, Switzerland"
+b3c60b642a1c64699ed069e3740a0edeabf1922c,Max-Margin Object Detection,"Max-Margin Object Detection
+Davis E. King"
+b3f7c772acc8bc42291e09f7a2b081024a172564,"A novel approach for performance parameter estimation of face recognition based on clustering , shape and corner detection","www.ijmer.com            Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3225-3230                 ISSN: 2249-6645
+International Journal of Modern Engineering Research (IJMER)
+A novel approach for performance parameter estimation of face
+recognition based on clustering, shape and corner detection
+.Smt.Minj Salen Kujur , 2.Prof. Prashant Jain,
+Department of Electronics & Communication Engineering college Jabalpur"
+b32cf547a764a4efa475e9c99a72a5db36eeced6,Mimicry of ingroup and outgroup emotional expressions,"UvA-DARE (Digital Academic Repository)
+Mimicry of ingroup and outgroup emotional expressions
+Sachisthal, M.S.M.; Sauter, D.A.; Fischer, A.H.
+Published in:
+Comprehensive Results in Social Psychology
+0.1080/23743603.2017.1298355
+Link to publication
+Citation for published version (APA):
+Sachisthal, M. S. M., Sauter, D. A., & Fischer, A. H. (2016). Mimicry of ingroup and outgroup emotional
+expressions. Comprehensive Results in Social Psychology, 1(1-3), 86-105. DOI:
+0.1080/23743603.2017.1298355
+General rights
+It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s),
+other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons).
+Disclaimer/Complaints regulations
+If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating
+your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask
+the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam,
+The Netherlands. You will be contacted as soon as possible.
+Download date: 08 Aug 2018"
+b32631f456397462b3530757f3a73a2ccc362342,Discriminant Tensor Dictionary Learning with Neighbor Uncorrelation for Image Set Based Classification,Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
+df90850f1c153bfab691b985bfe536a5544e438b,"Face Tracking Algorithm Robust to Pose , Illumination and Face Expression Changes : a 3 D Parametric Model Approach","FACE TRACKING ALGORITHM ROBUST TO POSE,
+ILLUMINATION AND FACE EXPRESSION CHANGES: A 3D
+PARAMETRIC MODEL APPROACH
+Marco Anisetti, Valerio Bellandi
+University of Milan - Department of Information Technology
+via Bramante 65 - 26013, Crema (CR), Italy
+Luigi Arnone, Fabrizio Beverina
+STMicroelectronics - Advanced System Technology Group
+via Olivetti 5 - 20041, Agrate Brianza, Italy
+Keywords:
+Face tracking, expression changes, FACS, illumination changes."
+df8da144a695269e159fb0120bf5355a558f4b02,Face Recognition using PCA and Eigen Face Approach,"International Journal of Computer Applications (0975 – 8887)
+International Conference on Recent Trends in engineering & Technology - 2013(ICRTET'2013)
+Face Recognition using PCA and Eigen Face
+Approach
+Anagha A. Shinde
+ME EXTC [VLSI & Embedded System]
+Sinhgad Academy of Engineering
+EXTC Department
+Pune, India"
+df577a89830be69c1bfb196e925df3055cafc0ed,"Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions","Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions
+Bichen Wu, Alvin Wan∗, Xiangyu Yue∗, Peter Jin, Sicheng Zhao,
+Noah Golmant, Amir Gholaminejad, Joseph Gonzalez, Kurt Keutzer
+UC Berkeley"
+df51dfe55912d30fc2f792561e9e0c2b43179089,Face Hallucination Using Linear Models of Coupled Sparse Support,"Face Hallucination using Linear Models of Coupled
+Sparse Support
+Reuben A. Farrugia, Member, IEEE, and Christine Guillemot, Fellow, IEEE
+grid and fuse them to suppress the aliasing caused by under-
+sampling [5], [6]. On the other hand, learning based meth-
+ods use coupled dictionaries to learn the mapping relations
+etween low- and high- resolution image pairs to synthesize
+high-resolution images from low-resolution images [4], [7].
+The research community has lately focused on the latter
+ategory of super-resolution methods, since they can provide
+higher quality images and larger magniﬁcation factors."
+df054fa8ee6bb7d2a50909939d90ef417c73604c,Image Quality-aware Deep Networks Ensemble for Efficient Gender Recognition in the Wild,"Image Quality-Aware Deep Networks Ensemble for Efﬁcient
+Gender Recognition in the Wild
+Mohamed Selim1, Suraj Sundararajan1, Alain Pagani2 and Didier Stricker1,2
+Augmented Vision Lab, Technical University Kaiserslautern, Kaiserslautern, Germany
+German Research Center for Artiﬁcial Intelligence (DFKI), Kaiserslautern, Germany
+{mohamed.selim, alain.pagani, s
+Keywords:
+Gender, Face, Deep Neural Networks, Quality, In the Wild"
+df80fed59ffdf751a20af317f265848fe6bfb9c9,Learning Deep Sharable and Structural Detectors for Face Alignment,"Learning Deep Sharable and Structural
+Detectors for Face Alignment
+Hao Liu, Jiwen Lu, Senior Member, IEEE, Jianjiang Feng, Member, IEEE, and Jie Zhou, Senior Member, IEEE"
+dfa80e52b0489bc2585339ad3351626dee1a8395,Human Action Forecasting by Learning Task Grammars,"Human Action Forecasting by Learning Task Grammars
+Tengda Han
+Jue Wang
+Anoop Cherian
+Stephen Gould"
+dfecaedeaf618041a5498cd3f0942c15302e75c3,A recursive framework for expression recognition: from web images to deep models to game dataset,"Noname manuscript No.
+(will be inserted by the editor)
+A Recursive Framework for Expression Recognition: From
+Web Images to Deep Models to Game Dataset
+Wei Li · Christina Tsangouri · Farnaz Abtahi · Zhigang Zhu
+Received: date / Accepted: date"
+df5fe0c195eea34ddc8d80efedb25f1b9034d07d,Robust modified Active Shape Model for automatic facial landmark annotation of frontal faces,"Robust Modiﬁed Active Shape Model for Automatic Facial Landmark
+Annotation of Frontal Faces
+Keshav Seshadri and Marios Savvides"
+df2494da8efa44d70c27abf23f73387318cf1ca8,Supervised Filter Learning for Representation Based Face Recognition,"RESEARCH ARTICLE
+Supervised Filter Learning for Representation
+Based Face Recognition
+Chao Bi1, Lei Zhang2, Miao Qi1, Caixia Zheng1, Yugen Yi3, Jianzhong Wang1*,
+Baoxue Zhang4*
+College of Computer Science and Information Technology, Northeast Normal University, Changchun,
+China, 2 Changchun Institute of Optics, Fine Mechanics and Physics, CAS, Changchun, China, 3 School of
+Software, Jiangxi Normal University, Nanchang, China, 4 School of Statistics, Capital University of
+Economics and Business, Beijing, China
+11111
+* (JW); (BZ)"
+df674dc0fc813c2a6d539e892bfc74f9a761fbc8,An Image Mining System for Gender Classification & Age Prediction Based on Facial Features,"IOSR Journal of Computer Engineering (IOSR-JCE)
+e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 10, Issue 6 (May. - Jun. 2013), PP 21-29
+www.iosrjournals.org
+An Image Mining System for Gender Classification & Age
+Prediction Based on Facial Features
+1.Ms.Dhanashri Shirkey  , 2Prof.Dr.S.R.Gupta,
+M.E(Scholar),Department Computer Science & Engineering, PRMIT & R, Badnera
+Asstt.Prof. Department Computer Science & Engineering, PRMIT & R, Badnera"
+dad7b8be074d7ea6c3f970bd18884d496cbb0f91,Super-Sparse Regression for Fast Age Estimation from Faces at Test Time,"Super-Sparse Regression for Fast Age
+Estimation From Faces at Test Time
+Ambra Demontis, Battista Biggio, Giorgio Fumera, and Fabio Roli
+Dept. of Electrical and Electronic Engineering, University of Cagliari
+Piazza d’Armi, 09123 Cagliari, Italy
+WWW home page: http://prag.diee.unica.it"
+da4170c862d8ae39861aa193667bfdbdf0ecb363,Multi-Task CNN Model for Attribute Prediction,"Multi-task CNN Model for Attribute Prediction
+Abrar H. Abdulnabi, Student Member, IEEE, Gang Wang, Member, IEEE, , Jiwen Lu, Member, IEEE
+nd Kui Jia, Member, IEEE"
+dac2103843adc40191e48ee7f35b6d86a02ef019,Unsupervised Celebrity Face Naming in Web Videos,"Unsupervised Celebrity Face Naming in Web Videos
+Lei Pang and Chong-Wah Ngo"
+dae420b776957e6b8cf5fbbacd7bc0ec226b3e2e,Recognizing Emotions in Spontaneous Facial Expressions,"RECOGNIZING EMOTIONS IN SPONTANEOUS FACIAL EXPRESSIONS
+Michael Grimm, Dhrubabrata Ghosh Dastidar, and Kristian Kroschel
+Institut f¨ur Nachrichtentechnik
+Universit¨at Karlsruhe (TH), Germany"
+daefac0610fdeff415c2a3f49b47968d84692e87,Multimodal Frame Identification with Multilingual Evaluation,"New Orleans, Louisiana, June 1 - 6, 2018. c(cid:13)2018 Association for Computational Linguistics
+Proceedings of NAACL-HLT 2018, pages 1481–1491"
+b49affdff167f5d170da18de3efa6fd6a50262a2,Linking Names and Faces : Seeing the Problem in Different Ways,"Author manuscript, published in ""Workshop on Faces in 'Real-Life' Images: Detection, Alignment, and Recognition, Marseille : France
+(2008)"""
+b41374f4f31906cf1a73c7adda6c50a78b4eb498,Iterative Gaussianization: From ICA to Random Rotations,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
+Iterative Gaussianization: From ICA to
+Random Rotations
+Valero Laparra, Gustavo Camps-Valls, Senior Member, IEEE, and Jesús Malo"
+b4ee64022cc3ccd14c7f9d4935c59b16456067d3,Unsupervised Cross-Domain Image Generation,"Unsupervised Cross-Domain Image Generation
+Xinru Hua, Davis Rempe, and Haotian Zhang"
+b40290a694075868e0daef77303f2c4ca1c43269,Combining Local and Global Information for Hair Shape Modeling,"第 40 卷 第 4 期
+014 年 4 月
+自 动 化 学 报
+ACTA AUTOMATICA SINICA
+Vol. 40, No. 4
+April, 2014
+融合局部与全局信息的头发形状模型
+王 楠 1 艾海舟 1
+摘 要 头发在人体表观中具有重要作用, 然而, 因为缺少有效的形状模型, 头发分割仍然是一个非常具有挑战性的问题. 本
+文提出了一种基于部件的模型, 它对头发形状以及环境变化更加鲁棒. 该模型将局部与全局信息相结合以描述头发的形状. 局
+部模型通过一系列算法构建, 包括全局形状词表生成, 词表分类器学习以及参数优化; 而全局模型刻画不同的发型, 采用支持
+向量机 (Support vector machine, SVM) 来学习, 它为所有潜在的发型配置部件并确定势函数. 在消费者图片上的实验证明
+了本文算法在头发形状多变和复杂环境等条件下的准确性与有效性.
+关键词 头发形状建模, 部件模型, 部件配置算法, 支持向量机
+引用格式 王楠, 艾海舟. 融合局部与全局信息的头发形状模型. 自动化学报, 2014, 40(4): 615−623
+DOI 10.3724/SP.J.1004.2014.00615
+Combining Local and Global Information for Hair Shape Modeling
+WANG Nan1
+AI Hai-Zhou1"
+b4b0bf0cbe1a2c114adde9fac64900b2f8f6fee4,Autonomous Learning Framework Based on Online Hybrid Classifier for Multi-view Object Detection in Video,"Autonomous Learning Framework Based on Online Hybrid
+Classifier for Multi-view Object Detection in Video
+Dapeng Luoa*Zhipeng Zenga Longsheng Weib Yongwen Liua Chen Luoc Jun Chenb Nong Sangd
+School of Electronic Information and Mechanics, China University of Geosciences, Wuhan, Hubei 430074, China
+School of Automation, China University of Geosciences, Wuhan, Hubei 430074, China
+Huizhou School Affiliated to Beijing Normal University, Huizhou 516002, China
+dNational Key Laboratory of Science and Technology on Multispectral Information Processing, School of Automation, Huazhong
+University of Science and Technology, Wuhan, 430074, China"
+a285b6edd47f9b8966935878ad4539d270b406d1,Facial Expression Recognition Based on Local Binary Patterns and Kernel Discriminant Isomap,"Sensors 2011, 11, 9573-9588; doi:10.3390/s111009573
+OPEN ACCESS
+sensors
+ISSN 1424-8220
+www.mdpi.com/journal/sensors
+Article
+Facial Expression Recognition Based on Local Binary Patterns
+nd Kernel Discriminant Isomap
+Xiaoming Zhao 1,* and Shiqing Zhang 2
+Department of Computer Science, Taizhou University, Taizhou 317000, China
+School of Physics and Electronic Engineering, Taizhou University, Taizhou 318000, China;
+E-Mail:
+*  Author to whom correspondence should be addressed; E-Mail:
+Tel.: +86-576-8513-7178; Fax: ++86-576-8513-7178.
+Received: 31 August 2011; in revised form: 27 September 2011 / Accepted: 9 October 2011 /
+Published: 11 October 2011"
+a2359c0f81a7eb032cff1fe45e3b80007facaa2a,Towards Structured Analysis of Broadcast Badminton Videos,"Towards Structured Analysis of Broadcast Badminton Videos
+Anurag Ghosh
+Suriya Singh
+C.V.Jawahar
+{anurag.ghosh,
+CVIT, KCIS, IIIT Hyderabad"
+a27735e4cbb108db4a52ef9033e3a19f4dc0e5fa,Intention from Motion,"Intention from Motion
+Andrea Zunino, Jacopo Cavazza, Atesh Koul, Andrea Cavallo, Cristina Becchio and Vittorio Murino"
+a2fbaa0b849ecc74f34ebb36d1442d63212b29d2,An Efficient Approach to Face Recognition of Surgically Altered Images,"Volume 5, Issue 6, June 2015                                           ISSN: 2277 128X
+International Journal of Advanced Research in
+Computer Science and Software Engineering
+Research Paper
+Available online at: www.ijarcsse.com
+An Efficient Approach to Face Recognition of Surgically
+Altered Images
+Er. Supriya, Er. Sukhpreet Kaur
+Department of computer science and engineering
+SUS college of Engineering and Technology,
+Tangori, District, Mohali, Punjab, India"
+a50b4d404576695be7cd4194a064f0602806f3c4,Efficiently Estimating Facial Expression and Illumination in Appearance-based Tracking,"In Proceedings of BMVC, Edimburgh, UK, September 2006
+Efﬁciently estimating facial expression and
+illumination in appearance-based tracking
+Jos´e M. Buenaposada†, Enrique Mu˜noz‡, Luis Baumela‡
+ESCET, U. Rey Juan Carlos
+C/ Tulip´an, s/n
+8933 M´ostoles, Spain
+Facultad Inform´atica, UPM
+Campus de Montegancedo s/n
+8660 Boadilla del Monte, Spain
+http://www.dia.fi.upm.es/~pcr"
+a5e5094a1e052fa44f539b0d62b54ef03c78bf6a,Detection without Recognition for Redaction,"Detection without Recognition for Redaction
+Shagan Sah1, Ram Longman1, Ameya Shringi1, Robert Loce2, Majid Rabbani1, and Raymond Ptucha1
+Rochester Institute of Technology - 83 Lomb Memorial Drive, Rochester, NY USA, 14623
+Conduent, Conduent Labs - US, 800 Phillips Rd, MS128, Webster, NY USA, 14580
+Email:"
+a56c1331750bf3ac33ee07004e083310a1e63ddc,Efficient Point-to-Subspace Query in ℓ1 with Application to Robust Object Instance Recognition,"Vol. xx, pp. x
+(cid:13) xxxx Society for Industrial and Applied Mathematics
+Ef‌f‌icient Point-to-Subspace Query in (cid:96)1 with Application to Robust Object
+Instance Recognition
+Ju Sun∗, Yuqian Zhang†, and John Wright‡"
+a54e0f2983e0b5af6eaafd4d3467b655a3de52f4,Face Recognition Using Convolution Filters and Neural Networks,"Face Recognition Using Convolution Filters and
+Neural Networks
+V. Rihani
+Head, Dept. of E&E,PEC
+Sec-12, Chandigarh – 160012
+Amit Bhandari
+Department of CSE & IT, PEC
+Sec-12, Chandigarh – 160012
+C.P. Singh
+Physics Department, CFSL,
+Sec-36, Chandigarh - 160036
+to:  (a)
+potential  method"
+a5625cfe16d72bd00e987857d68eb4d8fc3ce4fb,VFSC: A Very Fast Sparse Clustering to Cluster Faces from Videos,"VFSC: A Very Fast Sparse Clustering to Cluster Faces
+from Videos
+Dinh-Luan Nguyen, Minh-Triet Tran
+University of Science, VNU-HCMC, Ho Chi Minh city, Vietnam"
+a55efc4a6f273c5895b5e4c5009eabf8e5ed0d6a,"Continuous Head Movement Estimator for Driver Assistance: Issues, Algorithms, and On-Road Evaluations","Continuous Head Movement Estimator for
+Driver Assistance: Issues, Algorithms,
+nd On-Road Evaluations
+Ashish Tawari, Student Member, IEEE, Sujitha Martin, Student Member, IEEE, and
+Mohan Manubhai Trivedi, Fellow, IEEE"
+a51d5c2f8db48a42446cc4f1718c75ac9303cb7a,Cross-validating Image Description Datasets and Evaluation Metrics,"Cross-validating Image Description Datasets and Evaluation Metrics
+Josiah Wang and Robert Gaizauskas
+Department of Computer Science
+University of Shefﬁeld, UK
+{j.k.wang,"
+a52d9e9daf2cb26b31bf2902f78774bd31c0dd88,Understanding and Designing Convolutional Networks for Local Recognition Problems,"Understanding and Designing Convolutional Networks
+for Local Recognition Problems
+Jonathan Long
+Electrical Engineering and Computer Sciences
+University of California at Berkeley
+Technical Report No. UCB/EECS-2016-97
+http://www.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-97.html
+May 13, 2016"
+a5a44a32a91474f00a3cda671a802e87c899fbb4,Moments in Time Dataset: one million videos for event understanding,"Moments in Time Dataset: one million
+videos for event understanding
+Mathew Monfort, Bolei Zhou, Sarah Adel Bargal,
+Alex Andonian, Tom Yan, Kandan Ramakrishnan, Lisa Brown,
+Quanfu Fan, Dan Gutfruend, Carl Vondrick, Aude Oliva"
+bd0e100a91ff179ee5c1d3383c75c85eddc81723,Okutama-Action: An Aerial View Video Dataset for Concurrent Human Action Detection,"Okutama-Action: An Aerial View Video Dataset for Concurrent Human Action
+Detection∗
+Mohammadamin Barekatain1, Miquel Mart´ı2,3, Hsueh-Fu Shih4, Samuel Murray2, Kotaro Nakayama5,
+Yutaka Matsuo5, Helmut Prendinger6
+Technical University of Munich, Munich, 2KTH Royal Institute of Technology, Stockholm,
+Polytechnic University of Catalonia, Barcelona, 4National Taiwan University, Taipei, 5University of
+Tokyo, Tokyo, 6National Institute of Informatics, Tokyo"
+bd07d1f68486052b7e4429dccecdb8deab1924db,Face representation under different illumination conditions,
+bd13f50b8997d0733169ceba39b6eb1bda3eb1aa,Occlusion Coherence: Detecting and Localizing Occluded Faces,"Occlusion Coherence: Detecting and Localizing Occluded Faces
+Golnaz Ghiasi, Charless C. Fowlkes
+University of California at Irvine, Irvine, CA 92697"
+bd78a853df61d03b7133aea58e45cd27d464c3cf,A Sparse Representation Approach to Facial Expression Recognition Based on LBP plus LFDA,"A Sparse Representation Approach to Facial
+Expression Recognition Based on LBP plus LFDA
+Ritesh Bora, V.A.Chakkarvar
+Computer science and Engineering Department,
+Government College of Engineering, Aurangabad [Autonomous]
+Station Road, Aurangabad, Maharashtra, India."
+bd2d7c7f0145028e85c102fe52655c2b6c26aeb5,Attribute-based People Search: Lessons Learnt from a Practical Surveillance System,"Attribute-based People Search: Lessons Learnt from a
+Practical Surveillance System
+Rogerio Feris
+IBM Watson
+http://rogerioferis.com
+Russel Bobbitt
+IBM Watson
+Lisa Brown
+IBM Watson
+Sharath Pankanti
+IBM Watson"
+bdbba95e5abc543981fb557f21e3e6551a563b45,Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks,"International Journal of Computational Intelligence and Applications
+Vol. 17, No. 2 (2018) 1850008 (15 pages)
+#.c The Author(s)
+DOI: 10.1142/S1469026818500086
+Speeding up the Hyperparameter Optimization of Deep
+Convolutional Neural Networks
+Tobias Hinz*, Nicolas Navarro-Guerrero†, Sven Magg‡
+nd Stefan Wermter§
+Knowledge Technology, Department of Informatics
+Universit€at Hamburg
+Vogt-K€olln-Str. 30, Hamburg 22527, Germany
+Received 15 August 2017
+Accepted 23 March 2018
+Published 18 June 2018
+Most learning algorithms require the practitioner to manually set the values of many hyper-
+parameters before the learning process can begin. However, with modern algorithms, the
+evaluation of a given hyperparameter setting can take a considerable amount of time and the
+search space is often very high-dimensional. We suggest using a lower-dimensional represen-
+tation of the original data to quickly identify promising areas in the hyperparameter space. This
+information can then be used to initialize the optimization algorithm for the original, higher-"
+d1dfdc107fa5f2c4820570e369cda10ab1661b87,Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation,"Super SloMo: High Quality Estimation of Multiple Intermediate Frames
+for Video Interpolation
+Huaizu Jiang1
+Deqing Sun2
+Varun Jampani2
+Ming-Hsuan Yang3,2
+Erik Learned-Miller1
+Jan Kautz2
+UMass Amherst
+NVIDIA 3UC Merced"
+d1dae2993bdbb2667d1439ff538ac928c0a593dc,Gamma Correction Technique Based Feature Extraction for Face Recognition System,"International Journal of Computational Intelligence and Informatics, Vol. 3: No. 1, April - June 2013
+Gamma Correction Technique Based Feature Extraction
+for Face Recognition System
+B Vinothkumar
+P Kumar
+Electronics and Communication Engineering
+K S Rangasamy College of Technology
+Electronics and Communication Engineering
+K S Rangasamy College of Technology
+Tamilnadu, India
+Tamilnadu, India"
+d1f58798db460996501f224fff6cceada08f59f9,Transferrable Representations for Visual Recognition,"Transferrable Representations for Visual Recognition
+Jeffrey Donahue
+Electrical Engineering and Computer Sciences
+University of California at Berkeley
+Technical Report No. UCB/EECS-2017-106
+http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-106.html
+May 14, 2017"
+d1a43737ca8be02d65684cf64ab2331f66947207,IJB–S: IARPA Janus Surveillance Video Benchmark,"IJB–S: IARPA Janus Surveillance Video Benchmark (cid:3)
+Nathan D. Kalka y
+Stephen Elliott z
+Brianna Maze y
+Kaleb Hebert y
+James A. Duncan y
+Julia Bryan z
+Kevin O’Connor z
+Anil K. Jain x"
+d1082eff91e8009bf2ce933ac87649c686205195,Pruning of Error Correcting Output Codes by optimization of accuracy–diversity trade off,"(will be inserted by the editor)
+Pruning of Error Correcting Output Codes by
+Optimization of Accuracy-Diversity Trade off
+S¨ureyya ¨Oz¨o˘g¨ur Aky¨uz · Terry
+Windeatt · Raymond Smith
+Received: date / Accepted: date"
+d1d6f1d64a04af9c2e1bdd74e72bd3ffac329576,Neural Face Editing with Intrinsic Image Disentangling,"Neural Face Editing with Intrinsic Image Disentangling
+Zhixin Shu1 Ersin Yumer2 Sunil Hadap2 Kalyan Sunkavalli2 Eli Shechtman 2 Dimitris Samaras1,3
+Stony Brook University 2Adobe Research 3 CentraleSup´elec, Universit´e Paris-Saclay"
+d69df51cff3d6b9b0625acdcbea27cd2bbf4b9c0,Robust Remote Heart Rate Determination for E-Rehabilitation - A Method that Overcomes Motion and Intensity Artefacts,
+d61578468d267c2d50672077918c1cda9b91429b,Face Image Retrieval Using Pose Specific Set Sparse Feature Representation,"Abdul Afeef N et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.9, September- 2014, pg. 314-323
+Available Online at www.ijcsmc.com
+International Journal of Computer Science and Mobile Computing
+A Monthly Journal of Computer Science and Information Technology
+ISSN 2320–088X
+IJCSMC, Vol. 3, Issue. 9, September 2014, pg.314 – 323
+RESEARCH ARTICLE
+Face Image Retrieval Using Pose Specific
+Set Sparse Feature Representation
+Department of Computer Science, Viswajyothi College of Engineering and Technology Kerala, India
+Assistant Professor of Computer Science, Viswajyothi College of Engineering and Technology Kerala, India
+Abdul Afeef N1, Sebastian George2"
+d687fa99586a9ad229284229f20a157ba2d41aea,Face Recognition Based on Wavelet Packet Coefficients and Radial Basis Function Neural Networks,"Journal of Intelligent Learning Systems and Applications, 2013, 5, 115-122
+http://dx.doi.org/10.4236/jilsa.2013.52013 Published Online May 2013 (http://www.scirp.org/journal/jilsa)
+Face Recognition Based on Wavelet Packet Coefficients
+nd Radial Basis Function Neural Networks
+Thangairulappan Kathirvalavakumar1*, Jeyasingh Jebakumari Beulah Vasanthi2
+Department of Computer Science, Virudhunagar Hindu Nadars’ Senthikumara Nadar College, Virudhunagar, India; 2Department of
+Computer Applications, Ayya Nadar Janaki Ammal College, Sivakasi, India.
+Email:
+Received December 12th, 2012; revised April 19th, 2013; accepted April 26th, 2013
+Copyright © 2013 Thangairulappan Kathirvalavakumar, Jeyasingh Jebakumari Beulah Vasanthi. This is an open access article dis-
+tributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any me-
+dium, provided the original work is properly cited."
+d6a9ea9b40a7377c91c705f4c7f206a669a9eea2,Visual Representations for Fine-grained Categorization,"Visual Representations for Fine-grained
+Categorization
+Ning Zhang
+Electrical Engineering and Computer Sciences
+University of California at Berkeley
+Technical Report No. UCB/EECS-2015-244
+http://www.eecs.berkeley.edu/Pubs/TechRpts/2015/EECS-2015-244.html
+December 17, 2015"
+d671a210990f67eba9b2d3dda8c2cb91575b4a7a,Social Environment Description from Data Collected with a Wearable Device,"Journal of Machine Learning Research ()
+Submitted ; Published
+Social Environment Description from Data Collected with a
+Wearable Device
+Pierluigi Casale
+Computer Vision Center
+Autonomous University of Barcelona
+Barcelona, Spain
+Editor: Radeva Petia, Pujol Oriol"
+d6102a7ddb19a185019fd2112d2f29d9258f6dec,Fashion Style Generator,"Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
+GeneratorPatch……Global+…lstyle(2)lstyle(1)lcontent(1)lcontent(2)φθϕsϕcDiscriminatorDGXX(1)X(2)(a) Framework of the training stage(b) Examples of fashion style generationFigure1:Fashionstylegeneratorframeworkoverview.TheinputXconsistsofasetofclothingpatchesX(1)andfullclothingimagesX(2).Thesystemconsistsoftwocomponents:animagetransfor-mationnetworkGservedasfashionstylegenerator,andadiscrimi-natornetworkDcalculatesbothglobalandpatchbasedcontentandstylelosses.Gisaconvolutionalencoderdecodernetworkparam-eterizedbyweights(cid:18).Sixgeneratedshirtswithdifferentstylesbyourmethodareshownasexamples.(Wehighlyrecommendtozoominalltheﬁgureswithcolorversionformoredetails.)recentneuralstyletransferworks[Gatysetal.,2015].Tak-ingVanGogh’s“StarryNight”astheexamplestyleimage,styleisbetweenthelow-levelcolor/texture(e.g.,blueandyellowcolor,roughorsmoothertexture)andthehigh-levelobjects(e.g.,houseandmountain).“Style”isarelativelyab-stractconcept.Fashionstylegenerationhasatleasttwoprac-ticalusages.Designerscouldquicklyseehowtheclothinglookslikeinagivenstyletofacilitatethedesignprocessing.Shopperscouldsynthesizetheclothingimagewiththeidealstyleandapplyclothingretrievaltools[Jiangetal.,2016b]tosearchthesimilaritems.Fashionstylegenerationisrelatedtoexistingneuralstyletransferworks[Gatysetal.,2015;LiandWand,2016a;EfrosandFreeman,2001],buthasitsownchallenges.Infashionstylegeneration,thesyntheticclothingimageshould"
+d6bfa9026a563ca109d088bdb0252ccf33b76bc6,Unsupervised Temporal Segmentation of Facial Behaviour,"Unsupervised Temporal Segmentation of Facial Behaviour
+Abhishek Kar
+Advisors: Dr. Amitabha Mukerjee & Dr. Prithwijit Guha
+Department of Computer Science and Engineering, IIT Kanpur"
+d6c7092111a8619ed7a6b01b00c5f75949f137bf,A Novel Feature Extraction Technique for Facial Expression Recognition,"A Novel Feature Extraction Technique for Facial Expression
+Recognition
+*Mohammad Shahidul Islam1,  Surapong Auwatanamongkol2
+1 Department of Computer Science, School of Applied Statistics,
+National Institute of Development Administration,
+Bangkok, 10240, Thailand
+Department of Computer Science, School of Applied Statistics,
+National Institute of Development Administration,
+Bangkok, 10240, Thailand"
+bcee40c25e8819955263b89a433c735f82755a03,Biologically Inspired Vision for Human-Robot Interaction,"Biologically inspired vision for human-robot
+interaction
+M. Saleiro, M. Farrajota, K. Terzi´c, S. Krishna, J.M.F. Rodrigues, and J.M.H.
+du Buf
+Vision Laboratory, LARSyS, University of the Algarve, 8005-139 Faro, Portugal,
+{masaleiro, mafarrajota, kterzic, jrodrig,"
+bc6de183cd8b2baeebafeefcf40be88468b04b74,Age Group Recognition using Human Facial Images,"Age Group Recognition using Human Facial Images
+International Journal of Computer Applications (0975 – 8887)
+Volume 126 – No.13, September 2015
+Shailesh S. Kulkarni
+Dept. of Electronics and Telecommunication
+Government College of Engineering,
+Aurangabad, Maharashtra, India"
+bcf19b964e7d1134d00332cf1acf1ee6184aff00,Trajectory-Set Feature for Action Recognition,"IEICE TRANS. INF. & SYST., VOL.E100–D, NO.8 AUGUST 2017
+LETTER
+Trajectory-Set Feature for Action Recognition
+Kenji MATSUI†, Nonmember, Toru TAMAKI†a), Member, Bisser RAYTCHEV†, Nonmember,
+nd Kazufumi KANEDA†, Member
+SUMMARY We propose a feature for action recognition called
+Trajectory-Set (TS), on top of the improved Dense Trajectory (iDT).
+The TS feature encodes only trajectories around densely sampled inter-
+est points, without any appearance features. Experimental results on the
+UCF50 action dataset demonstrates that TS is comparable to state-of-the-
+rts, and outperforms iDT; the accuracy of 95.0%, compared to 91.7% by
+key words: action recognition, trajectory, improved Dense Trajectory
+the two-stream CNN [2] that uses a single frame and a opti-
+al flow stack. In their paper stacking trajectories was also
+reported but did not perform well, probably the sparseness
+of trajectories does not ﬁt to CNN architectures. In contrast,
+we take a hand-crafted approach that can be fused later with
+CNN outputs.
+Introduction
+Action recognition has been well studied in the computer"
+bc9003ad368cb79d8a8ac2ad025718da5ea36bc4,Facial expression recognition with a three-dimensional face model,"Technische Universit¨at M¨unchen
+Bildverstehen und Intelligente Autonome Systeme
+Facial Expression Recognition With A
+Three-Dimensional Face Model
+Christoph Mayer
+Vollst¨andiger Abdruck der von der Fakult¨at f¨ur Informatik der Technischen Uni-
+versit¨at M¨unchen zur Erlangung des akademischen Grades eines
+Doktors der Naturwissenschaften
+genehmigten Dissertation.
+Vorsitzender:
+Univ.-Prof. Dr. Johann Schlichter
+Pr¨ufer der Dissertation: 1. Univ.-Prof. Dr. Bernd Radig (i.R.)
+. Univ.-Prof. Gudrun J. Klinker, Ph.D.
+Die Dissertation wurde am 04.07.2011 bei der Technischen Universit¨at M¨unchen
+eingereicht und durch die Fakult¨at f¨ur Informatik am 02.12.2011 angenommen."
+bcc172a1051be261afacdd5313619881cbe0f676,A fast face clustering method for indexing applications on mobile phones,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE
+ICASSP 2017"
+bc811a66855aae130ca78cd0016fd820db1603ec,Towards three-dimensional face recognition in the real Huibin,"Towards three-dimensional face recognition in the real
+Huibin Li
+To cite this version:
+Huibin Li. Towards three-dimensional face recognition in the real. Other. Ecole Centrale de
+Lyon, 2013. English. <NNT : 2013ECDL0037>. <tel-00998798>
+HAL Id: tel-00998798
+https://tel.archives-ouvertes.fr/tel-00998798
+Submitted on 2 Jun 2014
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entiﬁc research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destin´ee au d´epˆot et `a la diffusion de documents
+scientiﬁques de niveau recherche, publi´es ou non,
+´emanant des ´etablissements d’enseignement et de
+recherche fran¸cais ou ´etrangers, des laboratoires
+publics ou priv´es."
+bc98027b331c090448492eb9e0b9721e812fac84,"Face Representation Using Combined Method of Gabor Filters, Wavelet Transformation and DCV and Recognition Using RBF","Journal of Intelligent Learning Systems and Applications, 2012, 4, 266-273
+http://dx.doi.org/10.4236/jilsa.2012.44027 Published Online November 2012 (http://www.SciRP.org/journal/jilsa)
+Face Representation Using Combined Method of Gabor
+Filters, Wavelet Transformation and DCV and Recognition
+Using RBF
+Kathirvalavakumar Thangairulappan1*, Jebakumari Beulah Vasanthi Jeyasingh2
+Department of Computer Science, VHNSN College, Virudhunagar, India; 2Department of Computer Applications, ANJA College,
+Sivakasi, India.
+Email:
+Received April 27th, 2012; revised July 19th, 2012; accepted July 26th, 2012"
+bc9af4c2c22a82d2c84ef7c7fcc69073c19b30ab,MoCoGAN: Decomposing Motion and Content for Video Generation,"MoCoGAN: Decomposing Motion and Content for Video Generation
+Sergey Tulyakov,
+Snap Research
+Ming-Yu Liu, Xiaodong Yang,
+NVIDIA
+Jan Kautz"
+bcac3a870501c5510df80c2a5631f371f2f6f74a,Structured Face Hallucination,"#1387
+CVPR 2013 Submission #1387. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
+#1387
+Structured Face Hallucination
+Anonymous CVPR submission
+Paper ID 1387"
+ae8d5be3caea59a21221f02ef04d49a86cb80191,Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks,"Published as a conference paper at ICLR 2018
+SKIP RNN: LEARNING TO SKIP STATE UPDATES IN
+RECURRENT NEURAL NETWORKS
+V´ıctor Campos∗†, Brendan Jou‡, Xavier Gir´o-i-Nieto§, Jordi Torres†, Shih-Fu ChangΓ
+Barcelona Supercomputing Center, ‡Google Inc,
+§Universitat Polit`ecnica de Catalunya, ΓColumbia University
+{victor.campos,"
+ae2cf545565c157813798910401e1da5dc8a6199,Cascade of Boolean detector combinations,"Mahkonen et al. EURASIP Journal on Image and Video
+Processing  (2018) 2018:61
+https://doi.org/10.1186/s13640-018-0303-9
+EURASIP Journal on Image
+nd Video Processing
+RESEARCH
+Open Access
+Cascade of Boolean detector
+ombinations
+Katariina Mahkonen*
+, Tuomas Virtanen and Joni Kämäräinen"
+aebb9649bc38e878baef082b518fa68f5cda23a5,A Multi - scale TVQI - based Illumination Normalization Model,
+aeeea6eec2f063c006c13be865cec0c350244e5b,"Induced Disgust, Happiness and Surprise: an Addition to the MMI Facial Expression Database","Induced Disgust, Happiness and Surprise: an Addition to the MMI Facial
+Expression Database
+Michel F. Valstar, Maja Pantic
+Imperial College London / Twente University
+Department of Computing / EEMCS
+80 Queen’s Gate / Drienerlolaan 5
+London / Twente"
+ae9257f3be9f815db8d72819332372ac59c1316b,Deciphering the enigmatic face: the importance of facial dynamics in interpreting subtle facial expressions.,"P SY CH O L O GIC AL SC I E NC E
+Research Article
+Deciphering the Enigmatic Face
+The Importance of Facial Dynamics in Interpreting Subtle
+Facial Expressions
+Zara Ambadar,1 Jonathan W. Schooler,2 and Jeffrey F. Cohn1
+University of Pittsburgh and 2University of British Columbia, Vancouver, British Columbia, Canada"
+ae89b7748d25878c4dc17bdaa39dd63e9d442a0d,On evaluating face tracks in movies,"On evaluating face tracks in movies
+Alexey Ozerov, Jean-Ronan Vigouroux, Louis Chevallier, Patrick Pérez
+To cite this version:
+Alexey Ozerov, Jean-Ronan Vigouroux, Louis Chevallier, Patrick Pérez. On evaluating face tracks
+in movies. IEEE International Conference on Image Processing (ICIP 2013), Sep 2013, Melbourne,
+Australia. 2013. <hal-00870059>
+HAL Id: hal-00870059
+https://hal.inria.fr/hal-00870059
+Submitted on 4 Oct 2013
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entific research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destinée au dépôt et à la diffusion de documents
+scientifiques de niveau recherche, publiés ou non,
+émanant des établissements d’enseignement et de
+recherche français ou étrangers, des laboratoires"
+aeff403079022683b233decda556a6aee3225065,DeepFace: Face Generation using Deep Learning,"DeepFace: Face Generation using Deep Learning
+Hardie Cate
+Fahim Dalvi
+Zeshan Hussain"
+ae753fd46a744725424690d22d0d00fb05e53350,Describing Clothing by Semantic Attributes,"Describing Clothing by Semantic Attributes
+Anonymous ECCV submission
+Paper ID 727"
+ae85c822c6aec8b0f67762c625a73a5d08f5060d,Retrieving Similar Styles to Parse Clothing,"This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.
+The final version of record is available at http://dx.doi.org/10.1109/TPAMI.2014.2353624
+IEEE TRANSACTION ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. M, NO. N, MONTH YEAR
+Retrieving Similar Styles to Parse Clothing
+Kota Yamaguchi, Member, IEEE, M. Hadi Kiapour, Student Member, IEEE,
+Luis E. Ortiz, and Tamara L. Berg, Member, IEEE"
+d861c658db2fd03558f44c265c328b53e492383a,Automated face extraction and normalization of 3D Mesh Data,"Automated Face Extraction and Normalization of 3D Mesh Data
+Jia Wu1, Raymond Tse2, Linda G. Shapiro1"
+d82b93f848d5442f82154a6011d26df8a9cd00e7,Neural Network Based Age Classification Using Linear Wavelet Transforms,"NEURAL NETWORK BASED AGE CLASSIFICATION USING
+LINEAR WAVELET TRANSFORMS
+NITHYASHRI JAYARAMAN1 & G.KULANTHAIVEL2
+Department of Computer Science & Engineering,
+Sathyabama University Old Mamallapuram Road, Chennai, India
+Electronics Engineering, National Institute of  Technical Teachers
+Training & Research, Taramani, Chennai, India
+E-mail :"
+d83d2fb5403c823287f5889b44c1971f049a1c93,Introducing the sick face,"Motiv Emot
+DOI 10.1007/s11031-013-9353-6
+O R I G I N A L P A P E R
+Introducing the sick face
+Sherri C. Widen • Joseph T. Pochedly •
+Kerrie Pieloch • James A. Russell
+Ó Springer Science+Business Media New York 2013"
+d8b568392970b68794a55c090c4dd2d7f90909d2,PDA Face Recognition System Using Advanced Correlation Filters,"PDA Face  Recognition  System
+Using  Advanced  Correlation
+Filters
+Chee  Kiat  Ng
+Advisor:  Prof.  Khosla/Reviere"
+d83ae5926b05894fcda0bc89bdc621e4f21272da,Frugal Forests: Learning a Dynamic and Cost Sensitive Feature Extraction Policy for Anytime Activity Classification,"The Thesis committee for Joshua Allen Kelle certiﬁes that this is the approved
+version of the following thesis:
+Frugal Forests: Learning a Dynamic and Cost Sensitive
+Feature Extraction Policy for Anytime Activity Classiﬁcation
+APPROVED BY
+SUPERVISING COMMITTEE:
+Kristen Grauman, Supervisor
+Peter Stone"
+d86fabd4498c8feaed80ec342d254fb877fb92f5,Region-Object Relevance-Guided Visual Relationship Detection,"Y. GOUTSU: REGION-OBJECT RELEVANCE-GUIDED VRD
+Region-Object Relevance-Guided
+Visual Relationship Detection
+Yusuke Goutsu
+National Institute of Informatics
+Tokyo, Japan"
+d89cfed36ce8ffdb2097c2ba2dac3e2b2501100d,Robust Face Recognition via Multimodal Deep Face Representation,"Robust Face Recognition via Multimodal Deep
+Face Representation
+Changxing Ding, Student Member, IEEE, Dacheng Tao, Fellow, IEEE"
+ab8f9a6bd8f582501c6b41c0e7179546e21c5e91,Nonparametric Face Verification Using a Novel Face Representation,"Nonparametric Face Veriﬁcation Using a Novel
+Face Representation
+Hae Jong Seo, Student Member, IEEE, Peyman Milanfar, Fellow, IEEE,"
+ab58a7db32683aea9281c188c756ddf969b4cdbd,Efficient Solvers for Sparse Subspace Clustering,"Efﬁcient Solvers for Sparse Subspace Clustering
+Farhad Pourkamali-Anaraki and Stephen Becker"
+aba770a7c45e82b2f9de6ea2a12738722566a149,Face Recognition in the Scrambled Domain via Salience-Aware Ensembles of Many Kernels,"Face Recognition in the Scrambled Domain via Salience-Aware
+Ensembles of Many Kernels
+Jiang, R., Al-Maadeed, S., Bouridane, A., Crookes, D., & Celebi, M. E. (2016). Face Recognition in the
+Scrambled Domain via Salience-Aware Ensembles of Many Kernels. IEEE Transactions on Information
+Forensics and Security, 11(8), 1807-1817. DOI: 10.1109/TIFS.2016.2555792
+Published in:
+Document Version:
+Peer reviewed version
+Queen's University Belfast - Research Portal:
+Link to publication record in Queen's University Belfast Research Portal
+Publisher rights
+(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/
+republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists,
+or reuse of any copyrighted components of this work in other works.
+General rights
+Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other
+opyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated
+with these rights.
+Take down policy
+The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to"
+ab989225a55a2ddcd3b60a99672e78e4373c0df1,"Sample, computation vs storage tradeoffs for classification using tensor subspace models","Sample, Computation vs Storage Tradeoffs for
+Classiﬁcation Using Tensor Subspace Models
+Mohammadhossein Chaghazardi and Shuchin Aeron, Senior Member, IEEE"
+ab6776f500ed1ab23b7789599f3a6153cdac84f7,A Survey on Various Facial Expression Techniques,"International Journal of Scientific & Engineering Research, Volume 6, Issue 4, April-2015                                                                                                   1212
+ISSN 2229-5518
+A Survey on Various Facial Expression
+Techniques
+Md. Sarfaraz Jalil, Joy Bhattacharya"
+ab1719f573a6c121d7d7da5053fe5f12de0182e7,Combining visual recognition and computational linguistics : linguistic knowledge for visual recognition and natural language descriptions of visual content,"Combining Visual Recognition
+nd Computational Linguistics
+Linguistic Knowledge for Visual Recognition
+nd Natural Language Descriptions
+of Visual Content
+Thesis for obtaining the title of
+Doctor of Engineering Science
+(Dr.-Ing.)
+of the Faculty of Natural Science and Technology I
+of Saarland University
+Marcus Rohrbach, M.Sc.
+Saarbrücken
+March 2014"
+ab2b09b65fdc91a711e424524e666fc75aae7a51,Multi-modal Biomarkers to Discriminate Cognitive State *,"Multi-modal Biomarkers to Discriminate Cognitive State*
+Thomas F. Quatieri 1, James R. Williamson1, Christopher J. Smalt1,
+Joey Perricone, Tejash Patel, Laura Brattain, Brian S. Helfer, Daryush D. Mehta, Jeffrey Palmer
+Kristin Heaton2, Marianna Eddy3, Joseph Moran3
+MIT Lincoln Laboratory, Lexington, Massachusetts, USA
+USARIEM, 3NSRDEC
+. Introduction
+Multimodal biomarkers based on behavorial, neurophysiolgical, and cognitive measurements have
+recently obtained increasing popularity in the detection of cognitive stress- and neurological-based
+disorders. Such conditions are significantly and adversely affecting human performance and quality
+of life for a large fraction of the world’s population. Example modalities used in detection of these
+onditions  include  voice,  facial  expression,  physiology,  eye  tracking,  gait,  and  EEG  analysis.
+Toward  the  goal  of  finding  simple,  noninvasive  means  to  detect,  predict  and  monitor  cognitive
+stress and neurological conditions, MIT Lincoln Laboratory is developing biomarkers that satisfy
+three  criteria.  First,  we  seek  biomarkers  that  reflect  core  components  of  cognitive  status  such  as
+working memory capacity, processing speed, attention, and arousal. Second, and as importantly, we
+seek  biomarkers  that  reflect  timing  and  coordination  relations  both  within  components  of  each
+modality and across different modalities. This is based on the hypothesis that neural coordination
+cross different parts of the brain is essential in cognition (Figure 1). An example of timing and
+oordination  within  a  modality  is  the  set  of  finely  timed  and  synchronized  physiological"
+ab87dfccb1818bdf0b41d732da1f9335b43b74ae,Structured Dictionary Learning for Classification,"SUBMITTED TO IEEE TRANSACTIONS ON SIGNAL PROCESSING
+Structured Dictionary Learning for Classiﬁcation
+Yuanming Suo, Student Member, IEEE, Minh Dao, Student Member, IEEE, Umamahesh Srinivas, Student
+Member, IEEE, Vishal Monga, Senior Member, IEEE, and Trac D. Tran, Fellow, IEEE"
+abc1ef570bb2d7ea92cbe69e101eefa9a53e1d72,Raisonnement abductif en logique de description exploitant les domaines concrets spatiaux pour l'interprétation d'images,"Raisonnement abductif en logique de
+description exploitant les domaines concrets
+spatiaux pour l’interprétation d’images
+Yifan Yang 1, Jamal Atif 2, Isabelle Bloch 1
+. LTCI, Télécom ParisTech, Université Paris-Saclay, Paris, France
+. Université Paris-Dauphine, PSL Research University, CNRS, UMR 7243,
+LAMSADE, 75016 Paris, France
+RÉSUMÉ. L’interprétation d’images a pour objectif non seulement de détecter et reconnaître des
+objets dans une scène mais aussi de fournir une description sémantique tenant compte des in-
+formations contextuelles dans toute la scène. Le problème de l’interprétation d’images peut être
+formalisé comme un problème de raisonnement abductif, c’est-à-dire comme la recherche de la
+meilleure explication en utilisant une base de connaissances. Dans ce travail, nous présentons
+une nouvelle approche utilisant une méthode par tableau pour la génération et la sélection
+d’explications possibles d’une image donnée lorsque les connaissances, exprimées dans une
+logique de description, comportent des concepts décrivant les objets mais aussi les relations
+spatiales entre ces objets. La meilleure explication est sélectionnée en exploitant les domaines
+oncrets pour évaluer le degré de satisfaction des relations spatiales entre les objets."
+abeda55a7be0bbe25a25139fb9a3d823215d7536,Understanding Human-Centric Images: From Geometry to Fashion,"UNIVERSITATPOLITÈCNICADECATALUNYAProgramadeDoctorat:AUTOMÀTICA,ROBÒTICAIVISIÓTesiDoctoralUnderstandingHuman-CentricImages:FromGeometrytoFashionEdgarSimoSerraDirectors:FrancescMorenoNoguerCarmeTorrasMay2015"
+ab8fb278db4405f7db08fa59404d9dd22d38bc83,Implicit and Automated Emotional Tagging of Videos,"UNIVERSITÉ DE GENÈVE
+Département d'Informatique
+FACULTÉ DES SCIENCES
+Professeur Thierry Pun
+Implicit and Automated Emotional
+Tagging of Videos
+THÈSE
+présenté à la Faculté des sciences de l'Université de Genève
+pour obtenir le grade de Docteur ès sciences, mention informatique
+Mohammad SOLEYMANI
+Téhéran (IRAN)
+Thèse No 4368
+GENÈVE
+Repro-Mail - Université de Genève"
+e5823a9d3e5e33e119576a34cb8aed497af20eea,DocFace+: ID Document to Selfie Matching,"DocFace+: ID Document to Selﬁe* Matching
+Yichun Shi, Student Member, IEEE, and Anil K. Jain, Life Fellow, IEEE"
+e510f2412999399149d8635a83eca89c338a99a1,Face Recognition using Block-Based DCT Feature Extraction,"Journal of Advanced Computer Science and Technology, 1 (4) (2012) 266-283
+(cid:13)Science Publishing Corporation
+www.sciencepubco.com/index.php/JACST
+Face Recognition using Block-Based
+DCT Feature Extraction
+K Manikantan1, Vaishnavi Govindarajan1,
+V V S Sasi Kiran1, S Ramachandran2
+Department of Electronics and Communication Engineering,
+M S Ramaiah Institute of Technology, Bangalore, Karnataka, India 560054
+E-mail:
+E-mail:
+E-mail:
+Department of Electronics and Communication Engineering,
+S J B Institute of Technology, Bangalore, Karnataka, India 560060
+E-mail:"
+e56c4c41bfa5ec2d86c7c9dd631a9a69cdc05e69,Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art,"Human Activity Recognition Based on Wearable
+Sensor Data: A Standardization of the
+State-of-the-Art
+Artur Jord˜ao, Antonio C. Nazare Jr., Jessica Sena and William Robson Schwartz
+Smart Surveillance Interest Group, Computer Science Department
+Universidade Federal de Minas Gerais, Brazil
+Email: {arturjordao, antonio.nazare, jessicasena,"
+e5342233141a1d3858ed99ccd8ca0fead519f58b,Finger print and Palm print based Multibiometric Authentication System with GUI Interface,"ISSN: 2277 – 9043
+International Journal of Advanced Research in Computer Science and Electronics Engineering (IJARCSEE)
+Volume 2, Issue 2, February 2013
+Finger print and Palm print based Multibiometric
+Authentication System with GUI Interface
+KALAIGNANASELVI.A#1, NARASIMMALOU.T*2
+#PG Scholar, Dept. of CSE, Dr.Pauls Engineering College, Villupuram District, Tamilnadu, India.
+*Assistant Professor, Dept. of CSE, Dr.Pauls Engineering College, Villupuram District, Tamilnadu, India."
+e52be9a083e621d9ed29c8e9914451a6a327ff59,UvA - DARE ( Digital Academic Repository ) Communication and Automatic Interpretation of Affect from Facial Expressions,"UvA-DARE (Digital Academic Repository)
+Communication and Automatic Interpretation of Affect from Facial Expressions
+Salah, A.A.; Sebe, N.; Gevers, T.
+Published in:
+Affective computing and interaction: psychological, cognitive, and neuroscientific perspectives
+Link to publication
+Citation for published version (APA):
+Salah, A. A., Sebe, N., & Gevers, T. (2010). Communication and Automatic Interpretation of Affect from Facial
+Expressions. In D. Gökçay, & G. Yildirim (Eds.), Affective computing and interaction: psychological, cognitive,
+nd neuroscientific perspectives (pp. 157-183). Hershey, PA: Information Science Reference.
+General rights
+It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s),
+other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons).
+Disclaimer/Complaints regulations
+If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating
+your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask
+the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam,
+The Netherlands. You will be contacted as soon as possible.
+Download date: 12 Sep 2017
+UvA-DARE is a service provided by the library of the University of Amsterdam (http://dare.uva.nl)"
+e5799fd239531644ad9270f49a3961d7540ce358,Kinship classification by modeling facial feature heredity,"KINSHIP CLASSIFICATION BY MODELING FACIAL FEATURE HEREDITY
+Ruogu Fang1, Andrew C. Gallagher1, Tsuhan Chen1, Alexander Loui2
+Dept. of Elec. and Computer Eng., Cornell University 2Eastman Kodak Company"
+e5eb7fa8c9a812d402facfe8e4672670541ed108,Performance of PCA Based Semi-supervised Learning in Face Recognition Using MPEG-7 Edge Histogram Descriptor,"Performance of PCA Based Semi-supervised
+Learning in Face Recognition Using MPEG-7
+Edge Histogram Descriptor
+Shaﬁn Rahman, Sheikh Motahar Naim, Abdullah Al Farooq and Md. Monirul Islam
+Department of Computer Science and Engineering
+Bangladesh University of Engineering and Technology(BUET)
+Dhaka-1000, Bangladesh
+Email: {shaﬁn buet, naim sbh2007,"
+e2d265f606cd25f1fd72e5ee8b8f4c5127b764df,Real-Time End-to-End Action Detection with Two-Stream Networks,"Real-Time End-to-End Action Detection
+with Two-Stream Networks
+Alaaeldin El-Nouby∗†, Graham W. Taylor∗†‡
+School of Engineering, University of Guelph
+Vector Institute for Artiﬁcial Intelligence
+Canadian Institute for Advanced Research"
+f437b3884a9e5fab66740ca2a6f1f3a5724385ea,Human identification technical challenges,"Human Identification Technical Challenges
+P. Jonathon Phillips
+DARPA
+701 N. Fairfax Dr
+Arlington, VA 22203"
+f412d9d7bc7534e7daafa43f8f5eab811e7e4148,Running Head : Anxiety and Emotional Faces in WS 2,"Durham Research Online
+Deposited in DRO:
+6 December 2014
+Version of attached le:
+Accepted Version
+Peer-review status of attached le:
+Peer-reviewed
+Citation for published item:
+Kirk, H. E. and Hocking, D. R. and Riby, D. M. and Cornish, K. M. (2013) 'Linking social behaviour and
+nxiety to attention to emotional faces in Williams syndrome.', Research in developmental disabilities., 34
+(12). pp. 4608-4616.
+Further information on publisher's website:
+http://dx.doi.org/10.1016/j.ridd.2013.09.042
+Publisher's copyright statement:
+NOTICE: this is the author's version of a work that was accepted for publication in Research in Developmental
+Disabilities. Changes resulting from the publishing process, such as peer review, editing, corrections, structural
+formatting, and other quality control mechanisms may not be reected in this document. Changes may have been made
+to this work since it was submitted for publication. A denitive version was subsequently published in Research in
+Developmental Disabilities, 34, 12, December 2013, 10.1016/j.ridd.2013.09.042.
+Additional information:"
+f442a2f2749f921849e22f37e0480ac04a3c3fec,Critical Features for Face Recognition in Humans and Machines,"Critical Features for Face Recognition in Humans and Machines  Naphtali Abudarham1, Lior Shkiller1, Galit Yovel1,2 1School of Psychological Sciences, 2Sagol School of Neuroscience Tel Aviv University, Tel Aviv, Israel   Correspondence regarding this manuscript should be addressed to: Galit Yovel  School of Psychological Sciences & Sagol School of Neuroscience Tel Aviv University Tel Aviv, 69978, Israel Email:"
+f4f6fc473effb063b7a29aa221c65f64a791d7f4,Facial expression recognition in the wild based on multimodal texture features,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 4/20/2018 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use
+FacialexpressionrecognitioninthewildbasedonmultimodaltexturefeaturesBoSunLiandongLiGuoyanZhouJunHeBoSun,LiandongLi,GuoyanZhou,JunHe,“Facialexpressionrecognitioninthewildbasedonmultimodaltexturefeatures,”J.Electron.Imaging25(6),061407(2016),doi:10.1117/1.JEI.25.6.061407."
+f4373f5631329f77d85182ec2df6730cbd4686a9,Recognizing Gender from Human Facial Regions using Genetic Algorithm,"Soft Computing manuscript No.
+(will be inserted by the editor)
+Recognizing Gender from Human Facial Regions using
+Genetic Algorithm
+Avirup Bhattacharyya · Rajkumar Saini ·
+Partha Pratim Roy · Debi Prosad Dogra ·
+Samarjit Kar
+Received: date / Accepted: date"
+f47404424270f6a20ba1ba8c2211adfba032f405,Identification of Face Age range Group using Neural Network,"International Journal of Emerging Technology and Advanced Engineering
+Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 5, May 2012)
+Identification of Face Age range Group using Neural
+Network
+Sneha Thakur1, Ligendra Verma2
+1M.Tech scholar, CSE, RITEE Raipur
+2 Reader, MCA dept, RITEE Raipur"
+f4ebbeb77249d1136c355f5bae30f02961b9a359,Human Computation for Attribute and Attribute Value Acquisition,"Human Computation for Attribute and Attribute Value Acquisition
+Edith Law, Burr Settles, Aaron Snook, Harshit Surana, Luis von Ahn, Tom Mitchell
+School of Computer Science
+Carnegie Melon University"
+f42dca4a4426e5873a981712102aa961be34539a,Next-Flow: Hybrid Multi-Tasking with Next-Frame Prediction to Boost Optical-Flow Estimation in the Wild,"Next-Flow: Hybrid Multi-Tasking with Next-Frame Prediction to Boost
+Optical-Flow Estimation in the Wild
+Nima Sedaghat
+University of Freiburg
+Germany"
+f3d9e347eadcf0d21cb0e92710bc906b22f2b3e7,"NosePose: a competitive, landmark-free methodology for head pose estimation in the wild","NosePose: a competitive, landmark-free
+methodology for head pose estimation in the wild
+Fl´avio H. B. Zavan, Antonio C. P. Nascimento, Olga R. P. Bellon and Luciano Silva
+IMAGO Research Group - Universidade Federal do Paran´a"
+f3ea181507db292b762aa798da30bc307be95344,Covariance Pooling For Facial Expression Recognition,"Covariance Pooling for Facial Expression Recognition
+Computer Vision Lab, ETH Zurich, Switzerland
+VISICS, KU Leuven, Belgium
+Dinesh Acharya†, Zhiwu Huang†, Danda Pani Paudel†, Luc Van Gool†‡
+{acharyad, zhiwu.huang, paudel,"
+f3cf10c84c4665a0b28734f5233d423a65ef1f23,Title Temporal Exemplar-based Bayesian Networks for facialexpression recognition,"Title
+Temporal Exemplar-based Bayesian Networks for facial
+expression recognition
+Author(s)
+Shang, L; Chan, KP
+Citation
+Proceedings - 7Th International Conference On Machine
+Learning And Applications, Icmla 2008, 2008, p. 16-22
+Issued Date
+http://hdl.handle.net/10722/61208
+Rights
+This work is licensed under a Creative Commons Attribution-
+NonCommercial-NoDerivatives 4.0 International License.;
+International Conference on Machine Learning and Applications
+Proceedings. Copyright © IEEE.; ©2008 IEEE. Personal use of
+this material is permitted. However, permission to
+reprint/republish this material for advertising or promotional
+purposes or for creating new collective works for resale or
+redistribution to servers or lists, or to reuse any copyrighted
+omponent of this work in other works must be obtained from"
+f3b7938de5f178e25a3cf477107c76286c0ad691,Object Detection with Deep Learning: A Review,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, MARCH 2017
+Object Detection with Deep Learning: A Review
+Zhong-Qiu Zhao, Member, IEEE, Peng Zheng,
+Shou-tao Xu, and Xindong Wu, Fellow, IEEE"
+eb526174fa071345ff7b1fad1fad240cd943a6d7,Deeply vulnerable: a study of the robustness of face recognition to presentation attacks,"Deeply Vulnerable – A Study of the Robustness of Face Recognition to
+Presentation Attacks
+Amir Mohammadi, Sushil Bhattacharjee, and S´ebastien Marcel ∗†"
+eb566490cd1aa9338831de8161c6659984e923fd,From Lifestyle Vlogs to Everyday Interactions,"From Lifestyle Vlogs to Everyday Interactions
+David F. Fouhey, Wei-cheng Kuo, Alexei A. Efros, Jitendra Malik
+EECS Department, UC Berkeley"
+eb9312458f84a366e98bd0a2265747aaed40b1a6,Facial Expression Sequence Synthesis Based on Shape and Texture Fusion Model,"-4244-1437-7/07/$20.00 ©2007 IEEE
+IV - 473
+ICIP 2007"
+eb716dd3dbd0f04e6d89f1703b9975cad62ffb09, Visual Object Category Discovery in Images and Videos,"Copyright
+Yong Jae Lee"
+eb4d2ec77fae67141f6cf74b3ed773997c2c0cf6,A new soft biometric approach for keystroke dynamics based on gender recognition,"Int. J. Information Technology and Management, Vol. 11, Nos. 1/2, 2012
+A new soft biometric approach for keystroke
+dynamics based on gender recognition
+Romain Giot* and Christophe Rosenberger
+GREYC Research Lab,
+ENSICAEN – Université de Caen Basse Normandie – CNRS,
+4000 Caen, France
+Fax: +33-231538110
+E-mail:
+E-mail:
+*Corresponding author"
+ebb7cc67df6d90f1c88817b20e7a3baad5dc29b9,Fast algorithms for Higher-order Singular Value Decomposition from incomplete data,"Journal of Computational Mathematics
+Vol.xx, No.x, 200x, 1–25.
+http://www.global-sci.org/jcm
+doi:??
+Fast algorithms for Higher-order Singular Value Decomposition
+from incomplete data*
+Department of Mathematics, University of Alabama, Tuscaloosa, AL
+Yangyang Xu
+Email:"
+ebabd1f7bc0274fec88a3dabaf115d3e226f198f,Driver Drowsiness Detection System Based on Feature Representation Learning Using Various Deep Networks,"Driver drowsiness detection system based on feature
+representation learning using various deep networks
+Sanghyuk Park, Fei Pan, Sunghun Kang and Chang D. Yoo
+School of Electrical Engineering, KAIST,
+Guseong-dong, Yuseong-gu, Dajeon, Rep. of Korea
+{shine0624, feipan, sunghun.kang, cd"
+eb48a58b873295d719827e746d51b110f5716d6c,Face Alignment Using K-Cluster Regression Forests With Weighted Splitting,"Face Alignment Using K-cluster Regression Forests
+With Weighted Splitting
+Marek Kowalski and Jacek Naruniec"
+ebd5df2b4105ba04cef4ca334fcb9bfd6ea0430c,Fast Localization of Facial Landmark Points,"Fast Localization of Facial Landmark Points
+Nenad Markuˇs*, Miroslav Frljak*, Igor S. Pandˇzi´c*, J¨orgen Ahlberg†, and Robert Forchheimer†
+* University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia
+Link¨oping University, Department of Electrical Engineering, SE-581 83 Link¨oping, Sweden
+March 28, 2014"
+ebf204e0a3e137b6c24e271b0d55fa49a6c52b41,Visual Tracking Using Deep Motion Features,"Master of Science Thesis in Electrical Engineering
+Department of Electrical Engineering, Linköping University, 2016
+Visual Tracking Using
+Deep Motion Features
+Susanna Gladh"
+c7e4c7be0d37013de07b6d829a3bf73e1b95ad4e,Dynemo: a Video Database of Natural Facial Expressions of Emotions,"The International Journal of Multimedia & Its Applications (IJMA) Vol.5, No.5, October 2013
+DYNEMO: A VIDEO DATABASE OF NATURAL FACIAL
+EXPRESSIONS OF EMOTIONS
+Anna Tcherkassof1, Damien Dupré1, Brigitte Meillon2, Nadine Mandran2,
+Michel Dubois1 and Jean-Michel Adam2
+LIP, Univ. Grenoble Alpes, BP 47 - 38040 Grenoble Cedex 9, France
+LIG, Univ. Grenoble Alpes, BP 53 - 38041 Grenoble Cedex 9, France"
+c7de0c85432ad17a284b5b97c4f36c23f506d9d1,RANSAC-Based Training Data Selection for Speaker State Recognition,"INTERSPEECH 2011
+RANSAC-based Training Data Selection for Speaker State Recognition
+Elif Bozkurt1, Engin Erzin1, C¸ i˘gdem Ero˘glu Erdem2, A.Tanju Erdem3
+Multimedia, Vision and Graphics Laboratory, Koc¸ University, Istanbul, Turkey
+Department of Electrical and Electronics Engineering, Bahc¸es¸ehir University, Istanbul, Turkey
+Department of Electrical and Computer Engineering, ¨Ozye˘gin University, Istanbul, Turkey
+ebozkurt,"
+c7f752eea91bf5495a4f6e6a67f14800ec246d08,Exploring the Transfer Learning Aspect of Deep Neural Networks in Facial Information Processing,"EXPLORING THE TRANSFER
+LEARNING ASPECT OF DEEP
+NEURAL NETWORKS IN FACIAL
+INFORMATION PROCESSING
+A DISSERTATION SUBMITTED TO THE UNIVERSITY OF MANCHESTER
+FOR THE DEGREE OF MASTER OF SCIENCE
+IN THE FACULTY OF ENGINEERING AND PHYSICAL SCIENCES
+Crefeda Faviola Rodrigues
+School of Computer Science"
+c758b9c82b603904ba8806e6193c5fefa57e9613,Heterogeneous Face Recognition with CNNs,"Heterogeneous Face Recognition with CNNs
+Shreyas Saxena
+Jakob Verbeek
+INRIA Grenoble, Laboratoire Jean Kuntzmann"
+c7c03324833ba262eeaada0349afa1b5990c1ea7,A Wearable Face Recognition System on Google Glass for Assisting Social Interactions,"A Wearable Face Recognition System on Google
+Glass for Assisting Social Interactions
+Bappaditya Mandal∗, Chia Shue Ching, Liyuan Li, Vijay Ramaseshan
+Chandrasekhar, Cheston Tan Yin Chet and Lim Joo Hwee
+Visual Computing Department, Institute for Infocomm Research, Singapore
+Email address: (∗Contact author: Bappaditya Mandal);
+{scchia, lyli, vijay, cheston-tan,"
+c7c8d150ece08b12e3abdb6224000c07a6ce7d47,DeMeshNet: Blind Face Inpainting for Deep MeshFace Verification,"DeMeshNet: Blind Face Inpainting for Deep MeshFace Veriﬁcation
+National Laboratory of Pattern Recognition, CASIA
+Center for Research on Intelligent Perception and Computing, CASIA
+Shu Zhang Ran He Tieniu Tan"
+c78fdd080df01fff400a32fb4cc932621926021f,Robust Automatic Facial Expression Detection Method,"Robust Automatic Facial Expression Detection
+Method
+Institute for Pattern Recognition and Artificial Intelligence/ Huazhong University of Science and Technology, Wuhan,
+Institute for Pattern Recognition and Artificial Intelligence/ Huazhong University of Science and Technology, Wuhan,
+Yan Ouyang
+China
+Nong Sang
+China
+Email:"
+c03f48e211ac81c3867c0e787bea3192fcfe323e,Mahalanobis Metric Scoring Learned from Weighted Pairwise Constraints in I-Vector Speaker Recognition System,"INTERSPEECH 2016
+September 8–12, 2016, San Francisco, USA
+Mahalanobis Metric Scoring Learned from Weighted Pairwise Constraints in
+I-vector Speaker Recognition System
+Zhenchun Lei1, Yanhong Wan1, Jian Luo1, Yingen Yang1
+School of Computer Information Engineering, Jiangxi Normal University, Nanchang, China"
+c038beaa228aeec174e5bd52460f0de75e9cccbe,Temporal Segment Networks for Action Recognition in Videos,"Temporal Segment Networks for Action
+Recognition in Videos
+Limin Wang, Yuanjun Xiong, Zhe Wang, Yu Qiao, Dahua Lin, Xiaoou Tang, and Luc Van Gool"
+c043f8924717a3023a869777d4c9bee33e607fb5,Emotion Separation Is Completed Early and It Depends on Visual Field Presentation,"Emotion Separation Is Completed Early and It Depends
+on Visual Field Presentation
+Lichan Liu1,2*, Andreas A. Ioannides1,2
+Lab for Human Brain Dynamics, RIKEN Brain Science Institute, Wakoshi, Saitama, Japan, 2 Lab for Human Brain Dynamics, AAI Scientific Cultural Services Ltd., Nicosia,
+Cyprus"
+c05a7c72e679745deab9c9d7d481f7b5b9b36bdd,"Naval Postgraduate School Monterey, California Approved for Public Release; Distribution Is Unlimited Biometric Challenges for Future Deployments: a Study of the Impact of Geography, Climate, Culture, and Social Conditions on the Effective Collection of Biometrics","NPS-CS-11-005
+NAVAL
+POSTGRADUATE
+SCHOOL
+MONTEREY, CALIFORNIA
+BIOMETRIC CHALLENGES FOR FUTURE DEPLOYMENTS:
+A STUDY OF THE IMPACT OF GEOGRAPHY, CLIMATE, CULTURE,
+AND SOCIAL CONDITIONS ON THE EFFECTIVE
+COLLECTION OF BIOMETRICS
+Paul C. Clark, Heather S. Gregg, with preface by Cynthia E. Irvine
+April 2011
+Approved for public release; distribution is unlimited"
+c0ff7dc0d575658bf402719c12b676a34271dfcd,A New Incremental Optimal Feature Extraction Method for On-Line Applications,"A New Incremental Optimal Feature Extraction
+Method for On-line Applications
+Youness Aliyari Ghassabeh, Hamid Abrishami Moghaddam
+Electrical Engineering Department, K. N. Toosi University of
+Technology, Tehran, Iran"
+c02847a04a99a5a6e784ab580907278ee3c12653,Fine Grained Video Classification for Endangered Bird Species Protection,"Fine Grained Video Classification for
+Endangered Bird Species Protection
+Non-Thesis MS Final Report
+Chenyu Wang
+.  Introduction
+.1 Background
+This project is about detecting eagles in videos. Eagles are endangered species at the brim of
+extinction since 1980s. With the bans of harmful pesticides, the number of eagles keep increasing.
+However, recent studies on golden eagles’ activities in the vicinity of wind turbines have shown
+significant number of turbine blade collisions with eagles as the major cause of eagles’ mortality. [1]
+This project is a part of a larger research project to build an eagle detection and deterrent system
+on wind turbine toward reducing eagles’ mortality. [2] The critical component of this study is a
+omputer vision system for eagle detection in videos. The key requirement are that the system should
+work in real time and detect eagles at a far distance from the camera (i.e. in low resolution).
+There are three different bird species in my dataset - falcon, eagle and seagull. The reason for
+involving only these three species is based on the real world situation. Wind turbines are always
+installed near coast and mountain hill where falcons and seagulls will be the majority. So my model
+will classify the minority eagles out of other bird species during the immigration season and protecting
+them by using the deterrent system.
+.2 Brief Approach"
+c0c8d720658374cc1ffd6116554a615e846c74b5,Modeling Multimodal Clues in a Hybrid Deep Learning Framework for Video Classification,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
+Modeling Multimodal Clues in a Hybrid Deep
+Learning Framework for Video Classiﬁcation
+Yu-Gang Jiang, Zuxuan Wu, Jinhui Tang, Zechao Li, Xiangyang Xue, Shih-Fu Chang"
+eee8a37a12506ff5df72c402ccc3d59216321346,Volume C,"Uredniki:
+dr. Tomaž Erjavec
+Odsek za tehnologije znanja
+Institut »Jožef Stefan«, Ljubljana
+dr. Jerneja Žganec Gros
+Alpineon d.o.o, Ljubljana
+Založnik: Institut »Jožef Stefan«, Ljubljana
+Tisk: Birografika BORI d.o.o.
+Priprava zbornika: Mitja Lasič
+Oblikovanje naslovnice: dr. Damjan Demšar
+Tiskano iz predloga avtorjev
+Naklada:  50
+Ljubljana, oktober 2008
+Konferenco IS 2008 sofinancirata
+Ministrstvo za visoko šolstvo, znanost in tehnologijo
+Institut »Jožef Stefan«
+Informacijska družba
+ISSN 1581-9973
+CIP - Kataložni zapis o publikaciji
+Narodna in univerzitetna knjižnica, Ljubljana"
+ee18e29a2b998eddb7f6663bb07891bfc7262248,Local Linear Discriminant Analysis Framework Using Sample Neighbors,"Local Linear Discriminant Analysis Framework
+Using Sample Neighbors
+Zizhu Fan, Yong Xu, Member, IEEE, and David Zhang, Fellow, IEEE"
+eefb8768f60c17d76fe156b55b8a00555eb40f4d,Subspace Scores for Feature Selection in Computer Vision,"Subspace Scores for Feature Selection in Computer Vision
+Cameron Musco
+Christopher Musco"
+ee463f1f72a7e007bae274d2d42cd2e5d817e751,Automatically Extracting Qualia Relations for the Rich Event Ontology,"Automatically Extracting Qualia Relations for the Rich Event Ontology
+Ghazaleh Kazeminejad1, Claire Bonial2, Susan Windisch Brown1 and Martha Palmer1
+{ghazaleh.kazeminejad, susan.brown,
+University of Colorado Boulder, 2U.S. Army Research Lab"
+eed1dd2a5959647896e73d129272cb7c3a2e145c,The Elements of Fashion Style,"INPUTSTYLE DOCUMENTTOP ITEMS“             ”I need an outﬁt for a beach wedding that I'm going to early this summer. I'm so excited -- it's going to be warm and exotic and tropical... I want my outﬁt to look effortless, breezy, flowy, like I’m floating over the sand! Oh, and obviously no white! For a tropical spot, I think my outﬁt should be bright and"
+ee92d36d72075048a7c8b2af5cc1720c7bace6dd,Face recognition using mixtures of principal components,"FACE RECOGNITION USING MIXTURES OF PRINCIPAL COMPONENTS
+Deepak S. Turaga and Tsuhan Chen
+Video and Display Processing
+Philips Research USA
+Briarcliff Manor, NY 10510"
+eedfb384a5e42511013b33104f4cd3149432bd9e,Multimodal probabilistic person tracking and identification in smart spaces,"Multimodal Probabilistic Person
+Tracking and Identiﬁcation
+in Smart Spaces
+zur Erlangung des akademischen Grades eines
+Doktors der Ingenieurwissenschaften
+der Fakultät für Informatik
+der Universität Fridericiana zu Karlsruhe (TH)
+genehmigte
+Dissertation
+Keni Bernardin
+us Karlsruhe
+Tag der mündlichen Prüfung: 20.11.2009
+Erster Gutachter:
+Zweiter Gutachter:
+Prof. Dr. A. Waibel
+Prof. Dr. R. Stiefelhagen"
+c91103e6612fa7e664ccbc3ed1b0b5deac865b02,Automatic Facial Expression Recognition Using Statistical-Like Moments,"Automatic facial expression recognition using
+statistical-like moments
+Roberto D’Ambrosio, Giulio Iannello, and Paolo Soda
+{r.dambrosio, g.iannello,
+Integrated Research Center, Universit`a Campus Bio-Medico di Roma,
+Via Alvaro del Portillo, 00128 Roma, Italy"
+fc1e37fb16006b62848def92a51434fc74a2431a,A Comprehensive Analysis of Deep Regression,"DRAFT
+A Comprehensive Analysis of Deep Regression
+St´ephane Lathuili`ere, Pablo Mesejo, Xavier Alameda-Pineda, Member IEEE, and Radu Horaud"
+fcd3d69b418d56ae6800a421c8b89ef363418665,Effects of Aging over Facial Feature Analysis and Face Recognition,"Effects of Aging over Facial Feature Analysis and Face
+Recognition
+Bilgin Esme & Bulent Sankur
+Bogaziçi Un. Electronics Eng. Dept. March 2010"
+fcd77f3ca6b40aad6edbd1dab9681d201f85f365,Machine Learning Based Attacks and Defenses in Computer Security: Towards Privacy and Utility Balance in Sensor Environments,"(cid:13)Copyright 2014
+Miro Enev"
+fcf8bb1bf2b7e3f71fb337ca3fcf3d9cf18daa46,Feature Selection via Sparse Approximation for Face Recognition,"MANUSCRIPT SUBMITTED TO IEEE TRANS. PATTERN ANAL. MACH. INTELL., JULY 2010
+Feature Selection via Sparse Approximation for
+Face Recognition
+Yixiong Liang, Lei Wang, Yao Xiang, and Beiji Zou"
+fcbf808bdf140442cddf0710defb2766c2d25c30,Unsupervised Semantic Action Discovery from Video Collections,"IJCV manuscript No.
+(will be inserted by the editor)
+Unsupervised Semantic Action Discovery from Video
+Collections
+Ozan Sener · Amir Roshan Zamir · Chenxia Wu · Silvio Savarese ·
+Ashutosh Saxena
+Received: date / Accepted: date"
+fd4ac1da699885f71970588f84316589b7d8317b,Supervised Descent Method for Solving Nonlinear Least Squares Problems in Computer Vision,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JANUARY 2007
+Supervised Descent Method
+for Solving Nonlinear Least Squares
+Problems in Computer Vision
+Xuehan Xiong, and Fernando De la Torre"
+fdf533eeb1306ba418b09210387833bdf27bb756,Exploiting Unrelated Tasks in Multi-Task Learning,
+fdda5852f2cffc871fd40b0cb1aa14cea54cd7e3,Im2Flow: Motion Hallucination from Static Images for Action Recognition,"Im2Flow: Motion Hallucination from Static Images for Action Recognition
+Ruohan Gao
+UT Austin
+Bo Xiong
+UT Austin
+Kristen Grauman
+UT Austin"
+fdfaf46910012c7cdf72bba12e802a318b5bef5a,Computerized Face Recognition in Renaissance Portrait Art,"Computerized Face Recognition in Renaissance
+Portrait Art
+Ramya Srinivasan, Conrad Rudolph and Amit Roy-Chowdhury"
+fdca08416bdadda91ae977db7d503e8610dd744f,ICT - 2009 . 7 . 1 KSERA Project 2010 - 248085,"ICT-2009.7.1
+KSERA Project
+010-248085
+Deliverable D3.1
+Deliverable D3.1
+Human Robot Interaction
+Human Robot Interaction
+8 October 2010
+Public Document
+The KSERA project (http://www.ksera
+KSERA project (http://www.ksera-project.eu) has received funding from the European Commission
+project.eu) has received funding from the European Commission
+under the 7th Framework Programme (FP7) for Research and Technological Development under grant
+under the 7th Framework Programme (FP7) for Research and Technological Development under grant
+under the 7th Framework Programme (FP7) for Research and Technological Development under grant
+greement n°2010-248085."
+fd96432675911a702b8a4ce857b7c8619498bf9f,Improved Face Detection and Alignment using Cascade Deep Convolutional Network,"Improved Face Detection and Alignment using Cascade
+Deep Convolutional Network
+Weilin Cong†, Sanyuan Zhao†, Hui Tian‡, and Jianbing Shen†
+Beijing Key Laboratory of Intelligent Information Technology, School of
+Computer Science,Beijing Institute of Technology, Beijing 100081, P.R.China
+China Mobile Research Institute, Xuanwu Men West Street, Beijing"
+fdb33141005ca1b208a725796732ab10a9c37d75,A connectionist computational method for face recognition,"Int.J.Appl. Math. Comput.Sci.,2016,Vol. 26,No. 2,451–465
+DOI: 10.1515/amcs-2016-0032
+A CONNECTIONIST COMPUTATIONAL METHOD FOR FACE RECOGNITION
+FRANCISCO A. PUJOL a, HIGINIO MORA a,∗
+, JOS ´E A. GIRONA-SELVA a
+Department of Computer Technology
+University of Alicante, 03690, San Vicente del Raspeig, Alicante, Spain
+e-mail:
+In this work, a modiﬁed version of the elastic bunch graph matching (EBGM) algorithm for face recognition is introduced.
+First, faces are detected by using a fuzzy skin detector based on the RGB color space. Then, the ﬁducial points for the facial
+graph are extracted automatically by adjusting a grid of points to the result of an edge detector. After that, the position of
+the nodes, their relation with their neighbors and their Gabor jets are calculated in order to obtain the feature vector deﬁning
+each face. A self-organizing map (SOM) framework is shown afterwards. Thus, the calculation of the winning neuron and
+the recognition process are performed by using a similarity function that takes into account both the geometric and texture
+information of the facial graph. The set of experiments carried out for our SOM-EBGM method shows the accuracy of our
+proposal when compared with other state-of the-art methods.
+Keywords: pattern recognition, face recognition, neural networks, self-organizing maps.
+Introduction
+libraries,
+In recent years, there has been intensive research carried"
+fd615118fb290a8e3883e1f75390de8a6c68bfde,Joint Face Alignment with Non-parametric Shape Models,"Joint Face Alignment with Non-Parametric
+Shape Models
+Brandon M. Smith and Li Zhang
+University of Wisconsin – Madison
+http://www.cs.wisc.edu/~lizhang/projects/joint-align/"
+fdaf65b314faee97220162980e76dbc8f32db9d6,Face recognition using both visible light image and near-infrared image and a deep network,"Accepted Manuscript
+Face recognition using both visible light image and near-infrared image and a deep
+network
+Kai Guo, Shuai Wu, Yong Xu
+Reference:
+S2468-2322(17)30014-8
+0.1016/j.trit.2017.03.001
+TRIT 41
+To appear in:
+CAAI Transactions on Intelligence Technology
+Received Date: 30 January 2017
+Accepted Date: 28 March 2017
+Please cite this article as: K. Guo, S. Wu, Y. Xu, Face recognition using both visible light image and
+near-infrared image and a deep network, CAAI Transactions on Intelligence Technology (2017), doi:
+0.1016/j.trit.2017.03.001.
+This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to
+our customers we are providing this early version of the manuscript. The manuscript will undergo
+opyediting, typesetting, and review of the resulting proof before it is published in its final form. Please
+note that during the production process errors may be discovered which could affect the content, and all
+legal disclaimers that apply to the journal pertain."
+f2e9494d0dca9fb6b274107032781d435a508de6,Title of Dissertation : UNCONSTRAINED FACE RECOGNITION,
+f2a7f9bd040aa8ea87672d38606a84c31163e171,Human Action Recognition without Human,"Human Action Recognition without Human
+Yun He, Soma Shirakabe, Yutaka Satoh, Hirokatsu Kataoka
+National Institute of Advanced Industrial Science and Technology (AIST)
+Tsukuba, Ibaraki, Japan
+{yun.he, shirakabe-s, yu.satou,"
+f231046d5f5d87e2ca5fae88f41e8d74964e8f4f,Perceived Age Estimation from Face Images,"We are IntechOpen,
+the first native scientific
+publisher of Open Access books
+,350
+08,000
+.7 M
+Open access books available
+International  authors and editors
+Downloads
+Our authors are among the
+Countries delivered to
+TOP 1%
+2.2%
+most cited scientists
+Contributors from top 500 universities
+Selection of our books indexed in the Book Citation Index
+in Web of Science™ Core Collection (BKCI)
+Interested in publishing with us?
+Contact
+Numbers displayed above are based on latest data collected."
+f5770dd225501ff3764f9023f19a76fad28127d4,Real Time Online Facial Expression Transfer with Single Video Camera,"Real Time Online Facial Expression Transfer
+with Single Video Camera"
+f519723238701849f1160d5a9cedebd31017da89,Impact of multi-focused images on recognition of soft biometric traits,"Impact of multi-focused images on recognition of soft biometric traits
+EURECOM, Campus SophiaTech, 450 Route des Chappes, CS 50193 - 06904 Biot Sophia
+V. Chiesaa, J.L. Dugelaya
+Antipolis cedex, FRANCE"
+f558af209dd4c48e4b2f551b01065a6435c3ef33,An Enhanced Attribute Reranking Design for Web Image Search,"International Journal of Emerging Technology in Computer Science & Electronics (IJETCSE)
+ISSN: 0976-1353 Volume 23 Issue 1 –JUNE 2016.
+AN ENHANCED ATTRIBUTE
+RERANKING DESIGN FOR WEB IMAGE
+SEARCH
+Sai Tejaswi Dasari#1 and G K Kishore Babu*2
+#Student,Cse, CIET, Lam,Guntur, India
+* Assistant Professort,Cse, CIET, Lam,Guntur , India"
+e378ce25579f3676ca50c8f6454e92a886b9e4d7,Robust Video Super-Resolution with Learned Temporal Dynamics,"Robust Video Super-Resolution with Learned Temporal Dynamics
+Ding Liu1 Zhaowen Wang2 Yuchen Fan1 Xianming Liu3
+Zhangyang Wang4 Shiyu Chang5 Thomas Huang1
+University of Illinois at Urbana-Champaign 2Adobe Research
+Facebook 4Texas A&M University 5IBM Research"
+e393a038d520a073b9835df7a3ff104ad610c552,Automatic temporal segment detection via bilateral long short-term memory recurrent neural networks,"Automatic temporal segment
+detection via bilateral long short-
+term memory recurrent neural
+networks
+Bo Sun
+Siming Cao
+Jun He
+Lejun Yu
+Liandong Li
+Bo Sun, Siming Cao, Jun He, Lejun Yu, Liandong Li, “Automatic temporal segment
+detection via bilateral long short-term memory recurrent neural networks,” J.
+Electron. Imaging 26(2), 020501 (2017), doi: 10.1117/1.JEI.26.2.020501.
+Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 03/03/2017 Terms of Use: http://spiedigitallibrary.org/ss/termsofuse.aspx"
+e315959d6e806c8fbfc91f072c322fb26ce0862b,An Efficient Face Recognition System Based on Sub-Window Extraction Algorithm,"An Efficient Face Recognition System Based on Sub-Window
+International Journal of Soft Computing and Engineering (IJSCE)
+ISSN: 2231-2307, Volume-1, Issue-6, January 2012
+Extraction Algorithm
+Manish Gupta, Govind sharma"
+e39a0834122e08ba28e7b411db896d0fdbbad9ba,Maximum Likelihood Estimation of Depth Maps Using Photometric Stereo,"Maximum Likelihood Estimation of Depth Maps
+Using Photometric Stereo
+Adam P. Harrison, Student Member, IEEE, and Dileepan Joseph, Member, IEEE"
+e3e2c106ccbd668fb9fca851498c662add257036,"Appearance, context and co-occurrence ensembles for identity recognition in personal photo collections","Appearance, Context and Co-occurrence Ensembles for
+Identity Recognition in Personal Photo Collections
+Archana Sapkota1
+Raghuraman Gopalan2
+University of Colorado at Colorado Springs
+Eric Zavesky2
+T.E.Boult1
+AT&T Labs-Research, Middletown, NJ"
+e3917d6935586b90baae18d938295e5b089b5c62,Face localization and authentication using color and depth images,"Face Localization and Authentication
+Using Color and Depth Images
+Filareti Tsalakanidou, Sotiris Malassiotis, and Michael G. Strintzis, Fellow, IEEE"
+e3144f39f473e238374dd4005c8b83e19764ae9e,Next-Flow: Hybrid Multi-Tasking with Next-Frame Prediction to Boost Optical-Flow Estimation in the Wild,"Next-Flow: Hybrid Multi-Tasking with Next-Frame Prediction to Boost
+Optical-Flow Estimation in the Wild
+Nima Sedaghat
+University of Freiburg
+Germany"
+cfffae38fe34e29d47e6deccfd259788176dc213,Training bookcowgrass flower ? ? water sky doggrass water boat water chair road ? cow grass chair grass dog building ?,"TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. X, NO. X, DECEMBER 2012
+Matrix Completion for Weakly-supervised
+Multi-label Image Classiﬁcation
+Ricardo Cabral, Fernando De la Torre, João P. Costeira, Alexandre Bernardino"
+cfd4004054399f3a5f536df71f9b9987f060f434,Person Recognition in Social Media Photos,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. ??, NO. ??, ?? 20??
+Person Recognition in Personal Photo Collections
+Seong Joon Oh,Rodrigo Benenson, Mario Fritz, and Bernt Schiele, Fellow, IEEE"
+cf875336d5a196ce0981e2e2ae9602580f3f6243,"7 What 1 S It Mean for a Computer to ""have"" Emotions?","7  What 1
+Rosalind W. Picard
+It Mean for a Computer to  ""Have""  Emotions?
+There  is a  lot  of  talk  about  giving machines  emotions,  some  of
+it fluff. Recently at a large technical meeting, a researcher stood up
+nd talked of how a Bamey stuffed animal [the purple dinosaur for
+kids) ""has  emotions.""  He did not define what he meant by this, but
+fter  repeating  it several  times,  it became  apparent  that  children
+ttributed  emotions  to  Barney,  and that  Barney  had  deliberately
+expressive behaviors that would  encourage the  kids to think. Bar-
+ney had emotions. But kids have  attributed  emotions to  dolls and
+stuffed animals for as long a s  we  know; and most of  my technical
+olleagues would agree that such toys have never had and still do
+not have emotions. What is different now that prompts a researcher
+to make such a claim? Is the computational plush an example of  a
+omputer that really does have emotions?
+If  not Barney, then what would  be  an example  of  a  computa-
+tional system that has emotions? I am not a philosopher, and this
+paper will not be  a  discussion  of  the meaning  of  this question in
+ny philosophical sense. However, as an engineer I am interested"
+cfd8c66e71e98410f564babeb1c5fd6f77182c55,Comparative Study of Coarse Head Pose Estimation,"Comparative Study of Coarse Head Pose Estimation
+Lisa M. Brown and Ying-Li Tian
+IBM T.J. Watson Research Center
+Hawthorne, NY 10532"
+cfbb2d32586b58f5681e459afd236380acd86e28,Improving alignment of faces for recognition,"Improving Alignment of Faces for Recognition
+Md. Kamrul Hasan
+Christopher J. Pal
+D´epartement de g´enie informatique et g´enie logiciel
+´Ecole Polytechnique de Montr´eal,
+D´epartement de g´enie informatique et g´enie logiciel
+´Ecole Polytechnique de Montr´eal,
+Qu´ebec, Canada
+Qu´ebec, Canada"
+cfa92e17809e8d20ebc73b4e531a1b106d02b38c,Parametric classification with soft labels using the evidential EM algorithm: linear discriminant analysis versus logistic regression,"Advances in Data Analysis and Classiﬁcation manuscript No.
+(will be inserted by the editor)
+Parametric Classiﬁcation with Soft Labels using the
+Evidential EM Algorithm
+Linear Discriminant Analysis vs. Logistic Regression
+Benjamin Quost · Thierry Denœux ·
+Shoumei Li
+Received: date / Accepted: date"
+cf5a0115d3f4dcf95bea4d549ec2b6bdd7c69150,Detection of emotions from video in non-controlled environment. (Détection des émotions à partir de vidéos dans un environnement non contrôlé),"Detection of emotions from video in non-controlled
+environment
+Rizwan Ahmed Khan
+To cite this version:
+Rizwan Ahmed Khan. Detection of emotions from video in non-controlled environment. Image
+Processing. Universit´e Claude Bernard - Lyon I, 2013. English. <NNT : 2013LYO10227>.
+<tel-01166539v2>
+HAL Id: tel-01166539
+https://tel.archives-ouvertes.fr/tel-01166539v2
+Submitted on 23 Jun 2015
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entiﬁc research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destin´ee au d´epˆot et `a la diffusion de documents
+scientiﬁques de niveau recherche, publi´es ou non,
+´emanant des ´etablissements d’enseignement et de"
+cfdc632adcb799dba14af6a8339ca761725abf0a,Probabilistic Formulations of Regression with Mixed Guidance,"Probabilistic Formulations of Regression with Mixed
+Guidance
+Aubrey Gress, Ian Davidson University of California, Davis"
+cfc30ce53bfc204b8764ebb764a029a8d0ad01f4,Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization,"Regularizing Deep Neural Networks by Noise:
+Its Interpretation and Optimization
+Hyeonwoo Noh
+Tackgeun You
+Dept. of Computer Science and Engineering, POSTECH, Korea
+Jonghwan Mun
+Bohyung Han"
+cf805d478aeb53520c0ab4fcdc9307d093c21e52,Finding Tiny Faces in the Wild with Generative Adversarial Network,"Finding Tiny Faces in the Wild with Generative Adversarial Network
+Yancheng Bai1
+Yongqiang Zhang1
+Mingli Ding2
+Bernard Ghanem1
+Visual Computing Center, King Abdullah University of Science and Technology (KAUST)
+School of Electrical Engineering and Automation, Harbin Institute of Technology (HIT)
+Institute of Software, Chinese Academy of Sciences (CAS)
+{zhangyongqiang,
+Figure1. The detection results of tiny faces in the wild. (a) is the original low-resolution blurry face, (b) is the result of
+re-sizing directly by a bi-linear kernel, (c) is the generated image by the super-resolution method, and our result (d) is learned
+y the super-resolution (×4 upscaling) and reﬁnement network simultaneously. Best viewed in color and zoomed in."
+cf86616b5a35d5ee777585196736dfafbb9853b5,Learning Multiscale Active Facial Patches for Expression Analysis,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
+Learning Multiscale Active Facial Patches for
+Expression Analysis
+Lin Zhong, Qingshan Liu, Peng Yang, Junzhou Huang, and Dimitris N. Metaxas, Senior Member, IEEE"
+cacd51221c592012bf2d9e4894178c1c1fa307ca,Face and Expression Recognition Techniques: A Review,"ISSN: 2277-3754
+ISO 9001:2008 Certified
+International Journal of Engineering and Innovative Technology (IJEIT)
+Volume 4, Issue 11, May 2015
+Face and Expression Recognition Techniques: A
+Review
+Advanced Communication & Signal Processing Laboratory, Department of Electronics & Communication
+engineering, Government College of Engineering Kannur, Kerala, India.
+Rishin C. K, Aswani Pookkudi, A. Ranjith Ram"
+ca0363d29e790f80f924cedaf93cb42308365b3d,Facial Expression Recognition in Image Sequences Using Geometric Deformation Features and Support Vector Machines,"Facial Expression Recognition in Image Sequences
+using Geometric Deformation Features and Support
+Vector Machines
+Irene Kotsiay and Ioannis Pitasy,Senior Member IEEE
+yAristotle University of Thessaloniki
+Department of Informatics
+Box 451
+54124 Thessaloniki, Greece
+email:"
+cad52d74c1a21043f851ae14c924ac689e197d1f,From Ego to Nos-Vision: Detecting Social Relationships in First-Person Views,"From Ego to Nos-vision:
+Detecting Social Relationships in First-Person Views
+Stefano Alletto, Giuseppe Serra, Simone Calderara, Francesco Solera and Rita Cucchiara
+Universit`a degli Studi di Modena e Reggio Emilia
+Via Vignolese 905, 41125 Modena - Italy"
+cad24ba99c7b6834faf6f5be820dd65f1a755b29,"Understanding hand-object manipulation by modeling the contextual relationship between actions, grasp types and object attributes","Understanding hand-object
+manipulation by modeling the
+ontextual relationship between actions,
+grasp types and object attributes
+Minjie Cai1, Kris M. Kitani2 and Yoichi Sato1
+Journal Title
+XX(X):1–14
+(cid:13)The Author(s) 2016
+Reprints and permission:
+sagepub.co.uk/journalsPermissions.nav
+DOI: 10.1177/ToBeAssigned
+www.sagepub.com/"
+cadba72aa3e95d6dcf0acac828401ddda7ed8924,Algorithms and VLSI Architectures for Low-Power Mobile Face Verification,"THÈSE PRÉSENTÉE À LA FACULTÉ DES SCIENCES
+POUR L’OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCES
+Algorithms and VLSI Architectures
+for Low-Power Mobile Face Verification
+Jean-Luc Nagel
+Acceptée sur proposition du jury:
+Prof. F. Pellandini, directeur de thèse
+PD Dr. M. Ansorge, co-directeur de thèse
+Prof. P.-A. Farine, rapporteur
+Dr. C. Piguet, rapporteur
+Soutenue le 2 juin 2005
+INSTITUT DE MICROTECHNIQUE
+UNIVERSITÉ DE NEUCHÂTEL"
+ca37eda56b9ee53610c66951ee7ca66a35d0a846,Semantic Concept Discovery for Large-Scale Zero-Shot Event Detection,"Semantic Concept Discovery for Large-Scale Zero-Shot Event Detection
+Xiaojun Chang1,2, Yi Yang1, Alexander G. Hauptmann2, Eric P. Xing3 and Yao-Liang Yu3∗
+Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney.
+Language Technologies Institute, Carnegie Mellon University.
+Machine Learning Department, Carnegie Mellon University.
+{cxj273, {alex, epxing,"
+ca606186715e84d270fc9052af8500fe23befbda,"Using subclass discriminant analysis, fuzzy integral and symlet decomposition for face recognition","Using Subclass Discriminant Analysis, Fuzzy Integral and Symlet Decomposition for
+Face Recognition
+Seyed Mohammad Seyedzade
+Department of Electrical Engineering,
+Iran Univ. of Science and Technology,
+Narmak, Tehran, Iran
+Email:
+Sattar Mirzakuchaki
+Amir Tahmasbi
+Department of Electrical Engineering,
+Iran Univ. of Science and Technology,
+Department of Electrical Engineering,
+Iran Univ. of Science and Technology,
+Narmak, Tehran, Iran
+Email:
+Narmak, Tehran, Iran
+Email:"
+e4bf70e818e507b54f7d94856fecc42cc9e0f73d,Face Recognition under Varying Blur in an Unconstrained Environment,"IJRET: International Journal of Research in Engineering and Technology        eISSN: 2319-1163 | pISSN: 2321-7308
+FACE RECOGNITION UNDER VARYING BLUR IN AN
+UNCONSTRAINED ENVIRONMENT
+Anubha Pearline.S1, Hemalatha.M2
+M.Tech, Information Technology,Madras Institute of Technology, TamilNadu,India,
+Assistant Professor, Information Technology,Madras Institute of Technology, TamilNadu,India, email:,"
+e4a1b46b5c639d433d21b34b788df8d81b518729,Side Information for Face Completion: a Robust PCA Approach,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
+Side Information for Face Completion: a Robust
+PCA Approach
+Niannan Xue, Student Member, IEEE, Jiankang Deng, Student Member,IEEE,
+Shiyang Cheng, Student Member,IEEE, Yannis Panagakis, Member,IEEE,
+nd Stefanos Zafeiriou, Member, IEEE"
+e4c81c56966a763e021938be392718686ba9135e,Bio-Inspired Architecture for Clustering into Natural and Non-Natural Facial Expressions,",100+OPEN ACCESS BOOKS103,000+INTERNATIONALAUTHORS AND EDITORS106+ MILLIONDOWNLOADSBOOKSDELIVERED TO151 COUNTRIESAUTHORS AMONGTOP 1%MOST CITED SCIENTIST12.2%AUTHORS AND EDITORSFROM TOP 500 UNIVERSITIESSelection of our books indexed in theBook Citation Index in Web of Science™Core Collection (BKCI)Chapter from the book Visual Cortex - Current Status and PerspectivesDownloaded from: http://www.intechopen.com/books/visual-cortex-current-status-and-perspectivesPUBLISHED BYWorld's largest Science,Technology & Medicine Open Access book publisherInterested in publishing with InTechOpen?Contact us at"
+e4e95b8bca585a15f13ef1ab4f48a884cd6ecfcc,Face Recognition with Independent Component Based Super-resolution,"Face Recognition with Independent Component Based
+Super-resolution
+Osman Gokhan Sezer†,a, Yucel Altunbasakb, Aytul Ercila
+Faculty of Engineering and Natural Sciences, Sabanci Univ., Istanbul, Turkiye, 34956
+School of Elec. and Comp. Eng. , Georgia Inst. of Tech., Atlanta, GA, USA, 30332-0250"
+e43ea078749d1f9b8254e0c3df4c51ba2f4eebd5,Facial Expression Recognition Based on Constrained Local Models and Support Vector Machines,"Facial Expression Recognition Based on Constrained
+Local Models and Support Vector Machines
+Nikolay Neshov1, Ivo Draganov2, Agata Manolova3"
+e4c2f8e4aace8cb851cb74478a63d9111ca550ae,Distributed One-class Learning,"DISTRIBUTED ONE-CLASS LEARNING
+Ali Shahin Shamsabadi(cid:63), Hamed Haddadi†, Andrea Cavallaro(cid:63)
+(cid:63)Queen Mary University of London,†Imperial College London"
+e475e857b2f5574eb626e7e01be47b416deff268,Facial Emotion Recognition Using Nonparametric Weighted Feature Extraction and Fuzzy Classifier,"Facial Emotion Recognition Using Nonparametric
+Weighted Feature Extraction and Fuzzy Classifier
+Maryam Imani and Gholam Ali Montazer"
+e4391993f5270bdbc621b8d01702f626fba36fc2,Head Pose Estimation Using Multi-scale Gaussian Derivatives,"Author manuscript, published in ""18th Scandinavian Conference on Image Analysis (2013)""
+DOI : 10.1007/978-3-642-38886-6_31"
+e4d8ba577cabcb67b4e9e1260573aea708574886,Um Sistema De Recomendaç˜ao Inteligente Baseado Em V ´ Idio Aulas Para Educaç˜ao a Distˆancia an Intelligent Recommendation System Based on Video Lectures for Distance Education (revelation),"UM SISTEMA DE RECOMENDAC¸ ˜AO INTELIGENTE BASEADO EM V´IDIO
+AULAS PARA EDUCAC¸ ˜AO A DIST ˆANCIA
+Gaspare Giuliano Elias Bruno
+Tese de Doutorado apresentada ao Programa
+de P´os-gradua¸c˜ao em Engenharia de Sistemas e
+Computa¸c˜ao, COPPE, da Universidade Federal
+do Rio de Janeiro, como parte dos requisitos
+necess´arios `a obten¸c˜ao do t´ıtulo de Doutor em
+Engenharia de Sistemas e Computa¸c˜ao.
+Orientadores: Edmundo Albuquerque de
+Souza e Silva
+Rosa Maria Meri Le˜ao
+Rio de Janeiro
+Janeiro de 2016"
+e475deadd1e284428b5e6efd8fe0e6a5b83b9dcd,Are you eligible? Predicting adulthood from face images via class specific mean autoencoder,"Accepted in Pattern Recognition Letters
+Pattern Recognition Letters
+journal homepage: www.elsevier.com
+Are you eligible? Predicting adulthood from face images via class speciﬁc mean
+utoencoder
+Maneet Singh, Shruti Nagpal, Mayank Vatsa∗∗, Richa Singh
+IIIT-Delhi, New Delhi, 110020, India
+Article history:
+Received 15 March 2017"
+e4abc40f79f86dbc06f5af1df314c67681dedc51,Head Detection with Depth Images in the Wild,"Head Detection with Depth Images in the Wild
+Diego Ballotta, Guido Borghi, Roberto Vezzani and Rita Cucchiara
+Department of Engineering ”Enzo Ferrari”
+University of Modena and Reggio Emilia, Italy
+Keywords:
+Head Detection, Head Localization, Depth Maps, Convolutional Neural Network"
+e4d0e87d0bd6ead4ccd39fc5b6c62287560bac5b,Implicit video multi-emotion tagging by exploiting multi-expression relations,"Implicit Video Multi-Emotion Tagging by Exploiting Multi-Expression
+Relations
+Zhilei Liu, Shangfei Wang*, Zhaoyu Wang and Qiang Ji"
+e48e94959c4ce799fc61f3f4aa8a209c00be8d7f,Design of an Efficient Real-Time Algorithm Using Reduced Feature Dimension for Recognition of Speed Limit Signs,"Hindawi Publishing Corporation
+The Scientific World Journal
+Volume 2013, Article ID 135614, 6 pages
+http://dx.doi.org/10.1155/2013/135614
+Research Article
+Design of an Efficient Real-Time Algorithm Using Reduced
+Feature Dimension for Recognition of Speed Limit Signs
+Hanmin Cho,1 Seungwha Han,2 and Sun-Young Hwang1
+Department of Electronic Engineering, Sogang University, Seoul 121-742, Republic of Korea
+Samsung Techwin R&D Center, Security Solution Division, 701 Sampyeong-dong, Bundang-gu, Seongnam-si,
+Gyeonggi 463-400, Republic of Korea
+Correspondence should be addressed to Sun-Young Hwang;
+Received 28 August 2013; Accepted 1 October 2013
+Academic Editors: P. Daponte, M. Nappi, and N. Nishchal
+Copyright © 2013 Hanmin Cho et al. This is an open access article distributed under the Creative Commons Attribution License,
+which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
+We propose a real-time algorithm for recognition of speed limit signs from a moving vehicle. Linear Discriminant Analysis (LDA)
+required for classification is performed by using Discrete Cosine Transform (DCT) coefficients. To reduce feature dimension in
+LDA, DCT coefficients are selected by a devised discriminant function derived from information obtained by training. Binarization
+nd thinning are performed on a Region of Interest (ROI) obtained by preprocessing a detected ROI prior to DCT for further"
+e496d6be415038de1636bbe8202cac9c1cea9dbe,Facial Expression Recognition in Older Adults using Deep Machine Learning,"Facial Expression Recognition in Older Adults using
+Deep Machine Learning
+Andrea Caroppo, Alessandro Leone and Pietro Siciliano
+National Research Council of Italy, Institute for Microelectronics and Microsystems, Lecce,
+Italy"
+e43cc682453cf3874785584fca813665878adaa7,Face Recognition using Local Derivative Pattern Face Descriptor,"www.ijecs.in
+International Journal Of Engineering And Computer Science ISSN:2319-7242
+Volume 3 Issue 10 October, 2014 Page No.8830-8834
+Face Recognition using Local Derivative Pattern Face
+Descriptor
+Pranita R. Chavan1,  Dr. Dnyandeo J. Pete2
+Department of Electronics and Telecommunication
+Datta Meghe College of Engineering
+Airoli, Navi Mumbai, India 1,2
+Mob: 99206746061
+Mob: 99870353142"
+fec6648b4154fc7e0892c74f98898f0b51036dfe,"A Generic Face Processing Framework: Technologies, Analyses and Applications","A Generic Face Processing
+Framework: Technologies,
+Analyses and Applications
+JANG Kim-fung
+A Thesis Submitted in Partial Ful(cid:12)lment
+of the Requirements for the Degree of
+Master of Philosophy
+Computer Science and Engineering
+Supervised by
+Prof. Michael R. Lyu
+(cid:13)The Chinese University of Hong Kong
+July 2003
+The Chinese University of Hong Kong holds the copyright of this thesis. Any
+person(s) intending to use a part or whole of the materials in the thesis in
+proposed publication must seek copyright release from the Dean of the
+Graduate School."
+fea0a5ed1bc83dd1b545a5d75db2e37a69489ac9,Enhancing Recommender Systems for TV by Face Recognition,"Enhancing Recommender Systems for TV by Face Recognition
+Toon De Pessemier, Damien Verlee and Luc Martens
+iMinds - Ghent University, Technologiepark 15, B-9052 Ghent, Belgium
+{toon.depessemier,
+Keywords:
+Recommender System, Face Recognition, Face Detection, TV, Emotion Detection."
+fe9c460d5ca625402aa4d6dd308d15a40e1010fa,Neural Architecture for Temporal Emotion Classification,"Neural Architecture for Temporal Emotion
+Classiﬁcation
+Roland Schweiger, Pierre Bayerl, and Heiko Neumann
+Universit¨at Ulm, Neuroinformatik, Germany"
+fe464b2b54154d231671750053861f5fd14454f5,Multi Joint Action in CoTeSys-Setup and Challenges-Technical report CoTeSys-TR-1001,"Multi Joint Action in CoTeSys
+- Setup and Challenges -
+Technical report CoTeSys-TR-10-01
+D. Brˇsˇci´c, F. Rohrm¨uller, O. Kourakos, S. Sosnowski, D. Althoff, M. Lawitzky,
+A. M¨ortl, M. Rambow, V. Koropouli, J.R. Medina Hern´andez, X. Zang,
+W. Wang, D. Wollherr, K. K¨uhnlenz, S. Hirche and M. Buss 1
+{drazen, rohrm, omirosk, sosnowski, dalthoff, lawitzky, moertl, rambow, vicky,
+medina, xueliang zang, wangwei, dirk, kuehnlen, hirche,
+M. Eggers, C. Mayer, T. Kruse, A. Kirsch, M. Beetz and B. Radig 2
+{eggers, mayerc, kruset, kirsch, beetz,
+J. Blume, A. Bannat, T. Rehrl and F. Wallhoff 3
+{blume, bannat, rehrl,
+T. Lorenz and A. Schub¨o 4
+{lorenz,
+P. Basili and S. Glasauer 5
+C. Lenz, T. R¨oder, G. Panin and A. Knoll 6
+W. Maier and E. Steinbach 7
+{werner.maier,
+Institute of Automatic Control
+Experimental Psychology Unit"
+fea83550a21f4b41057b031ac338170bacda8805,Learning a Metric Embedding for Face Recognition using the Multibatch Method,"Learning a Metric Embedding
+for Face Recognition
+using the Multibatch Method
+Oren Tadmor
+Yonatan Wexler
+Tal Rosenwein
+Shai Shalev-Shwartz
+Amnon Shashua
+Orcam Ltd., Jerusalem, Israel"
+feeb0fd0e254f38b38fe5c1022e84aa43d63f7cc,Search Pruning with Soft Biometric Systems: Efficiency-Reliability Tradeoff,"EURECOM
+Multimedia Communications Department
+Mobile Communications Department
+229, route des Crˆetes
+B.P. 193
+06904 Sophia-Antipolis
+FRANCE
+Research Report RR-11-255
+Search Pruning with Soft Biometric Systems:
+Efﬁciency-Reliability Tradeoff
+June 1st, 2011
+Last update June 1st, 2011
+Antitza Dantcheva, Arun Singh, Petros Elia and Jean-Luc Dugelay
+EURECOM’s research is partially supported by its industrial members: BMW Group, Cisco,
+Monaco Telecom, Orange, SAP, SFR, Sharp, STEricsson, Swisscom, Symantec, Thales."
+fe0c51fd41cb2d5afa1bc1900bbbadb38a0de139,Bayesian face recognition using 2D Gaussian-Hermite moments,"Rahman et al. EURASIP Journal on Image and Video Processing  (2015) 2015:35
+DOI 10.1186/s13640-015-0090-5
+RESEARCH
+Open Access
+Bayesian face recognition using 2D
+Gaussian-Hermite moments
+S. M. Mahbubur Rahman1*, Shahana Parvin Lata2 and Tamanna Howlader2"
+c8db8764f9d8f5d44e739bbcb663fbfc0a40fb3d,Modeling for part-based visual object detection based on local features,"Modeling for part-based visual object
+detection based on local features
+Von der Fakult¨at f¨ur Elektrotechnik und Informationstechnik
+der Rheinisch-Westf¨alischen Technischen Hochschule Aachen
+zur Erlangung des akademischen Grades eines Doktors
+der Ingenieurwissenschaften genehmigte Dissertation
+vorgelegt von
+Diplom-Ingenieur
+Mark Asbach
+us Neuss
+Berichter:
+Univ.-Prof. Dr.-Ing. Jens-Rainer Ohm
+Univ.-Prof. Dr.-Ing. Til Aach
+Tag der m¨undlichen Pr¨ufung: 28. September 2011
+Diese Dissertation ist auf den Internetseiten der
+Hochschulbibliothek online verf¨ugbar."
+c86e6ed734d3aa967deae00df003557b6e937d3d,Generative Adversarial Networks with Decoder-Encoder Output Noise,"Generative Adversarial Networks with
+Decoder-Encoder Output Noise
+Guoqiang Zhong, Member, IEEE, Wei Gao, Yongbin Liu, Youzhao Yang
+onditional distribution of their neighbors. In [32], Portilla and
+Simoncelli proposed a parametric texture model based on joint
+statistics, which uses a decomposition method that is called
+steerable pyramid decomposition to decompose the texture
+of images. An example-based super-resolution algorithm [11]
+was proposed in 2002, which uses a Markov network to model
+the spatial relationship between the pixels of an image. A
+scene completion algorithm [16] was proposed in 2007, which
+pplied a semantic scene match technique. These traditional
+lgorithms can be applied to particular image generation tasks,
+such as texture synthesis and super-resolution. Their common
+haracteristic is that they predict the images pixel by pixel
+rather than generate an image as a whole, and the basic idea
+of them is to make an interpolation according to the existing
+part of the images. Here, the problem is, given a set of images,
+an we generate totally new images with the same distribution
+of the given ones?"
+c8a4b4fe5ff2ace9ab9171a9a24064b5a91207a3,Locating facial landmarks with binary map cross-correlations,"LOCATING FACIAL LANDMARKS WITH BINARY MAP CROSS-CORRELATIONS
+J´er´emie Nicolle
+K´evin Bailly
+Vincent Rapp
+Mohamed Chetouani
+Univ. Pierre & Marie Curie, ISIR - CNRS UMR 7222, F-75005, Paris - France
+{nicolle, bailly, rapp,"
+c866a2afc871910e3282fd9498dce4ab20f6a332,Surveillance Face Recognition Challenge,"Noname manuscript No.
+(will be inserted by the editor)
+Surveillance Face Recognition Challenge
+Zhiyi Cheng · Xiatian Zhu · Shaogang Gong
+Received: date / Accepted: date"
+c84233f854bbed17c22ba0df6048cbb1dd4d3248,Exploring Locally Rigid Discriminative Patches for Learning Relative Attributes,"Y. VERMA, C. V. JAWAHAR: EXPLORING PATCHES FOR RELATIVE ATTRIBUTES
+Exploring Locally Rigid Discriminative
+Patches for Learning Relative Attributes
+Yashaswi Verma
+http://researchweb.iiit.ac.in/~yashaswi.verma/
+C. V. Jawahar
+http://www.iiit.ac.in/~jawahar/
+IIIT-Hyderabad, India
+http://cvit.iiit.ac.in"
+c81ee278d27423fd16c1a114dcae486687ee27ff,Search Based Face Annotation Using Weakly Labeled Facial Images,"Search Based Face Annotation Using Weakly
+Labeled Facial Images
+Shital Shinde1, Archana Chaugule2
+Computer Department, Savitribai Phule Pune University
+D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune-18
+Mahatma Phulenagar, 120/2 Mahaganpati soc, Chinchwad, Pune-19, MH, India
+D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune-18, Savitribai Phule Pune University
+DYPIET, Pimpri, Pune-18, MH, India"
+c83a05de1b4b20f7cd7cd872863ba2e66ada4d3f,A Deep Learning Perspective on the Origin of Facial Expressions,"BREUER, KIMMEL: A DEEP LEARNING PERSPECTIVE ON FACIAL EXPRESSIONS
+A Deep Learning Perspective on the Origin
+of Facial Expressions
+Ran Breuer
+Ron Kimmel
+Department of Computer Science
+Technion - Israel Institute of Technology
+Technion City, Haifa, Israel
+Figure 1: Demonstration of the ﬁlter visualization process."
+c8adbe00b5661ab9b3726d01c6842c0d72c8d997,Deep Architectures for Face Attributes,"Deep Architectures for Face Attributes
+Tobi Baumgartner, Jack Culpepper
+Computer Vision and Machine Learning Group, Flickr, Yahoo,
+{tobi,"
+fb4545782d9df65d484009558e1824538030bbb1,"Learning Visual Patterns: Imposing Order on Objects, Trajectories and Networks",
+fbf196d83a41d57dfe577b3a54b1b7fa06666e3b,Extreme Learning Machine for Large-Scale Action Recognition,"Extreme Learning Machine for Large-Scale
+Action Recognition
+G¨ul Varol and Albert Ali Salah
+Department of Computer Engineering, Bo˘gazi¸ci University, Turkey"
+fba464cb8e3eff455fe80e8fb6d3547768efba2f,Survey Paper on Emotion Recognition,"International Journal of Engineering and Applied Sciences (IJEAS)
+ISSN: 2394-3661, Volume-3, Issue-2, February 2016
+Survey Paper on Emotion Recognition
+Prachi Shukla, Sandeep Patil"
+fbb2f81fc00ee0f257d4aa79bbef8cad5000ac59,Reading Hidden Emotions: Spontaneous Micro-expression Spotting and Recognition,"Reading Hidden Emotions: Spontaneous
+Micro-expression Spotting and Recognition
+Xiaobai Li, Student Member, IEEE, Xiaopeng Hong, Member, IEEE, Antti Moilanen, Xiaohua Huang, Student
+Member, IEEE, Tomas Pﬁster, Guoying Zhao, Senior Member, IEEE, and Matti Pietik¨ainen, Fellow, IEEE"
+fb9ad920809669c1b1455cc26dbd900d8e719e61,3 D Gaze Estimation from Remote RGB-D Sensors THÈSE,"D Gaze Estimation from Remote RGB-D Sensors
+THÈSE NO 6680 (2015)
+PRÉSENTÉE LE 9 OCTOBRE 2015
+À LA FACULTÉ DES SCIENCES ET TECHNIQUES DE L'INGÉNIEUR
+LABORATOIRE DE L'IDIAP
+PROGRAMME DOCTORAL EN GÉNIE ÉLECTRIQUE
+ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE
+POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCES
+Kenneth Alberto FUNES MORA
+cceptée sur proposition du jury:
+Prof. K. Aminian, président du jury
+Dr J.-M. Odobez,   directeur de thèse
+Prof. L.-Ph. Morency, rapporteur
+Prof. D. Witzner Hansen, rapporteur
+Dr R. Boulic, rapporteur
+Suisse"
+ed28e8367fcb7df7e51963add9e2d85b46e2d5d6,A Novel Approach of Face Recognition Using Convolutional Neural Networks with Auto Encoder,"International J. of Engg. Research & Indu. Appls. (IJERIA).
+ISSN 0974-1518, Vol.9, No. III (December 2016), pp.23-42
+A NOVEL APPROACH OF FACE RECOGNITION USING
+CONVOLUTIONAL NEURAL  NETWORKS WITH AUTO
+ENCODER
+T. SYED AKHEEL1 AND DR. S. A. K JILANI2
+Research Scholar, Dept. of Electronics & Communication Engineering,
+Rayalaseema University Kurnool, Andhra Pradesh.
+2 Research Supervisor, Professor, Dept. of Electronics & Communication Engineering,
+Madanapalle Institute of Technology & Science, Madanapalle, Andhra Pradesh."
+ed08ac6da6f8ead590b390b1d14e8a9b97370794,An Efficient Approach for 3D Face Recognition Using ANN Based Classifiers,"ISSN(Online): 2320-9801
+ISSN (Print):  2320-9798
+International Journal of Innovative Research in Computer
+nd Communication Engineering
+(An ISO 3297: 2007 Certified Organization)
+Vol. 3, Issue 9, September 2015
+An Efficient Approach for 3D Face
+Recognition Using ANN Based Classifiers
+Vaibhav M. Pathak1, Suhas S.Satonkar2, Dr.Prakash B.Khanale3
+Assistant Professor, Dept. of C.S., Shri Shivaji College, Parbhani, M.S, India1
+Assistant Professor, Dept. of C.S., Arts, Commerce and Science College, Gangakhed, M.S, India2
+Associate Professor, Dept. of C.S., Dnyanopasak College Parbhani, M.S, India3"
+edef98d2b021464576d8d28690d29f5431fd5828,Pixel-Level Alignment of Facial Images for High Accuracy Recognition Using Ensemble of Patches,"Pixel-Level Alignment of Facial Images
+for High Accuracy Recognition
+Using Ensemble of Patches
+Hoda Mohammadzade, Amirhossein Sayyafan, Benyamin Ghojogh"
+ed04e161c953d345bcf5b910991d7566f7c486f7,Mirror my emotions! Combining facial expression analysis and synthesis on a robot,"Combining facial expression analysis and synthesis on a
+Mirror my emotions!
+robot
+Stefan Sosnowski1 and Christoph Mayer2 and Kolja K¨uhnlenz3 and Bernd Radig4"
+c1d2d12ade031d57f8d6a0333cbe8a772d752e01,Convex optimization techniques for the efficient recovery of a sparsely corrupted low-rank matrix,"Journal of Math-for-Industry, Vol.2(2010B-5), pp.147–156
+Convex optimization techniques for the ef‌f‌icient recovery of a sparsely
+orrupted low-rank matrix
+Silvia Gandy and Isao Yamada
+Received on August 10, 2010 / Revised on August 31, 2010"
+c10a15e52c85654db9c9343ae1dd892a2ac4a279,Learning the Relative Importance of Objects from Tagged Images for Retrieval and Cross-Modal Search,"Int J Comput Vis (2012) 100:134–153
+DOI 10.1007/s11263-011-0494-3
+Learning the Relative Importance of Objects from Tagged Images
+for Retrieval and Cross-Modal Search
+Sung Ju Hwang · Kristen Grauman
+Received: 16 December 2010 / Accepted: 23 August 2011 / Published online: 18 October 2011
+© Springer Science+Business Media, LLC 2011"
+c1dfabe36a4db26bf378417985a6aacb0f769735,Describing Visual Scene through EigenMaps,"Journal of Computer Vision and Image Processing, NWPJ-201109-50
+Describing Visual Scene through EigenMaps
+Shizhi Chen, Student Member, IEEE, and YingLi Tian, Senior Member, IEEE"
+c1ff88493721af1940df0d00bcfeefaa14f1711f,Subspace Regression: Predicting a Subspace from one Sample,"#1369
+CVPR 2010 Submission #1369. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
+#1369
+Subspace Regression: Predicting a Subspace from one Sample
+Anonymous CVPR submission
+Paper ID 1369"
+c11eb653746afa8148dc9153780a4584ea529d28,Global and Local Consistent Wavelet-domain Age Synthesis,"Global and Local Consistent Wavelet-domain Age
+Synthesis
+Peipei Li†, Yibo Hu†, Ran He Member, IEEE and Zhenan Sun Member, IEEE"
+c1ebbdb47cb6a0ed49c4d1cf39d7565060e6a7ee,Robust Facial Landmark Localization Based on Texture and Pose Correlated Initialization,"Robust Facial Landmark Localization Based on
+Yiyun Pan, Junwei Zhou, Member, IEEE, Yongsheng Gao, Senior Member, IEEE, Shengwu Xiong"
+c1dd69df9dfbd7b526cc89a5749f7f7fabc1e290,Unconstrained face identification with multi-scale block-based correlation,"Unconstrained face identification with multi-scale block-based
+orrelation
+Gaston, J., MIng, J., & Crookes, D. (2016). Unconstrained face identification with multi-scale block-based
+orrelation. In Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal
+Processing (pp. 1477-1481). [978-1-5090-4117-6/17] Institute of Electrical and Electronics Engineers (IEEE).
+Published in:
+Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing
+Document Version:
+Peer reviewed version
+Queen's University Belfast - Research Portal:
+Link to publication record in Queen's University Belfast Research Portal
+Publisher rights
+© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future
+media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or
+redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
+General rights
+Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other
+opyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated
+with these rights.
+Take down policy"
+c68ec931585847b37cde9f910f40b2091a662e83,A Comparative Evaluation of Dotted Raster-Stereography and Feature-Based Techniques for Automated Face Recognition,"(IJACSA) International Journal of Advanced Computer Science and Applications,
+Vol. 9, No. 6, 2018
+A Comparative Evaluation of Dotted Raster-
+Stereography and Feature-Based Techniques for
+Automated Face Recognition
+Muhammad Wasim
+S. Talha Ahsan
+Department of Computer Science
+Department of Electrical Engineering
+Usman Institute of Technology
+Usman Institute of Technology
+Karachi, Pakistan
+Karachi, Pakistan
+Lubaid Ahmed, Syed Faisal Ali,
+Fauzan Saeed
+Department of Computer Science
+Usman Institute of Technology
+Karachi, Pakistan
+feature-based
+system.  The"
+c614450c9b1d89d5fda23a54dbf6a27a4b821ac0,Face Image Retrieval of Efficient Sparse Code words and Multiple Attribute in Binning Image,"Vol.60: e17160480, January-December 2017
+http://dx.doi.org/10.1590/1678-4324-2017160480
+ISSN 1678-4324 Online Edition
+Engineering,Technology and Techniques
+BRAZILIAN ARCHIVES OF
+BIOLOGY AND TECHNOLOGY
+A N   I N T E R N A T I O N A L   J O U R N A L
+Face  Image  Retrieval  of  Efficient  Sparse  Code  words  and
+Multiple Attribute in Binning Image
+Suchitra S1*.
+Srm Easwari Engineering College, Ramapuram, Bharathi Salai, Chennai, Tamil Nadu, India."
+c6f3399edb73cfba1248aec964630c8d54a9c534,A comparison of CNN-based face and head detectors for real-time video surveillance applications,"A Comparison of CNN-based Face and Head Detectors for
+Real-Time Video Surveillance Applications
+Le Thanh Nguyen-Meidine1, Eric Granger 1, Madhu Kiran1 and Louis-Antoine Blais-Morin2
+´Ecole de technologie sup´erieure, Universit´e du Qu´ebec, Montreal, Canada
+Genetec Inc., Montreal, Canada"
+c6ffa09c4a6cacbbd3c41c8ae7a728b0de6e10b6,Feature extraction using constrained maximum variance mapping,"This article appeared in a journal published by Elsevier. The attached
+opy is furnished to the author for internal non-commercial research
+nd education use, including for instruction at the authors institution
+nd sharing with colleagues.
+Other uses, including reproduction and distribution, or selling or
+licensing copies, or posting to personal, institutional or third party
+websites are prohibited.
+In most cases authors are permitted to post their version of the
+rticle (e.g. in Word or Tex form) to their personal website or
+institutional repository. Authors requiring further information
+regarding Elsevier’s archiving and manuscript policies are
+encouraged to visit:
+http://www.elsevier.com/copyright"
+c62c07de196e95eaaf614fb150a4fa4ce49588b4,SSR-Net: A Compact Soft Stagewise Regression Network for Age Estimation,Proceedings of the Twenty-Seventh International Joint Conference on Artiﬁcial Intelligence (IJCAI-18)
+ec90d333588421764dff55658a73bbd3ea3016d2,Protocol for Systematic Literature Review of Face Recognition in Uncontrolled Environment,"Research Article
+Protocol for Systematic Literature Review of Face
+Recognition in Uncontrolled Environment
+Faizan Ullah, Sabir Shah, Dilawar Shah, Abdusalam, Shujaat Ali
+Department of Computer Science, Bacha Khan University, Charsadda, KPK, Pakistan"
+ec1e03ec72186224b93b2611ff873656ed4d2f74,D Reconstruction of “ Inthe-Wild ” Faces in Images and Videos,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
+D Reconstruction of “In-the-Wild” Faces in
+Images and Videos
+James Booth, Anastasios Roussos, Evangelos Ververas, Epameinondas Anton-
+kos, Stylianos Ploumpis, Yannis Panagakis, and Stefanos Zafeiriou"
+ec12f805a48004a90e0057c7b844d8119cb21b4a,Distance-Based Descriptors and Their Application in the Task of Object Detection,"Distance-Based Descriptors and Their
+Application in the Task of Object Detection
+Radovan Fusek(B) and Eduard Sojka
+Department of Computer Science, Technical University of Ostrava, FEECS,
+7. Listopadu 15, 708 33 Ostrava-Poruba, Czech Republic"
+ec54000c6c0e660dd99051bdbd7aed2988e27ab8,Two in One: Joint Pose Estimation and Face Recognition with Pca,"TWO IN ONE: JOINT POSE ESTIMATION AND FACE RECOGNITION WITH P2CA1
+Francesc Tarres*, Antonio Rama*
+{tarres,
+Davide Onofrio+, Stefano Tubaro+
+{d.onofrio,
+*Dept. Teoria del Senyal i Comunicacions - Universitat Politècnica de Catalunya, Barcelona, Spain
++Dipartimento di Elettronica e Informazione - Politecnico di Milano, Meiland, Italy"
+ec0104286c96707f57df26b4f0a4f49b774c486b,An Ensemble CNN2ELM for Age Estimation,"An Ensemble CNN2ELM for Age Estimation
+Mingxing Duan , Kenli Li, Senior Member, IEEE, and Keqin Li, Fellow, IEEE"
+4e32fbb58154e878dd2fd4b06398f85636fd0cf4,A Hierarchical Matcher using Local Classifier Chains,"A Hierarchical Matcher using Local Classiﬁer Chains
+L. Zhang and I.A. Kakadiaris
+Computational Biomedicine Lab, 4849 Calhoun Rd, Rm 373, Houston, TX 77204"
+4ea53e76246afae94758c1528002808374b75cfa,A Review of Scholastic Examination and Models for Face Recognition and Retrieval in Video,"Lasbela, U. J.Sci. Techl., vol.IV , pp. 57-70, 2015
+Review ARTICLE
+A Review of Scholastic  Examination and  Models for Face Recognition
+ISSN 2306-8256
+nd Retrieval in Video
+Varsha Sachdeva1, Junaid Baber2, Maheen Bakhtyar2, Muzamil Bokhari3, Imran Ali4
+Department of Computer Science, SBK Women’s University, Quetta, Balochistan
+Department of CS and IT, University of Balochistan, Quetta
+Department of Physics, University of Balochistan, Quetta
+Institute of Biochemistry, University of Balochistan, Quetta"
+4e97b53926d997f451139f74ec1601bbef125599,Discriminative Regularization for Generative Models,"Discriminative Regularization for Generative Models
+Alex Lamb, Vincent Dumoulin and Aaron Courville
+Montreal Institute for Learning Algorithms, Universit´e de Montr´eal"
+4e27fec1703408d524d6b7ed805cdb6cba6ca132,SSD-Sface: Single shot multibox detector for small faces,"SSD-Sface: Single shot multibox detector for small faces
+C. Thuis"
+4e6c9be0b646d60390fe3f72ce5aeb0136222a10,Long-Term Temporal Convolutions for Action Recognition,"Long-term Temporal Convolutions
+for Action Recognition
+G¨ul Varol, Ivan Laptev, and Cordelia Schmid, Fellow, IEEE"
+4ef0a6817a7736c5641dc52cbc62737e2e063420,Study of Face Recognition Techniques,"International Journal of Advanced Computer Research (ISSN (Print): 2249-7277   ISSN (Online): 2277-7970)
+Volume-4 Number-4 Issue-17 December-2014
+Study of Face Recognition Techniques
+Sangeeta Kaushik1*, R. B. Dubey2 and Abhimanyu Madan3
+Received: 10-November-2014; Revised: 18-December-2014; Accepted: 23-December-2014
+©2014 ACCENTS"
+4e0e49c280acbff8ae394b2443fcff1afb9bdce6,Automatic Learning of Gait Signatures for People Identification,"Automatic learning of gait signatures for people identiﬁcation
+F.M. Castro
+Univ. of Malaga
+fcastro<at>uma.es
+M.J. Mar´ın-Jim´enez
+Univ. of Cordoba
+mjmarin<at>uco.es
+N. Guil
+Univ. of Malaga
+nguil<at>uma.es
+N. P´erez de la Blanca
+Univ. of Granada
+nicolas<at>ugr.es"
+20a432a065a06f088d96965f43d0055675f0a6c1,The Effects of Regularization on Learning Facial Expressions with Convolutional Neural Networks,"In: Proc. of the 25th Int. Conference on Artiﬁcial Neural Networks (ICANN)
+Part II, LNCS 9887, pp. 80-87, Barcelona, Spain, September 2016
+The ﬁnal publication is available at Springer via
+http://dx.doi.org//10.1007/978-3-319-44781-0_10
+The Effects of Regularization on Learning Facial
+Expressions with Convolutional Neural Networks
+Tobias Hinz, Pablo Barros, and Stefan Wermter
+University of Hamburg Department of Computer Science,
+Vogt-Koelln-Strasse 30, 22527 Hamburg, Germany
+http://www.informatik.uni-hamburg.de/WTM"
+20a3ce81e7ddc1a121f4b13e439c4cbfb01adfba,Sparse-MVRVMs Tree for Fast and Accurate Head Pose Estimation in the Wild,"Sparse-MVRVMs Tree for Fast and Accurate
+Head Pose Estimation in the Wild
+Mohamed Selim, Alain Pagani, and Didier Stricker
+Augmented Vision Research Group,
+German Research Center for Artiﬁcial Intelligence (DFKI),
+Tripstaddterstr. 122, 67663 Kaiserslautern, Germany
+Technical University of Kaiserslautern
+http://www.av.dfki.de"
+2004afb2276a169cdb1f33b2610c5218a1e47332,Deep Convolutional Neural Network Used in Single Sample per Person Face Recognition,"Hindawi
+Computational Intelligence and Neuroscience
+Volume 2018, Article ID 3803627, 11 pages
+https://doi.org/10.1155/2018/3803627
+Research Article
+Deep Convolutional Neural Network Used in Single Sample per
+Person Face Recognition
+Junying Zeng , Xiaoxiao Zhao , Junying Gan , Chaoyun Mai
+nd Fan Wang
+, Yikui Zhai,
+School of Information Engineering, Wuyi University, Jiangmen 529020, China
+Correspondence should be addressed to Xiaoxiao Zhao;
+Received 27 November 2017; Revised 23 May 2018; Accepted 26 July 2018; Published 23 August 2018
+Academic Editor: Jos´e Alfredo Hern´andez-P´erez
+Copyright © 2018 Junying Zeng et al. 0is is an open access article distributed under the Creative Commons Attribution License,
+which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
+Face recognition (FR) with single sample per person (SSPP) is a challenge in computer vision. Since there is only one sample to be
+trained, it makes facial variation such as pose, illumination, and disguise dif‌f‌icult to be predicted. To overcome this problem, this paper
+proposes a scheme combined traditional and deep learning (TDL) method to process the task. First, it proposes an expanding sample
+method based on traditional approach. Compared with other expanding sample methods, the method can be used easily and"
+20e504782951e0c2979d9aec88c76334f7505393,Robust LSTM-Autoencoders for Face De-Occlusion in the Wild,"Robust LSTM-Autoencoders for Face De-Occlusion
+in the Wild
+Fang Zhao, Jiashi Feng, Jian Zhao, Wenhan Yang, Shuicheng Yan"
+20ade100a320cc761c23971d2734388bfe79f7c5,Subspace Clustering via Good Neighbors,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
+Subspace Clustering via Good Neighbors
+Jufeng Yang, Jie Liang, Kai Wang, Ming-Hsuan Yang"
+202d8d93b7b747cdbd6e24e5a919640f8d16298a,Face Classification via Sparse Approximation,"Face Classiﬁcation via Sparse Approximation
+Elena Battini S˝onmez1, Bulent Sankur2 and Songul Albayrak3
+Computer Science Department, Bilgi University, Dolapdere, Istanbul, TR
+Electric and Electronic Engineering Department, Bo¯gazici University, Istanbul, TR
+Computer Engineering Department, Yıldız Teknik University, Istanbul, TR"
+205b34b6035aa7b23d89f1aed2850b1d3780de35,Log-domain polynomial filters for illumination-robust face recognition,"014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP)
+978-1-4799-2893-4/14/$31.00 ©2014 IEEE
+Shenzhen Key Lab. of Information Sci&Tech,
+♯Nagaoka University of Technology, Japan
+RECOGNITION
+. INTRODUCTION"
+2059d2fecfa61ddc648be61c0cbc9bc1ad8a9f5b,Co-Localization of Audio Sources in Images Using Binaural Features and Locally-Linear Regression,"TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 23, NO. 4, APRIL 2015
+Co-Localization of Audio Sources in Images Using
+Binaural Features and Locally-Linear Regression
+Antoine Deleforge∗ Radu Horaud∗ Yoav Y. Schechner‡ Laurent Girin∗†
+INRIA Grenoble Rhˆone-Alpes, Montbonnot Saint-Martin, France
+Univ. Grenoble Alpes, GIPSA-Lab, France
+Dept. Electrical Eng., Technion-Israel Inst. of Technology, Haifa, Israel"
+20111924fbf616a13d37823cd8712a9c6b458cd6,Linear Regression Line based Partial Face Recognition,"International Journal of Computer Applications (0975 – 8887)
+Volume 130 – No.11, November2015
+Linear Regression Line based Partial Face Recognition
+Naveena M.
+Department of Studies in
+Computer Science,
+Manasagagothri,
+Mysore.
+G. Hemantha Kumar
+Department of Studies in
+Computer Science,
+Manasagagothri,
+Mysore.
+P. Nagabhushan
+Department of Studies in
+Computer Science,
+Manasagagothri,
+Mysore.
+images.  In"
+20532b1f80b509f2332b6cfc0126c0f80f438f10,A Deep Matrix Factorization Method for Learning Attribute Representations,"A deep matrix factorization method for learning
+ttribute representations
+George Trigeorgis, Konstantinos Bousmalis, Student Member, IEEE, Stefanos Zafeiriou, Member, IEEE
+Bj¨orn W. Schuller, Senior member, IEEE"
+205af28b4fcd6b569d0241bb6b255edb325965a4,Facial expression recognition and tracking for intelligent human-robot interaction,"Intel Serv Robotics (2008) 1:143–157
+DOI 10.1007/s11370-007-0014-z
+SPECIAL ISSUE
+Facial expression recognition and tracking for intelligent human-robot
+interaction
+Y. Yang · S. S. Ge · T. H. Lee · C. Wang
+Received: 27 June 2007 / Accepted: 6 December 2007 / Published online: 23 January 2008
+© Springer-Verlag 2008"
+20a0b23741824a17c577376fdd0cf40101af5880,Learning to Track for Spatio-Temporal Action Localization,"Learning to track for spatio-temporal action localization
+Philippe Weinzaepfela
+Zaid Harchaouia,b
+NYU
+Inria∗
+Cordelia Schmida"
+18c72175ddbb7d5956d180b65a96005c100f6014,From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 23, NO. 6,
+JUNE 2001
+From Few to Many: Illumination Cone
+Models for Face Recognition under
+Variable Lighting and Pose
+Athinodoros S. Georghiades, Student Member, IEEE, Peter N. Belhumeur, Member, IEEE, and
+David J. Kriegman, Senior Member, IEEE"
+18636347b8741d321980e8f91a44ee054b051574,Facial marks: Soft biometric for face recognition,"978-1-4244-5654-3/09/$26.00 ©2009 IEEE
+ICIP 2009"
+181045164df86c72923906aed93d7f2f987bce6c,Rheinisch-westfälische Technische Hochschule Aachen,"RHEINISCH-WESTFÄLISCHE TECHNISCHE
+HOCHSCHULE AACHEN
+KNOWLEDGE-BASED SYSTEMS GROUP
+PROF. GERHARD LAKEMEYER, PH. D.
+Detection and Recognition of Human
+Faces using Random Forests for a
+Mobile Robot
+MASTER OF SCIENCE THESIS
+VAISHAK BELLE
+MATRICULATION NUMBER: 26 86 51
+SUPERVISOR:
+SECOND SUPERVISOR:
+PROF. GERHARD LAKEMEYER, PH. D.
+PROF. ENRICO BLANZIERI, PH. D.
+ADVISERS:
+STEFAN SCHIFFER, THOMAS DESELAERS"
+18d5b0d421332c9321920b07e0e8ac4a240e5f1f,Collaborative Representation Classification Ensemble for Face Recognition,"Collaborative Representation Classiﬁcation
+Ensemble for Face Recognition
+Xiao Chao Qu, Suah Kim, Run Cui and Hyoung Joong Kim"
+18d51a366ce2b2068e061721f43cb798177b4bb7,Looking into your eyes: observed pupil size influences approach-avoidance responses.,"Cognition and Emotion
+ISSN: 0269-9931 (Print) 1464-0600 (Online) Journal homepage: http://www.tandfonline.com/loi/pcem20
+Looking into your eyes: observed pupil size
+influences approach-avoidance responses
+Marco Brambilla, Marco Biella & Mariska E. Kret
+To cite this article: Marco Brambilla, Marco Biella & Mariska E. Kret (2018): Looking into your
+eyes: observed pupil size influences approach-avoidance responses, Cognition and Emotion, DOI:
+0.1080/02699931.2018.1472554
+To link to this article:  https://doi.org/10.1080/02699931.2018.1472554
+View supplementary material
+Published online: 11 May 2018.
+Submit your article to this journal
+View related articles
+View Crossmark data
+Full Terms & Conditions of access and use can be found at
+http://www.tandfonline.com/action/journalInformation?journalCode=pcem20"
+1885acea0d24e7b953485f78ec57b2f04e946eaf,Combining Local and Global Features for 3D Face Tracking,"Combining Local and Global Features for 3D Face Tracking
+Pengfei Xiong, Guoqing Li, Yuhang Sun
+Megvii (face++) Research
+{xiongpengfei, liguoqing,"
+18a849b1f336e3c3b7c0ee311c9ccde582d7214f,"Efficiently Scaling up Crowdsourced Video Annotation A Set of Best Practices for High Quality, Economical Video Labeling","Int J Comput Vis
+DOI 10.1007/s11263-012-0564-1
+Efﬁciently Scaling up Crowdsourced Video Annotation
+A Set of Best Practices for High Quality, Economical Video Labeling
+Carl Vondrick · Donald Patterson · Deva Ramanan
+Received: 31 October 2011 / Accepted: 20 August 2012
+© Springer Science+Business Media, LLC 2012"
+18cd79f3c93b74d856bff6da92bfc87be1109f80,A N a Pplication to H Uman F Ace P Hoto - S Ketch S Ynthesis and R Ecognition,"International Journal of Advances in Engineering & Technology, May 2012.
+©IJAET                                                                                                          ISSN: 2231-1963
+AN APPLICATION TO HUMAN FACE PHOTO-SKETCH
+SYNTHESIS AND RECOGNITION
+Amit R. Sharma and 2Prakash. R. Devale
+Student and 2Professor & Head,
+Department of Information Tech., Bharti Vidyapeeth Deemed University, Pune, India"
+1886b6d9c303135c5fbdc33e5f401e7fc4da6da4,Knowledge Guided Disambiguation for Large-Scale Scene Classification With Multi-Resolution CNNs,"Knowledge Guided Disambiguation for Large-Scale
+Scene Classiﬁcation with Multi-Resolution CNNs
+Limin Wang, Sheng Guo, Weilin Huang, Member, IEEE, Yuanjun Xiong, and Yu Qiao, Senior Member, IEEE"
+1888bf50fd140767352158c0ad5748b501563833,A Guided Tour of Face Processing,"PA R T 1
+THE BASICS"
+185360fe1d024a3313042805ee201a75eac50131,Person De-Identification in Videos,"Person De-Identiﬁcation in Videos
+Prachi Agrawal and P. J. Narayanan"
+1824b1ccace464ba275ccc86619feaa89018c0ad,One millisecond face alignment with an ensemble of regression trees,"One Millisecond Face Alignment with an Ensemble of Regression Trees
+Vahid Kazemi and Josephine Sullivan
+KTH, Royal Institute of Technology
+Computer Vision and Active Perception Lab
+Teknikringen 14, Stockholm, Sweden"
+27a0a7837f9114143717fc63294a6500565294c2,Face Recognition in Unconstrained Environments: A Comparative Study,"Face Recognition in Unconstrained Environments: A
+Comparative Study
+Rodrigo Verschae, Javier Ruiz-Del-Solar, Mauricio Correa
+To cite this version:
+Rodrigo Verschae, Javier Ruiz-Del-Solar, Mauricio Correa. Face Recognition in Unconstrained
+Environments: A Comparative Study: . Workshop on Faces in ’Real-Life’ Images: Detection,
+Alignment, and Recognition, Oct 2008, Marseille, France. 2008. <inria-00326730>
+HAL Id: inria-00326730
+https://hal.inria.fr/inria-00326730
+Submitted on 5 Oct 2008
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entiﬁc research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destin´ee au d´epˆot et `a la diffusion de documents
+scientiﬁques de niveau recherche, publi´es ou non,
+´emanant des ´etablissements d’enseignement et de"
+275b5091c50509cc8861e792e084ce07aa906549,Leveraging the User's Face as a Known Object in Handheld Augmented Reality,"Institut für Informatik
+der Technischen
+Universität München
+Dissertation
+Leveraging the User’s Face as a Known Object
+in Handheld Augmented Reality
+Sebastian Bernhard Knorr"
+276dbb667a66c23545534caa80be483222db7769,An Introduction to Image-based 3D Surface Reconstruction and a Survey of Photometric Stereo Methods,"D Res. 2, 03(2011)4
+0.1007/3DRes.03(2011)4
+DR REVIEW                                                            w
+An  Introduction  to  Image-based  3D  Surface  Reconstruction  and  a
+Survey of Photometric Stereo Methods
+Steffen Herbort • Christian Wöhler
+introduction
+image-based  3D
+techniques.  Then  we  describe
+Received: 21Feburary 2011 / Revised: 20 March 2011 / Accepted: 11 May 2011
+© 3D Research Center, Kwangwoon University and Springer 2011"
+270733d986a1eb72efda847b4b55bc6ba9686df4,Recognizing Facial Expressions Using Model-Based Image Interpretation,"We are IntechOpen,
+the first native scientific
+publisher of Open Access books
+,350
+08,000
+.7 M
+Open access books available
+International  authors and editors
+Downloads
+Our authors are among the
+Countries delivered to
+TOP 1%
+2.2%
+most cited scientists
+Contributors from top 500 universities
+Selection of our books indexed in the Book Citation Index
+in Web of Science™ Core Collection (BKCI)
+Interested in publishing with us?
+Contact
+Numbers displayed above are based on latest data collected."
+27169761aeab311a428a9dd964c7e34950a62a6b,Face Recognition Using 3D Head Scan Data Based on Procrustes Distance,"International Journal of the Physical Sciences Vol. 5(13), pp. 2020 -2029, 18 October, 2010
+Available online at http://www.academicjournals.org/IJPS
+ISSN 1992 - 1950 ©2010 Academic Journals
+Full Length Research Paper
+Face recognition using 3D head scan data based on
+Ahmed Mostayed1, Sikyung Kim1, Mohammad Mynuddin Gani Mazumder1* and Se Jin Park2
+Procrustes distance
+Department of Electrical Engineering, Kongju National University, South Korea.
+Korean Research Institute of Standards and Science (KRISS), Korea.
+Accepted 6 July, 2010
+Recently,  face  recognition  has  attracted  significant  attention  from  the  researchers  and  scientists  in
+various  fields  of  research,  such  as  biomedical  informatics,  pattern  recognition,  vision,  etc  due  its
+pplications in commercially available systems, defense and security purpose. In this paper a practical
+method  for  face  reorganization  utilizing  head  cross  section  data  based  on  Procrustes  analysis  is
+proposed. This proposed method relies on shape signatures of the contours extracted from face data.
+The shape signatures are created by calculating the centroid distance of the boundary points, which is
+translation  and  rotation  invariant  signature.  The  shape  signatures  for  a  selected  region  of  interest
+(ROI)  are  used  as  feature  vectors  and  authentication  is  done  using  them.  After  extracting  feature
+vectors  a  comparison  analysis  is  performed  utilizing  Procrustes  distance  to  differentiate  their  face
+pattern from each other. The proposed scheme attains an equal error rate (EER) of 4.563% for the 400"
+27173d0b9bb5ce3a75d05e4dbd8f063375f24bb5,Effect of Different Occlusion on Facial Expressions Recognition,"Ankita Vyas  Int. Journal of Engineering Research and Applications                               www.ijera.com
+ISSN : 2248-9622, Vol. 4, Issue 10( Part - 3), October 2014, pp.40-44
+RESEARCH ARTICLE
+OPEN ACCESS
+Effect of Different Occlusion on Facial Expressions Recognition
+Ankita Vyas*, Ramchand Hablani**
+*(Department of Computer Science, RGPV University, Indore)
+** (Department of Computer Science, RGPV University, Indore)"
+2770b095613d4395045942dc60e6c560e882f887,GridFace: Face Rectification via Learning Local Homography Transformations,"GridFace: Face Rectiﬁcation via Learning Local
+Homography Transformations
+Erjin Zhou, Zhimin Cao, and Jian Sun
+Face++, Megvii Inc."
+27cccf992f54966feb2ab4831fab628334c742d8,"Facial Expression Recognition by Statistical, Spatial Features and using Decision Tree","International Journal of Computer Applications (0975 – 8887)
+Volume 64– No.18, February 2013
+Facial Expression Recognition by Statistical, Spatial
+Features and using Decision Tree
+Nazil Perveen
+Assistant Professor
+CSIT Department
+GGV BIlaspur, Chhattisgarh
+India
+Darshan Kumar
+Assistant Professor
+Electronics (ECE) Department
+JECRC Jaipur, Rajasthan India
+IshanBhardwaj
+Student of Ph.D.
+Electrical Department
+NIT Raipur, Chhattisgarh India"
+27f8b01e628f20ebfcb58d14ea40573d351bbaad,Events based Multimedia Indexing and Retrieval,"DEPARTMENT OF INFORMATION ENGINEERING AND COMPUTER SCIENCE
+ICT International Doctoral School
+Events based Multimedia Indexing
+nd Retrieval
+Kashif Ahmad
+SUBMITTED TO THE DEPARTMENT OF
+INFORMATION ENGINEERING AND COMPUTER SCIENCE (DISI)
+IN THE PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE
+DOCTOR OF PHILOSOPHY
+Advisor:
+Examiners: Prof. Marco Carli, Universit`a degli Studi di Roma Tre, Italy
+Prof. Nicola Conci, Universit`a degli Studi di Trento, Italy
+Prof. Pietro Zanuttigh, Universit`a degli Studi di Padova, Italy
+Prof. Giulia Boato, Universit`a degli Studi di Trento, Italy
+December 2017"
+27b1670e1b91ab983b7b1ecfe9eb5e6ba951e0ba,Comparison between k-nn and svm method for speech emotion recognition,"Comparison between k-nn and svm method
+for speech emotion recognition
+Muzaffar Khan, Tirupati Goskula, Mohmmed Nasiruddin ,Ruhina Quazi
+Anjuman College of Engineering & Technology ,Sadar, Nagpur, India"
+27ee8482c376ef282d5eb2e673ab042f5ded99d7,Scale Normalization for the Distance Maps AAM,"Scale Normalization for the Distance Maps AAM.
+Denis GIRI, Maxime ROSENWALD, Benjamin VILLENEUVE, Sylvain LE GALLOU and Renaud S ´EGUIER
+Email: {denis.giri, maxime.rosenwald, benjamin.villeneuve, sylvain.legallou,
+Avenue de la boulaie, BP 81127,
+5 511 Cesson-S´evign´e, France
+Sup´elec, IETR-SCEE Team"
+4b4106614c1d553365bad75d7866bff0de6056ed,Unconstrained Facial Images: Database for Face Recognition Under Real-World Conditions,"Unconstrained Facial Images: Database for Face
+Recognition under Real-world Conditions⋆
+Ladislav Lenc1,2 and Pavel Kr´al1,2
+Dept. of Computer Science & Engineering
+University of West Bohemia
+Plzeˇn, Czech Republic
+NTIS - New Technologies for the Information Society
+University of West Bohemia
+Plzeˇn, Czech Republic"
+4b89cf7197922ee9418ae93896586c990e0d2867,Unsupervised Discovery of Action Classes,"LATEX Author Guidelines for CVPR Proceedings
+First Author
+Institution1
+Institution1 address"
+4b04247c7f22410681b6aab053d9655cf7f3f888,Robust Face Recognition by Constrained Part-based Alignment,"Robust Face Recognition by Constrained Part-based
+Alignment
+Yuting Zhang, Kui Jia, Yueming Wang, Gang Pan, Tsung-Han Chan, Yi Ma"
+4b60e45b6803e2e155f25a2270a28be9f8bec130,Attribute based object identification,"Attribute Based Object Identiﬁcation
+Yuyin Sun, Liefeng Bo and Dieter Fox"
+4b48e912a17c79ac95d6a60afed8238c9ab9e553,Minimum Margin Loss for Deep Face Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
+Minimum Margin Loss for Deep Face Recognition
+Xin Wei, Student Member, IEEE, Hui Wang, Member, IEEE, Bryan Scotney, and Huan Wan"
+4b5eeea5dd8bd69331bd4bd4c66098b125888dea,Human Activity Recognition Using Conditional Random Fields and Privileged Information,"Human Activity Recognition Using Conditional
+Random Fields and Privileged Information
+DOCTORAL THESIS
+submitted to
+the designated by the General Assembly Composition of the
+Department of Computer Science & Engineering Inquiry
+Committee
+Michalis Vrigkas
+in partial fulﬁllment of the Requirements for the Degree of
+DOCTOR OF PHILOSOPHY
+February 2016"
+4be03fd3a76b07125cd39777a6875ee59d9889bd,Content-based analysis for accessing audiovisual archives: Alternatives for concept-based indexing and search,"CONTENT-BASED ANALYSIS FOR ACCESSING AUDIOVISUAL ARCHIVES:
+ALTERNATIVES FOR CONCEPT-BASED INDEXING AND SEARCH
+Tinne Tuytelaars
+ESAT/PSI - IBBT
+KU Leuven, Belgium"
+11f7f939b6fcce51bdd8f3e5ecbcf5b59a0108f5,Rolling Riemannian Manifolds to Solve the Multi-class Classification Problem,"Rolling Riemannian Manifolds to Solve the Multi-class Classiﬁcation Problem
+Rui Caseiro1, Pedro Martins1, João F. Henriques1, Fátima Silva Leite1,2, and Jorge Batista1
+Institute of Systems and Robotics - University of Coimbra, Portugal
+Department of Mathematics - University of Coimbra, Portugal ,
+{ruicaseiro, pedromartins, henriques,"
+11691f1e7c9dbcbd6dfd256ba7ac710581552baa,SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos,"SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos
+Silvio Giancola, Mohieddine Amine, Tarek Dghaily, Bernard Ghanem
+King Abdullah University of Science and Technology (KAUST), Saudi Arabia"
+1149c6ac37ae2310fe6be1feb6e7e18336552d95,"Classification of Face Images for Gender, Age, Facial Expression, and Identity","Proc. Int. Conf. on Artiﬁcial Neural Networks (ICANN’05), Warsaw, LNCS 3696, vol. I, pp. 569-574, Springer Verlag 2005
+Classiﬁcation of Face Images for Gender, Age,
+Facial Expression, and Identity1
+Torsten Wilhelm, Hans-Joachim B¨ohme, and Horst-Michael Gross
+Department of Neuroinformatics and Cognitive Robotics
+Ilmenau Technical University, P.O.Box 100565, 98684 Ilmenau, Germany"
+11f17191bf74c80ad0b16b9f404df6d03f7c8814,Recognition of Visually Perceived Compositional Human Actions by Multiple Spatio-Temporal Scales Recurrent Neural Networks,"Recognition of Visually Perceived Compositional
+Human Actions by Multiple Spatio-Temporal Scales
+Recurrent Neural Networks
+Haanvid Lee, Minju Jung, and Jun Tani"
+1198572784788a6d2c44c149886d4e42858d49e4,Learning Discriminative Features using Encoder-Decoder type Deep Neural Nets,"Learning Discriminative Features using Encoder/Decoder type Deep
+Neural Nets
+Vishwajeet Singh1, Killamsetti Ravi Kumar2, K Eswaran3
+ALPES, Bolarum, Hyderabad 500010,
+ALPES, Bolarum, Hyderabad 500010,
+SNIST, Ghatkesar, Hyderabad 501301,"
+11fe6d45aa2b33c2ec10d9786a71c15ec4d3dca8,Tied Factor Analysis for Face Recognition across Large Pose Differences,"JUNE 2008
+Tied Factor Analysis for Face Recognition
+cross Large Pose Differences
+Simon J.D. Prince, Member, IEEE, James H. Elder, Member, IEEE,
+Jonathan Warrell, Member, IEEE, and Fatima M. Felisberti"
+1134a6be0f469ff2c8caab266bbdacf482f32179,Facial Expression Identification Using Four-bit Co- Occurrence Matrixfeatures and K-nn Classifier,"IJRET: International Journal of Research in Engineering and Technology        eISSN: 2319-1163 | pISSN: 2321-7308
+FACIAL EXPRESSION IDENTIFICATION USING FOUR-BIT CO-
+OCCURRENCE MATRIXFEATURES AND K-NN CLASSIFIER
+Bonagiri  C S K Sunil Kumar1, V Bala Shankar2, Pullela S V V S R Kumar3
+,2,3 Department of Computer Science & Engineering, Aditya College of Engineering, Surampalem, East Godavari
+District, Andhra Pradesh, India"
+111a9645ad0108ad472b2f3b243ed3d942e7ff16,Facial Expression Classification Using Combined Neural Networks,"Facial Expression Classification Using
+Combined Neural Networks
+Rafael V. Santos, Marley M.B.R. Vellasco, Raul Q. Feitosa, Ricardo Tanscheit
+DEE/PUC-Rio, Marquês de São Vicente 225, Rio de Janeiro – RJ - Brazil"
+111d0b588f3abbbea85d50a28c0506f74161e091,Facial Expression Recognition from Visual Information using Curvelet Transform,"International Journal of Computer Applications (0975 – 8887)
+Volume 134 – No.10, January 2016
+Facial Expression Recognition from Visual Information
+using Curvelet Transform
+Pratiksha Singh
+Surabhi Group of Institution Bhopal
+systems.  Further  applications"
+11ac88aebe0230e743c7ea2c2a76b5d4acbfecd0,Hybrid Cascade Model for Face Detection in the Wild Based on Normalized Pixel Difference and a Deep Convolutional Neural Network,"Hybrid Cascade Model for Face Detection in the Wild
+Based on Normalized Pixel Difference and a Deep
+Convolutional Neural Network
+Darijan Marčetić[0000-0002-6556-665X], Martin Soldić[0000-0002-4031-0404]
+nd Slobodan Ribarić[0000-0002-8708-8513]
+University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia
+{darijan.marcetic, martin.soldic,"
+7d98dcd15e28bcc57c9c59b7401fa4a5fdaa632b,Face Appearance Factorization for Expression Analysis and Synthesis,"FACE APPEARANCE FACTORIZATION FOR EXPRESSION ANALYSIS AND SYNTHESIS
+Bouchra Abboud, Franck Davoine
+Heudiasyc Laboratory, CNRS, University of Technology of Compi`egne.
+BP 20529, 60205 COMPIEGNE Cedex, FRANCE.
+E-mail:"
+7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22,Labeled Faces in the Wild: A Survey,"Labeled Faces in the Wild: A Survey
+Erik Learned-Miller, Gary Huang, Aruni RoyChowdhury, Haoxiang Li, Gang Hua"
+7d73adcee255469aadc5e926066f71c93f51a1a5,Face alignment by deep convolutional network with adaptive learning rate,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE
+ICASSP 2016"
+7d9fe410f24142d2057695ee1d6015fb1d347d4a,Facial Expression Feature Extraction Based on FastLBP,"Facial Expression Feature Extraction Based on
+FastLBP
+Computer and Information Engineering Department of Beijing Technology and Business University, Beijing, China
+Ya Zheng
+Email:
+Computer and Information Engineering Department of Beijing Technology and Business University, Beijing, China
+Email:
+Xiuxin Chen, Chongchong Yu and Cheng Gao
+facial  expression"
+7dffe7498c67e9451db2d04bb8408f376ae86992,LEAR-INRIA submission for the THUMOS workshop,"LEAR-INRIA submission for the THUMOS workshop
+Heng Wang and Cordelia Schmid
+LEAR, INRIA, France"
+7d3f6dd220bec883a44596ddec9b1f0ed4f6aca2,Linear Regression for Face Recognition,"Linear Regression for Face Recognition
+Imran Naseem,
+Roberto Togneri, Senior Member, IEEE, and
+Mohammed Bennamoun"
+29ce6b54a87432dc8371f3761a9568eb3c5593b0,Age Sensitivity of Face Recognition Algorithms,"Kent Academic Repository
+Full text document (pdf)
+Citation for published version
+Yassin, DK H. PHM and Hoque, Sanaul and Deravi, Farzin  (2013) Age Sensitivity of Face Recognition
+pp. 12-15.
+https://doi.org/10.1109/EST.2013.8
+Link to record in KAR
+http://kar.kent.ac.uk/43222/
+Document Version
+Author's Accepted Manuscript
+Copyright & reuse
+Content in the Kent Academic Repository is made available for research purposes. Unless otherwise stated all
+ontent is protected by copyright and in the absence of an open licence (eg Creative Commons), permissions
+for further reuse of content should be sought from the publisher, author or other copyright holder.
+Versions of research
+The version in the Kent Academic Repository may differ from the final published version.
+Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the
+published version of record.
+Enquiries
+For any further enquiries regarding the licence status of this document, please contact:"
+292eba47ef77495d2613373642b8372d03f7062b,Deep Secure Encoding: An Application to Face Recognition,"Deep Secure Encoding: An Application to Face Recognition
+Rohit Pandey
+Yingbo Zhou
+Venu Govindaraju"
+29e96ec163cb12cd5bd33bdf3d32181c136abaf9,Regularized Locality Preserving Projections with Two-Dimensional Discretized Laplacian Smoothing,"Report No. UIUCDCS-R-2006-2748
+UILU-ENG-2006-1788
+Regularized Locality Preserving Projections with Two-Dimensional
+Discretized Laplacian Smoothing
+Deng Cai, Xiaofei He, and Jiawei Han
+July 2006"
+29e793271370c1f9f5ac03d7b1e70d1efa10577c,Face Recognition Based on Multi-classifierWeighted Optimization and Sparse Representation,"International Journal of Signal Processing, Image Processing and Pattern Recognition
+Vol.6, No.5 (2013), pp.423-436
+http://dx.doi.org/10.14257/ijsip.2013.6.5.37
+Face Recognition Based on Multi-classifierWeighted Optimization
+nd Sparse Representation
+Deng Nan1, Zhengguang Xu2 and ShengQin Bian3
+,2,3Institute of control science and engineering,
+University of Science and Technology Beijing
+,2,330 Xueyuan Road, Haidian District, Beijing 100083 P. R.China"
+29c7dfbbba7a74e9aafb6a6919629b0a7f576530,Automatic Facial Expression Analysis and Emotional Classification,"Automatic Facial Expression Analysis and Emotional
+Classiﬁcation
+Robert Fischer
+Submitted to the Department of Math and Natural Sciences
+in partial fulﬁllment of the requirements for the degree of a
+Diplomingenieur der Optotechnik und Bildverarbeitung (FH)
+(Diplom Engineer of Photonics and Image Processing)
+t the
+UNIVERSITY OF APPLIED SCIENCE DARMSTADT (FHD)
+Accomplished and written at the
+MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT)
+October 2004
+Author . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
+Department of Math and Natural Sciences
+October 30, 2004
+Certiﬁed by . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
+Dr. Harald Scharfenberg
+Professor at FHD
+Thesis Supervisor
+Accepted by . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ."
+294d1fa4e1315e1cf7cc50be2370d24cc6363a41,A modular non-negative matrix factorization for parts-based object recognition using subspace representation,"008 SPIE Digital Library -- Subscriber Archive Copy
+Processing: Machine Vision Applications, edited by Kurt S. Niel, David Fofi, Proc. of SPIE-IS&T Electronic Imaging, SPIE Vol. 6813, 68130C, © 2008 SPIE-IS&T · 0277-786X/08/$18SPIE-IS&T/ Vol. 6813  68130C-1"
+29d414bfde0dfb1478b2bdf67617597dd2d57fc6,Perfect histogram matching PCA for face recognition,"Multidim Syst Sign Process (2010) 21:213–229
+DOI 10.1007/s11045-009-0099-y
+Perfect histogram matching PCA for face recognition
+Ana-Maria Sevcenco · Wu-Sheng Lu
+Received: 10 August 2009 / Revised: 21 November 2009 / Accepted: 29 December 2009 /
+Published online: 14 January 2010
+© Springer Science+Business Media, LLC 2010"
+290136947fd44879d914085ee51d8a4f433765fa,On a taxonomy of facial features,"On a Taxonomy of Facial Features
+Brendan Klare and Anil K. Jain"
+2957715e96a18dbb5ed5c36b92050ec375214aa6,InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender Diversity,"Improving Face Attribute Detection with Race and Gender Diversity
+InclusiveFaceNet:
+Hee Jung Ryu 1 Hartwig Adam * 1 Margaret Mitchell * 1"
+2965d092ed72822432c547830fa557794ae7e27b,Improving Representation and Classification of Image and Video Data for Surveillance Applications,"Improving Representation and Classiﬁcation of Image and
+Video Data for Surveillance Applications
+Andres Sanin
+BSc(Biol), MSc(Biol), MSc(CompSc)
+A thesis submitted for the degree of Doctor of Philosophy at
+The University of Queensland in 2012
+School of Information Technology and Electrical Engineering"
+2921719b57544cfe5d0a1614d5ae81710ba804fa,Face Recognition Enhancement Based on Image File Formats and Wavelet De - noising,"Face Recognition Enhancement Based on Image
+File Formats and Wavelet De-noising
+Isra’a Abdul-Ameer Abdul-Jabbar, Jieqing Tan, and Zhengfeng Hou"
+29a013b2faace976f2c532533bd6ab4178ccd348,Hierarchical Manifold Learning With Applications to Supervised Classification for High-Resolution Remotely Sensed Images,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
+Hierarchical Manifold Learning With Applications
+to Supervised Classiﬁcation for High-Resolution
+Remotely Sensed Images
+Hong-Bing Huang, Hong Huo, and Tao Fang"
+29756b6b16d7b06ea211f21cdaeacad94533e8b4,Thresholding Approach based on GPU for Facial Expression Recognition,"Thresholding Approach based on GPU for Facial
+Expression Recognition
+Jesús García-Ramírez1, J. Arturo Olvera-López1, Ivan Olmos-Pineda1, Georgina
+Flores-Becerra2, Adolfo Aguilar-Rico2
+Benemérita Universidad Autónoma de Puebla, Faculty of Computer Science, Puebla, México
+Instituto Tecnológico de Puebla, Puebla, México"
+293193d24d5c4d2975e836034bbb2329b71c4fe7,Building a Corpus of Facial Expressions for Learning-Centered Emotions,"Building a Corpus of Facial Expressions
+for Learning-Centered Emotions
+María Lucía Barrón-Estrada, Ramón Zatarain-Cabada,
+Bianca Giovanna Aispuro-Medina, Elvia Minerva Valencia-Rodríguez,
+Ana Cecilia Lara-Barrera
+Instituto Tecnológico de Culiacán, Culiacán, Sinaloa,
+Mexico
+{lbarron, rzatarain, m06170904, m95170906, m15171452}"
+294bd7eb5dc24052237669cdd7b4675144e22306,Automatic Face Annotation,"International Journal of Science and Research (IJSR)
+ISSN (Online): 2319-7064
+Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438
+Automatic Face Annotation
+Ashna Shajahan
+M.Tech Student, Dept. of Computer Science & Engineering, Mount Zion College of Engineering, Pathanamthitta, Kerala, India"
+2988f24908e912259d7a34c84b0edaf7ea50e2b3,A Model of Brightness Variations Due to Illumination Changes and Non-rigid Motion Using Spherical Harmonics,"A Model of Brightness Variations Due to
+Illumination Changes and Non-rigid Motion
+Using Spherical Harmonics
+Jos´e M. Buenaposada
+Alessio Del Bue
+Dep. Ciencias de la Computaci´on,
+U. Rey Juan Carlos, Spain
+http://www.dia.fi.upm.es/~pcr
+Inst. for Systems and Robotics
+Inst. Superior T´ecnico, Portugal
+http://www.isr.ist.utl.pt/~adb
+Enrique Mu˜noz
+Facultad de Inform´atica,
+U. Complutense de Madrid, Spain
+Luis Baumela
+Dep. de Inteligencia Artiﬁcial,
+U. Polit´ecnica de Madrid, Spain
+http://www.dia.fi.upm.es/~pcr
+http://www.dia.fi.upm.es/~pcr"
+7cee802e083c5e1731ee50e731f23c9b12da7d36,2^B3^C: 2 Box 3 Crop of Facial Image for Gender Classification with Convolutional Networks,"B3C: 2 Box 3 Crop of Facial Image for Gender Classification with Convolutional
+Networks
+Vandit Gajjar
+Department of Electronics and Communication Engineering and
+Computer Vision Group, L. D. College of Engineering, Ahmedabad, India"
+7c47da191f935811f269f9ba3c59556c48282e80,Robust eye centers localization with zero-crossing encoded image projections,"Robust Eye Centers Localization
+with Zero–Crossing Encoded Image Projections
+Laura Florea
+Image Processing and Analysis Laboratory
+University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313
+Corneliu Florea
+Image Processing and Analysis Laboratory
+University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313
+Constantin Vertan
+Image Processing and Analysis Laboratory
+University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313"
+7c45b5824645ba6d96beec17ca8ecfb22dfcdd7f,News Image Annotation on a Large Parallel Text-image Corpus,"News image annotation on a large parallel text-image corpus
+Pierre Tirilly, Vincent Claveau, Patrick Gros
+Universit´e de Rennes 1/IRISA, CNRS/IRISA, INRIA Rennes-Bretagne Atlantique
+Campus de Beaulieu
+5042 Rennes Cedex, France"
+7c0a6824b556696ad7bdc6623d742687655852db,MPCA+MDA: A novel approach for face recognition based on tensor objects,"8th Telecommunications forum TELFOR 2010
+Serbia, Belgrade, November 23-25, 2010.
+MPCA+DATER: A Novel Approach for Face
+Recognition Based on Tensor Objects
+Ali. A. Shams Baboli, Member, IEEE, G. Rezai-rad, Member, IEEE, Aref. Shams Baboli"
+7c95449a5712aac7e8c9a66d131f83a038bb7caa,This is an author produced version of Facial first impressions from another angle: How social judgements are influenced by changeable and invariant facial properties. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/102935/,"This is an author produced version of Facial first impressions from another angle: How
+social judgements are influenced by changeable and invariant facial properties.
+White Rose Research Online URL for this paper:
+http://eprints.whiterose.ac.uk/102935/
+Article:
+Sutherland, Clare, Young, Andrew William orcid.org/0000-0002-1202-6297 and Gillian,
+Rhodes (2017) Facial first impressions from another angle: How social judgements are
+influenced by changeable and invariant facial properties. British journal of psychology. pp.
+97-415. ISSN 0007-1269
+https://doi.org/10.1111/bjop.12206
+promoting access to
+White Rose research papers
+http://eprints.whiterose.ac.uk/"
+7c3e09e0bd992d3f4670ffacb4ec3a911141c51f,Transferring Object-Scene Convolutional Neural Networks for Event Recognition in Still Images,"Noname manuscript No.
+(will be inserted by the editor)
+Transferring Object-Scene Convolutional Neural Networks for
+Event Recognition in Still Images
+Limin Wang · Zhe Wang · Yu Qiao · Luc Van Gool
+Received: date / Accepted: date"
+7c7b0550ec41e97fcfc635feffe2e53624471c59,"Head, Eye, and Hand Patterns for Driver Activity Recognition","051-4651/14 $31.00 © 2014 IEEE
+DOI 10.1109/ICPR.2014.124"
+7c119e6bdada2882baca232da76c35ae9b5277f8,Facial expression recognition using embedded Hidden Markov Model,"Facial Expression Recognition Using Embedded
+Hidden Markov Model
+Languang He, Xuan Wang, Member, IEEE, Chenglong Yu, Member, IEEE, Kun Wu
+Intelligence Computing Research Center
+HIT Shenzhen Graduate School
+Shenzhen, China
+{telent, wangxuan, ycl, wukun}"
+7c9a65f18f7feb473e993077d087d4806578214e,SpringerLink - Zeitschriftenbeitrag,"SpringerLink - Zeitschriftenbeitrag
+http://www.springerlink.com/content/93hr862660nl1164/?p=abe5352...
+Deutsch
+Deutsch
+Vorherige Beitrag    Nächste Beitrag
+Beitrag markieren
+In den Warenkorb legen
+Zu gespeicherten Artikeln
+hinzufügen
+Permissions & Reprints
+Diesen Artikel empfehlen
+Ergebnisse
+finden
+Erweiterte Suche
+im gesamten Inhalt
+in dieser Zeitschrift
+in diesem Heft
+Diesen Beitrag exportieren
+Diesen Beitrag exportieren als RIS
+| Text"
+7c1e1c767f7911a390d49bed4f73952df8445936,Non-Rigid Object Detection with LocalInterleaved Sequential Alignment (LISA),"NON-RIGID OBJECT DETECTION WITH LOCAL INTERLEAVED SEQUENTIAL ALIGNMENT (LISA)
+Non-Rigid Object Detection with Local
+Interleaved Sequential Alignment (LISA)
+Karel Zimmermann, Member, IEEE,, David Hurych, Member, IEEE,
+nd Tom´aˇs Svoboda, Member, IEEE"
+7cf579088e0456d04b531da385002825ca6314e2,Emotion Detection on TV Show Transcripts with Sequence-based Convolutional Neural Networks,"Emotion Detection on TV Show Transcripts with
+Sequence-based Convolutional Neural Networks
+Sayyed M. Zahiri
+Jinho D. Choi
+Mathematics and Computer Science
+Mathematics and Computer Science
+Emory University
+Atlanta, GA 30322, USA
+Emory University
+Atlanta, GA 30322, USA"
+7c349932a3d083466da58ab1674129600b12b81c,Leveraging Multiple Features for Image Retrieval and Matching,
+1648cf24c042122af2f429641ba9599a2187d605,Boosting cross-age face verification via generative age normalization,"Boosting Cross-Age Face Veriﬁcation via Generative Age Normalization
+Grigory Antipov(cid:2)†
+Jean-Luc Dugelay†
+(cid:2) Orange Labs, 4 rue Clos Courtel, 35512 Cesson-S´evign´e, France
+Moez Baccouche(cid:2)
+Eurecom, 450 route des Chappes, 06410 Biot, France"
+162403e189d1b8463952fa4f18a291241275c354,Action Recognition with Spatio-Temporal Visual Attention on Skeleton Image Sequences,"Action Recognition with Spatio-Temporal
+Visual Attention on Skeleton Image Sequences
+Zhengyuan Yang, Student Member, IEEE, Yuncheng Li, Jianchao Yang, Member, IEEE,
+nd Jiebo Luo, Fellow, IEEE
+With a strong ability of modeling sequential data, Recur-
+rent Neural Networks (RNN) with Long Short-Term Memory
+(LSTM) neurons outperform the previous hand-crafted feature
+ased methods [9], [10]. Each skeleton frame is converted into
+feature vector and the whole sequence is fed into the RNN.
+Despite the strong ability in modeling temporal sequences,
+RNN structures lack the ability to efﬁciently learn the spatial
+relations between the joints. To better use spatial information,
+hierarchical structure is proposed in [11], [12] that feeds
+the joints into the network as several pre-deﬁned body part
+groups. However,
+limit
+the effectiveness of representing spatial relations. A spatio-
+temporal 2D LSTM (ST-LSTM) network [13] is proposed
+to learn the spatial and temporal relations simultaneously.
+Furthermore, a two-stream RNN structure [14] is proposed to"
+160259f98a6ec4ec3e3557de5e6ac5fa7f2e7f2b,Discriminant multi-label manifold embedding for facial Action Unit detection,"Discriminant Multi-Label Manifold Embedding for Facial Action Unit
+Detection
+Signal Procesing Laboratory (LTS5), ´Ecole Polytechnique F´ed´erale de Lausanne, Switzerland
+Anıl Y¨uce, Hua Gao and Jean-Philippe Thiran"
+16671b2dc89367ce4ed2a9c241246a0cec9ec10e,Detecting the Number of Clusters in n-Way Probabilistic Clustering,"Detecting the Number of Clusters
+in n-Way Probabilistic Clustering
+Zhaoshui He, Andrzej Cichocki, Senior Member, IEEE,
+Shengli Xie, Senior Member, IEEE, and Kyuwan Choi"
+16395b40e19cbc6d5b82543039ffff2a06363845,Action Recognition in Video Using Sparse Coding and Relative Features,"Action Recognition in Video Using Sparse Coding and Relative Features
+Anal´ı Alfaro
+Domingo Mery
+Alvaro Soto
+P. Universidad Catolica de Chile
+P. Universidad Catolica de Chile
+P. Universidad Catolica de Chile
+Santiago, Chile
+Santiago, Chile
+Santiago, Chile"
+16b9d258547f1eccdb32111c9f45e2e4bbee79af,NormFace: L2 Hypersphere Embedding for Face Verification,"006 Xiyuan Ave.
+Chengdu, Sichuan 611731
+Jian Cheng
+006 Xiyuan Ave.
+Chengdu, Sichuan 611731
+University of Electronic Science and Technology of China
+Xiang Xiang
+Johns Hopkins University
+400 N. Charles St.
+Baltimore, Maryland 21218
+Alan L. Yuille
+Johns Hopkins University
+400 N. Charles St.
+Baltimore, Maryland 21218
+NormFace: L2 Hypersphere Embedding for Face Verification
+University of Electronic Science and Technology of China
+Feng Wang∗"
+16c884be18016cc07aec0ef7e914622a1a9fb59d,Exploiting Multimodal Data for Image Understanding,"UNIVERSITÉ DE GRENOBLE
+No attribué par la bibliothèque
+THÈSE
+pour obtenir le grade de
+DOCTEUR DE L’UNIVERSITÉ DE GRENOBLE
+Spécialité : Mathématiques et Informatique
+préparée au Laboratoire Jean Kuntzmann
+dans le cadre de l’École Doctorale Mathématiques,
+Sciences et Technologies de l’Information, Informatique
+présentée et soutenue publiquement
+Matthieu Guillaumin
+le 27 septembre 2010
+Exploiting Multimodal Data for Image Understanding
+Données multimodales pour l’analyse d’image
+Directeurs de thèse : Cordelia Schmid et Jakob Verbeek
+M. Éric Gaussier
+M. Antonio Torralba
+Mme Tinne Tuytelaars Katholieke Universiteit Leuven
+M. Mark Everingham University of Leeds
+Mme Cordelia Schmid"
+1630e839bc23811e340bdadad3c55b6723db361d,Exploiting relationship between attributes for improved face verification,"SONG, TAN, CHEN: EXPLOITING RELATIONSHIP BETWEEN ATTRIBUTES
+Exploiting Relationship between Attributes for
+Improved Face Veriﬁcation
+Fengyi Song
+Xiaoyang Tan
+Songcan Chen
+Department of Computer Science and
+Technology, Nanjing University of Aero-
+nautics and Astronautics, Nanjing 210016,
+P.R. China"
+16286fb0f14f6a7a1acc10fcd28b3ac43f12f3eb,"All Smiles are Not Created Equal: Morphology and Timing of Smiles Perceived as Amused, Polite, and Embarrassed/Nervous.","J Nonverbal Behav
+DOI 10.1007/s10919-008-0059-5
+O R I G I N A L P A P E R
+All Smiles are Not Created Equal: Morphology
+nd Timing of Smiles Perceived as Amused, Polite,
+nd Embarrassed/Nervous
+Zara Ambadar Æ Jeffrey F. Cohn Æ Lawrence Ian Reed
+Ó Springer Science+Business Media, LLC 2008"
+166186e551b75c9b5adcc9218f0727b73f5de899,Automatic Age and Gender Recognition in Human Face Image Dataset using Convolutional Neural Network System,"Volume 4, Issue 2, February 2016
+International Journal of Advance Research in
+Computer Science and Management Studies
+Research Article / Survey Paper / Case Study
+Available online at: www.ijarcsms.com
+ISSN: 2321-7782 (Online)
+Automatic Age and Gender Recognition in Human Face Image
+Dataset using Convolutional Neural Network System
+Subhani Shaik1
+Assoc. Prof & Head of the Department
+Department of CSE,
+Anto A. Micheal2
+Associate Professor
+Department of CSE,
+St.Mary’s Group of Institutions Guntur
+St.Mary’s Group of Institutions Guntur
+Chebrolu(V&M),Guntur(Dt),
+Andhra Pradesh - India
+Chebrolu(V&M),Guntur(Dt),
+Andhra Pradesh - India"
+16d9b983796ffcd151bdb8e75fc7eb2e31230809,GazeDirector: Fully Articulated Eye Gaze Redirection in Video,"EUROGRAPHICS 2018 / D. Gutierrez and A. Sheffer
+(Guest Editors)
+Volume 37 (2018), Number 2
+GazeDirector: Fully Articulated Eye Gaze Redirection in Video
+ID: paper1004"
+162c33a2ec8ece0dc96e42d5a86dc3fedcf8cd5e,Large-Scale Classification by an Approximate Least Squares One-Class Support Vector Machine Ensemble,"Mygdalis, V., Iosifidis, A., Tefas, A., & Pitas, I. (2016). Large-Scale
+Classification by an Approximate Least Squares One-Class Support Vector
+of a meeting held 20-22 August 2015, Helsinki, Finland (Vol. 2, pp. 6-10).
+Institute of Electrical and Electronics Engineers (IEEE). DOI:
+0.1109/Trustcom.2015.555
+Peer reviewed version
+Link to published version (if available):
+0.1109/Trustcom.2015.555
+Link to publication record in Explore Bristol Research
+PDF-document
+University of Bristol - Explore Bristol Research
+General rights
+This document is made available in accordance with publisher policies. Please cite only the published
+version using the reference above. Full terms of use are available:
+http://www.bristol.ac.uk/pure/about/ebr-terms"
+161eb88031f382e6a1d630cd9a1b9c4bc6b47652,Automatic facial expression recognition using features of salient facial patches,"Automatic Facial Expression Recognition
+Using Features of Salient Facial Patches
+S L Happy and Aurobinda Routray"
+4209783b0cab1f22341f0600eed4512155b1dee6,Accurate and Efficient Similarity Search for Large Scale Face Recognition,"Accurate and Efﬁcient Similarity Search for Large Scale Face Recognition
+Ce Qi
+Zhizhong Liu
+Fei Su"
+42e3dac0df30d754c7c7dab9e1bb94990034a90d,PANDA: Pose Aligned Networks for Deep Attribute Modeling,"PANDA: Pose Aligned Networks for Deep Attribute Modeling
+Ning Zhang1,2, Manohar Paluri1, Marc’Aurelio Ranzato1, Trevor Darrell2, Lubomir Bourdev1
+EECS, UC Berkeley
+{mano, ranzato,
+Facebook AI Research
+{nzhang,"
+42cc9ea3da1277b1f19dff3d8007c6cbc0bb9830,Coordinated Local Metric Learning,"Coordinated Local Metric Learning
+Shreyas Saxena
+Jakob Verbeek
+Inria∗"
+42350e28d11e33641775bef4c7b41a2c3437e4fd,Multilinear Discriminant Analysis for Face Recognition,"Multilinear Discriminant Analysis
+for Face Recognition
+Shuicheng Yan, Member, IEEE, Dong Xu, Qiang Yang, Senior Member, IEEE, Lei Zhang, Member, IEEE,
+Xiaoou Tang, Senior Member, IEEE, and Hong-Jiang Zhang, Fellow, IEEE"
+42e155ea109eae773dadf74d713485be83fca105,Sparse reconstruction of facial expressions with localized gabor moments,
+4270460b8bc5299bd6eaf821d5685c6442ea179a,"Partial Similarity of Objects, or How to Compare a Centaur to a Horse","Int J Comput Vis (2009) 84: 163–183
+DOI 10.1007/s11263-008-0147-3
+Partial Similarity of Objects, or How to Compare a Centaur
+to a Horse
+Alexander M. Bronstein · Michael M. Bronstein · Alfred
+M. Bruckstein · Ron Kimmel
+Received: 30 September 2007 / Accepted: 3 June 2008 / Published online: 26 July 2008
+© Springer Science+Business Media, LLC 2008"
+429d4848d03d2243cc6a1b03695406a6de1a7abd,"Face Recognition based on Logarithmic Fusion of SVD and KT Ramachandra A C , Raja K B , Venugopal K R , L M Patnaik","Face Recognition based on Logarithmic Fusion
+International Journal of Soft Computing and Engineering (IJSCE)
+ISSN: 2231-2307, Volume-2, Issue-3, July 2012
+of SVD and KT
+Ramachandra A C, Raja K B, Venugopal K R, L M Patnaik"
+42dc36550912bc40f7faa195c60ff6ffc04e7cd6,Visible and Infrared Face Identification via Sparse Representation,"Hindawi Publishing Corporation
+ISRN Machine Vision
+Volume 2013, Article ID 579126, 10 pages
+http://dx.doi.org/10.1155/2013/579126
+Research Article
+Visible and Infrared Face Identification via
+Sparse Representation
+Pierre Buyssens1 and Marinette Revenu2
+LITIS EA 4108-QuantIF Team, University of Rouen, 22 Boulevard Gambetta, 76183 Rouen Cedex, France
+GREYC UMR CNRS 6072 ENSICAEN-Image Team, University of Caen Basse-Normandie, 6 Boulevard Mar´echal Juin,
+4050 Caen, France
+Correspondence should be addressed to Pierre Buyssens;
+Received 4 April 2013; Accepted 27 April 2013
+Academic Editors: O. Ghita, D. Hernandez, Z. Hou, M. La Cascia, and J. M. Tavares
+Copyright © 2013 P. Buyssens and M. Revenu. This is an open access article distributed under the Creative Commons Attribution
+License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
+ited.
+We present a facial recognition technique based on facial sparse representation. A dictionary is learned from data, and patches
+extracted from a face are decomposed in a sparse manner onto this dictionary. We particularly focus on the design of dictionaries
+that play a crucial role in the final identification rates. Applied to various databases and modalities, we show that this approach"
+42ecfc3221c2e1377e6ff849afb705ecd056b6ff,Pose Invariant Face Recognition Under Arbitrary Unknown Lighting Using Spherical Harmonics,"Pose Invariant Face Recognition under Arbitrary
+Unknown Lighting using Spherical Harmonics
+Lei Zhang and Dimitris Samaras
+Department of Computer Science,
+SUNY at Stony Brook, NY, 11790
+{lzhang,"
+421955c6d2f7a5ffafaf154a329a525e21bbd6d3,Evolutionary Pursuit and Its Application to Face Recognition,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 22, NO. 6,
+JUNE 2000
+Evolutionary Pursuit and Its
+Application to Face Recognition
+Chengjun Liu, Member, IEEE, and Harry Wechsler, Fellow, IEEE"
+42df75080e14d32332b39ee5d91e83da8a914e34,Illumination Compensation Using Oriented Local Histogram Equalization and its Application to Face Recognition,"Illumination Compensation Using Oriented
+Local Histogram Equalization and
+Its Application to Face Recognition
+Ping-Han Lee, Szu-Wei Wu, and Yi-Ping Hung"
+89945b7cd614310ebae05b8deed0533a9998d212,Divide-and-Conquer Method for L1 Norm Matrix Factorization in the Presence of Outliers and Missing Data,"Divide-and-Conquer Method for L1 Norm Matrix
+Factorization in the Presence of Outliers and
+Missing Data
+Deyu Meng and Zongben Xu"
+89c84628b6f63554eec13830851a5d03d740261a,Image Enhancement and Automated Target Recognition Techniques for Underwater Electro-Optic Imagery,"Image Enhancement and Automated Target Recognition
+Techniques for Underwater Electro-Optic Imagery
+Thomas Giddings (PI), Cetin Savkli and Joseph Shirron
+Metron, Inc.
+1911 Freedom Dr., Suite 800
+Reston, VA 20190
+phone: (703) 437-2428   fax: (703) 787-3518    email:
+Contract Number N00014-07-C-0351
+http:www.metsci.com
+LONG TERM GOALS
+The long-term goal of this project is to provide a flexible, accurate and extensible automated target
+recognition (ATR) system for use with a variety of imaging and non-imaging sensors.  Such an ATR
+system, once it achieves a high level of performance, can relieve human operators from the tedious
+usiness of pouring over vast quantities of mostly mundane data, calling the operator in only when the
+omputer assessment involves an unacceptable level of  ambiguity. The ATR system will provide most
+leading edge algorithms for detection, segmentation, and classification while incorporating many novel
+lgorithms that we are developing at Metron.  To address one of the most critical challenges in ATR
+technology, the system will also provide powerful feature extraction routines designed for specific
+pplications of current interest.
+OBJECTIVES"
+89c51f73ec5ebd1c2a9000123deaf628acf3cdd8,Face Recognition Based on Nonlinear Feature Approach Eimad,"American Journal of Applied Sciences 5 (5): 574-580, 2008
+ISSN 1546-9239
+© 2008 Science Publications
+Face Recognition Based on Nonlinear Feature Approach
+Eimad E.A. Abusham, 1Andrew T.B. Jin, 1Wong E. Kiong and 2G. Debashis
+Faculty of Information Science and Technology,
+Faculty of Engineering and Technology, Multimedia University (Melaka Campus),
+Jalan Ayer Keroh Lama, 75450 Bukit Beruang, Melaka, Malaysia"
+89c73b1e7c9b5e126a26ed5b7caccd7cd30ab199,Application of an Improved Mean Shift Algorithm in Real-time Facial Expression Recognition,"Application of an Improved Mean Shift Algorithm
+in Real-time Facial Expression Recognition
+School of Computer and Communication, Hunan University of Technology, Hunan, Zhuzhou, 412008，china
+School of Electrical and Information Engineering, Hunan University of Technology, Hunan, Zhuzhou, 412008，china
+School of Computer and Communication, Hunan University of Technology, Hunan, Zhuzhou, 412008，china
+Zhao-yi PENG
+Yu ZHOU
+Yan-hui  ZHU
+Email:
+Zhi-qiang WEN
+Email:
+School of Computer and Communication, Hunan University of Technology, Hunan, Zhuzhou, 412008，china
+facial
+real-time
+expression"
+893239f17dc2d17183410d8a98b0440d98fa2679,UvA-DARE ( Digital Academic Repository ) Expression-Invariant Age Estimation,"UvA-DARE (Digital Academic Repository)
+Expression-Invariant Age Estimation
+Alnajar, F.; Lou, Z.; Alvarez Lopez, J.M.; Gevers, T.
+Published in:
+Proceedings of the British Machine Vision Conference 2014
+0.5244/C.28.14
+Link to publication
+Citation for published version (APA):
+Alnajar, F., Lou, Z., Alvarez, J., & Gevers, T. (2014). Expression-Invariant Age Estimation. In M. Valstar, A.
+French, & T. Pridmore (Eds.), Proceedings of the British Machine Vision Conference 2014 (pp. 14.1-14.11).
+BMVA Press. DOI: 10.5244/C.28.14
+General rights
+It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s),
+other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons).
+Disclaimer/Complaints regulations
+If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating
+your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask
+the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam,
+The Netherlands. You will be contacted as soon as possible.
+Download date: 04 Aug 2017"
+8913a5b7ed91c5f6dec95349fbc6919deee4fc75,BigBIRD: A large-scale 3D database of object instances,"BigBIRD: A Large-Scale 3D Database of Object Instances
+Arjun Singh, James Sha, Karthik S. Narayan, Tudor Achim, Pieter Abbeel"
+89d3a57f663976a9ac5e9cdad01267c1fc1a7e06,Neural Class-Specific Regression for face verification,"Neural Class-Speciﬁc Regression for face
+veriﬁcation
+Guanqun Cao, Alexandros Iosiﬁdis, Moncef Gabbouj"
+89bc311df99ad0127383a9149d1684dfd8a5aa34,Towards ontology driven learning of visual concept detectors,"Towards ontology driven learning of
+visual concept detectors
+Sanchit ARORA, Chuck CHO, Paul FITZPATRICK, Franc¸ois SCHARFFE 1
+Dextro Robotics, Inc. 101 Avenue of the Americas, New York, USA"
+898a66979c7e8b53a10fd58ac51fbfdb6e6e6e7c,Dynamic vs. Static Recognition of Facial Expressions,"Dynamic vs. Static Recognition of Facial
+Expressions
+No Author Given
+No Institute Given"
+89d7cc9bbcd2fdc4f4434d153ecb83764242227b,Face-Name Graph Matching For The Personalities In Movie Screen,"Einstein.J, DivyaBaskaran / International Journal of Engineering Research and Applications
+(IJERA)             ISSN: 2248-9622           www.ijera.com
+Vol. 3, Issue 2, March -April 2013, pp.351-355
+Face-Name Graph Matching For The Personalities In Movie
+Screen
+*(Asst. Professor, Dept. of IT, VelTech HighTech Dr. Rangarajan Dr.Sakunthala Engineering College,
+Einstein.J*, DivyaBaskaran**
+** (Final Year Student, M.Tech IT, Vel Tech Dr. RR &Dr. SR Technical University, Chennai.)
+Chennai.)"
+891b10c4b3b92ca30c9b93170ec9abd71f6099c4,2 New Statement for Structured Output Regression Problems,"Facial landmark detection using structured output deep
+neural networks
+Souﬁane Belharbi ∗1, Cl´ement Chatelain∗1, Romain H´erault∗1, and S´ebastien
+Adam∗2
+LITIS EA 4108, INSA de Rouen, Saint ´Etienne du Rouvray 76800, France
+LITIS EA 4108, UFR des Sciences, Universit´e de Rouen, France.
+September 24, 2015"
+45c340c8e79077a5340387cfff8ed7615efa20fd,Assessment of the Emotional States of Students during e-Learning,
+45e7ddd5248977ba8ec61be111db912a4387d62f,Adversarial Learning of Structure-Aware Fully Convolutional Networks for Landmark Localization,"CHEN ET AL.: ADVERSARIAL POSENET
+Adversarial Learning of Structure-Aware Fully
+Convolutional Networks for Landmark
+Localization
+Yu Chen1, Chunhua Shen2, Hao Chen2, Xiu-Shen Wei3, Lingqiao Liu2 and Jian Yang1"
+4526992d4de4da2c5fae7a5ceaad6b65441adf9d,System for Medical Mask Detection in the Operating Room Through Facial Attributes,"System for Medical Mask Detection
+in the Operating Room Through
+Facial Attributes
+A. Nieto-Rodr´ıguez, M. Mucientes(B), and V.M. Brea
+Center for Research in Information Technologies (CiTIUS),
+University of Santiago de Compostela, Santiago de Compostela, Spain"
+45efd6c2dd4ca19eed38ceeb7c2c5568231451e1,Comparative Analysis of Statistical Approach for Face Recognition,"Comparative Analysis of Statistical Approach
+for Face Recognition
+S.Pradnya1, M.Riyajoddin2, M.Janga Reddy3
+CMR Institute of Technology, Hyderabad, (India)"
+4560491820e0ee49736aea9b81d57c3939a69e12,Investigating the Impact of Data Volume and Domain Similarity on Transfer Learning Applications,"Investigating the Impact of Data Volume and
+Domain Similarity on Transfer Learning
+Applications
+Michael Bernico, Yuntao Li, and Dingchao Zhang
+State Farm Insurance, Bloomington IL 61710, USA,"
+4571626d4d71c0d11928eb99a3c8b10955a74afe,Geometry Guided Adversarial Facial Expression Synthesis,"Geometry Guided Adversarial Facial Expression Synthesis
+Lingxiao Song1,2
+Zhihe Lu1,3 Ran He1,2,3
+Zhenan Sun1,2
+Tieniu Tan1,2,3
+National Laboratory of Pattern Recognition, CASIA
+Center for Research on Intelligent Perception and Computing, CASIA
+Center for Excellence in Brain Science and Intelligence Technology, CAS"
+4534d78f8beb8aad409f7bfcd857ec7f19247715,Transformation-Based Models of Video Sequences,"Under review as a conference paper at ICLR 2017
+TRANSFORMATION-BASED MODELS OF VIDEO
+SEQUENCES
+Joost van Amersfoort ∗, Anitha Kannan, Marc’Aurelio Ranzato,
+Arthur Szlam, Du Tran & Soumith Chintala
+Facebook AI Research
+{akannan, ranzato, aszlam, trandu,"
+459e840ec58ef5ffcee60f49a94424eb503e8982,One-shot Face Recognition by Promoting Underrepresented Classes,"One-shot Face Recognition by Promoting Underrepresented Classes
+Yandong Guo, Lei Zhang
+Microsoft
+One Microsoft Way, Redmond, Washington, United States
+{yandong.guo,"
+451c42da244edcb1088e3c09d0f14c064ed9077e,Using subclasses in discriminant non-negative subspace learning for facial expression recognition,"© EURASIP, 2011  -  ISSN 2076-1465
+9th European Signal Processing Conference (EUSIPCO 2011)
+INTRODUCTION"
+4568063b7efb66801e67856b3f572069e774ad33,Correspondence driven adaptation for human profile recognition,"Correspondence Driven Adaptation for Human Proﬁle Recognition
+Ming Yang1, Shenghuo Zhu1, Fengjun Lv2, Kai Yu1
+NEC Laboratories America, Inc.
+Huawei Technologies (USA)
+Cupertino, CA 95014
+Santa Clara, CA 95050"
+45e459462a80af03e1bb51a178648c10c4250925,LCrowdV: Generating Labeled Videos for Simulation-based Crowd Behavior Learning,"LCrowdV: Generating Labeled Videos for
+Simulation-based Crowd Behavior Learning
+Ernest Cheung1, Tsan Kwong Wong1, Aniket Bera1, Xiaogang Wang2, and
+Dinesh Manocha1
+The University of North Carolina at Chapel Hill"
+458677de7910a5455283a2be99f776a834449f61,Face Image Retrieval Using Facial Attributes By K-Means,"Face Image Retrieval Using Facial Attributes By
+K-Means
+[1]I.Sudha,  [2]V.Saradha, [3]M.Tamilselvi, [4]D.Vennila
+[1]AP, Department of CSE ,[2][3][4] B.Tech(CSE)
+Achariya college of Engineering Technology-
+Puducherry"
+45a6333fc701d14aab19f9e2efd59fe7b0e89fec,Dataset Creation for Gesture Recognition,"HAND POSTURE DATASET CREATION FOR GESTURE
+RECOGNITION
+Luis Anton-Canalis
+Instituto de Sistemas Inteligentes y Aplicaciones Numericas en Ingenieria
+Campus Universitario de Taﬁra, 35017 Gran Canaria, Spain
+Elena Sanchez-Nielsen
+Departamento de E.I.O. y Computacion
+8271 Universidad de La Laguna, Spain
+Keywords:
+Image understanding, Gesture recognition, Hand dataset."
+1ffe20eb32dbc4fa85ac7844178937bba97f4bf0,Face Clustering: Representation and Pairwise Constraints,"Face Clustering: Representation and Pairwise
+Constraints
+Yichun Shi, Student Member, IEEE, Charles Otto, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
+1f8304f4b51033d2671147b33bb4e51b9a1e16fe,Beyond Trees: MAP Inference in MRFs via Outer-Planar Decomposition,"Noname manuscript No.
+(will be inserted by the editor)
+Beyond Trees:
+MAP Inference in MRFs via Outer-Planar Decomposition
+Dhruv Batra · Andrew C. Gallagher · Devi Parikh · Tsuhan Chen
+Received: date / Accepted: date"
+1f9ae272bb4151817866511bd970bffb22981a49,An Iterative Regression Approach for Face Pose Estimation from RGB Images,"An Iterative Regression Approach for Face Pose Estima-
+tion from RGB Images
+Wenye He
+This paper presents a iterative optimization method, explicit shape regression, for face pose
+detection and localization. The regression function is learnt to ﬁnd out the entire facial shape
+nd minimize the alignment errors. A cascaded learning framework is employed to enhance
+shape constraint during detection. A combination of a two-level boosted regression, shape
+performance. In this paper, we have explain the advantage of ESR for deformable object like
+face pose estimation and reveal its generic applications of the method. In the experiment,
+we compare the results with different work and demonstrate the accuracy and robustness in
+different scenarios.
+Introduction
+Pose estimation is an important problem in computer vision, and has enabled many practical ap-
+plication from face expression 1 to activity tracking 2. Researchers design a new algorithm called
+explicit shape regression (ESR) to ﬁnd out face alignment from a picture 3. Figure 1 shows how
+the system uses ESR to learn a shape of a human face image. A simple way to identify a face is to
+ﬁnd out facial landmarks like eyes, nose, mouth and chin. The researchers deﬁne a face shape S
+nd S is composed of Nf p facial landmarks. Therefore, they get S = [x1, y1, ..., xNf p, yNf p]T . The
+objective of the researchers is to estimate a shape S of a face image. The way to know the accuracy"
+1fc249ec69b3e23856b42a4e591c59ac60d77118,Evaluation of a 3D-aided pose invariant 2D face recognition system,"Evaluation of a 3D-aided Pose Invariant 2D Face Recognition System
+Xiang Xu, Ha A. Le, Pengfei Dou, Yuhang Wu, Ioannis A. Kakadiaris
+{xxu18, hale4, pdou, ywu35,
+Computational Biomedicine Lab
+800 Calhoun Rd. Houston, TX, USA"
+1fbde67e87890e5d45864e66edb86136fbdbe20e,The Action Similarity Labeling Challenge,"The Action Similarity Labeling Challenge
+Orit Kliper-Gross, Tal Hassner, and
+Lior Wolf, Member, IEEE"
+1f41a96589c5b5cee4a55fc7c2ce33e1854b09d6,Demographic Estimation from Face Images: Human vs. Machine Performance,"Demographic Estimation from Face Images:
+Human vs. Machine Performance
+Hu Han, Member, IEEE, Charles Otto, Student Member, IEEE, Xiaoming Liu, Member, IEEE
+nd Anil K. Jain, Fellow, IEEE"
+1f8e44593eb335c2253d0f22f7f9dc1025af8c0d,Fine-Tuning Regression Forests Votes for Object Alignment in the Wild,"Fine-tuning regression forests votes for object alignment in the wild.
+Yang, H; Patras, I
+© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be
+obtained for all other uses, in any current or future media, including reprinting/republishing
+this material for advertising or promotional purposes, creating new collective works, for resale
+or redistribution to servers or lists, or reuse of any copyrighted component of this work in
+other works.
+For additional information about this publication click this link.
+http://qmro.qmul.ac.uk/xmlui/handle/123456789/22607
+Information about this research object was correct at the time of download; we occasionally
+make corrections to records, please therefore check the published record when citing. For
+more information contact"
+1f94734847c15fa1da68d4222973950d6b683c9e,Embedding Label Structures for Fine-Grained Feature Representation,"Embedding Label Structures for Fine-Grained Feature Representation
+Xiaofan Zhang
+UNC Charlotte
+Charlotte, NC 28223
+Feng Zhou
+NEC Lab America
+Cupertino, CA 95014
+Yuanqing Lin
+NEC Lab America
+Cupertino, CA 95014
+Shaoting Zhang
+UNC Charlotte
+Charlotte, NC 28223"
+1f745215cda3a9f00a65166bd744e4ec35644b02,Facial cosmetics database and impact analysis on automatic face recognition,"Facial Cosmetics Database and Impact Analysis on
+Automatic Face Recognition
+Marie-Lena Eckert #1, Neslihan Kose ∗2, Jean-Luc Dugelay ∗3
+# Computer Science Department, TU Muenchen
+Boltzmannstr. 3, 85748 Garching b. Muenchen, Germany
+Multimedia Communications Department, EURECOM
+50 Route des Chappes, 06410 Biot, France"
+1fff309330f85146134e49e0022ac61ac60506a9,Data-Driven Sparse Sensor Placement for Reconstruction,"Data-Driven Sparse Sensor Placement for Reconstruction
+Krithika Manohar∗, Bingni W. Brunton, J. Nathan Kutz, and Steven L. Brunton
+Corresponding author:"
+73f467b4358ac1cafb57f58e902c1cab5b15c590,Combination of Dimensionality Reduction Techniques for Face Image Retrieval: A Review,"ISSN 0976 3724                                                                                                                                  47
+Combination of Dimensionality Reduction Techniques for Face
+Image Retrieval: A Review
+Fousiya K.K 1, Jahfar Ali P 2
+M.Tech Scholar, MES College of Engineering, Kuttippuram,
+Kerala
+Asst. Professor, MES College of Engineering, Kuttippuram,
+Kerala"
+7323b594d3a8508f809e276aa2d224c4e7ec5a80,An Experimental Evaluation of Covariates Effects on Unconstrained Face Verification,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
+An Experimental Evaluation of Covariates
+Effects on Unconstrained Face Veriﬁcation
+Boyu Lu, Student Member, IEEE, Jun-Cheng Chen, Member, IEEE, Carlos D Castillo, Member, IEEE
+nd Rama Chellappa, Fellow, IEEE"
+732e8d8f5717f8802426e1b9debc18a8361c1782,Unimodal Probability Distributions for Deep Ordinal Classification,"Unimodal Probability Distributions for Deep Ordinal Classiﬁcation
+Christopher Beckham 1 Christopher Pal 1"
+73ed64803d6f2c49f01cffef8e6be8fc9b5273b8,Cooking in the kitchen: Recognizing and Segmenting Human Activities in Videos,"Noname manuscript No.
+(will be inserted by the editor)
+Cooking in the kitchen: Recognizing and Segmenting Human
+Activities in Videos
+Hilde Kuehne · Juergen Gall · Thomas Serre
+Received: date / Accepted: date"
+7306d42ca158d40436cc5167e651d7ebfa6b89c1,Transductive Zero-Shot Action Recognition by Word-Vector Embedding,"Noname manuscript No.
+(will be inserted by the editor)
+Transductive Zero-Shot Action Recognition by
+Word-Vector Embedding
+Xun Xu · Timothy Hospedales · Shaogang Gong
+Received: date / Accepted: date"
+734cdda4a4de2a635404e4c6b61f1b2edb3f501d,Automatic landmark point detection and tracking for human facial expressions,"Tie and Guan EURASIP Journal on Image and Video Processing 2013, 2013:8
+http://jivp.eurasipjournals.com/content/2013/1/8
+R ES EAR CH
+Open Access
+Automatic landmark point detection and tracking
+for human facial expressions
+Yun Tie* and Ling Guan"
+732686d799d760ccca8ad47b49a8308b1ab381fb,Teachers’ differing classroom behaviors: The role of emotional sensitivity and cultural tolerance,"Running head: TEACHERS’ DIFFERING BEHAVIORS
+Graduate School of Psychology
+RESEARCH MASTER’S PSYCHOLOGY THESıS REPORT
+Teachers’ differing classroom behaviors:
+The role of emotional sensitivity and cultural tolerance
+Ceren Su Abacıoğlu
+Supervisor: prof. dr. Agneta Fischer
+Second supervisor: dr. Disa Sauter
+External Supervisor: prof. dr. Monique Volman
+Research Master’s, Social Psychology
+Ethics Committee Reference Code: 2016-SP-7084"
+73fbdd57270b9f91f2e24989178e264f2d2eb7ae,Kernel linear regression for low resolution face recognition under variable illumination,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE
+ICASSP 2012"
+73c9cbbf3f9cea1bc7dce98fce429bf0616a1a8c,Unsupervised Learning of Object Landmarks by Factorized Spatial Embeddings,"imagesViewpoint factorizationLearned landmarksFigure1.Wepresentanovelmethodthatcanlearnviewpointin-variantlandmarkswithoutanysupervision.Themethodusesaprocessofviewpointfactorizationwhichlearnsadeeplandmarkdetectorcompatiblewithimagedeformations.Itcanbeappliedtorigidanddeformableobjectsandobjectcategories.terns.Achievingadeeperunderstandingofobjectsrequiresmodelingtheirintrinsicviewpoint-independentstructure.Oftenthisstructureisdeﬁnedmanuallybyspecifyingen-titiessuchaslandmarks,parts,andskeletons.Givensufﬁ-cientmanualannotations,itispossibletoteachdeepneuralnetworksandothermodelstorecognizesuchstructuresinimages.However,theproblemoflearningsuchstructureswithoutmanualsupervisionremainslargelyopen.Inthispaper,wecontributeanewapproachtolearnviewpoint-independentrepresentationsofobjectsfromim-ageswithoutmanualsupervision(ﬁg.1).Weformulatethistaskasafactorizationproblem,wheretheeffectsofimagedeformations,forexamplearisingfromaviewpointchange,areexplainedbythemotionofareferenceframeattachedtotheobjectandindependentoftheviewpoint.Afterdescribingthegeneralprinciple(sec.3.1),wein-1"
+8796f2d54afb0e5c924101f54d469a1d54d5775d,Illumination Invariant Face Recognition Using Fuzzy LDA and FFNN,"Journal of Signal and Information Processing, 2012, 3, 45-50
+http://dx.doi.org/10.4236/jsip.2012.31007 Published Online February 2012 (http://www.SciRP.org/journal/jsip)
+Illumination Invariant Face Recognition Using Fuzzy LDA
+nd FFNN
+Behzad Bozorgtabar, Hamed Azami, Farzad Noorian
+School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran.
+Email:
+Received October 20th, 2011; revised November 24th, 2011; accepted December 10th, 2011"
+87f285782d755eb85d8922840e67ed9602cfd6b9,Incorporating Boltzmann Machine Priors for Semantic Labeling in Images and Videos,"INCORPORATING BOLTZMANN MACHINE PRIORS
+FOR SEMANTIC LABELING IN IMAGES AND VIDEOS
+A Dissertation Presented
+ANDREW KAE
+Submitted to the Graduate School of the
+University of Massachusetts Amherst in partial fulﬁllment
+of the requirements for the degree of
+DOCTOR OF PHILOSOPHY
+May 2014
+Computer Science"
+871f5f1114949e3ddb1bca0982086cc806ce84a8,Discriminative learning of apparel features,"Discriminative Learning of Apparel Features
+Rasmus Rothe1, Marko Ristin1, Matthias Dantone1, and Luc Van Gool1,2
+Computer Vision Laboratory, D-ITET, ETH Z¨urich, Switzerland
+ESAT - PSI / IBBT, K.U. Leuven, Belgium"
+87bee0e68dfc86b714f0107860d600fffdaf7996,Automated 3D Face Reconstruction from Multiple Images Using Quality Measures,"Automated 3D Face Reconstruction from Multiple Images
+using Quality Measures
+Marcel Piotraschke and Volker Blanz
+Institute for Vision and Graphics, University of Siegen, Germany"
+878169be6e2c87df2d8a1266e9e37de63b524ae7,Image interpretation above and below the object level.,"CBMM Memo No. 089
+May 10, 2018
+Image interpretation above and below the object level
+Guy Ben-Yosef, Shimon Ullman"
+878301453e3d5cb1a1f7828002ea00f59cbeab06,Faceness-Net: Face Detection through Deep Facial Part Responses,"Faceness-Net: Face Detection through
+Deep Facial Part Responses
+Shuo Yang, Ping Luo, Chen Change Loy, Senior Member, IEEE and Xiaoou Tang, Fellow, IEEE"
+87e592ee1a7e2d34e6b115da08700a1ae02e9355,Deep Pictorial Gaze Estimation,"Deep Pictorial Gaze Estimation
+Seonwook Park, Adrian Spurr, and Otmar Hilliges
+AIT Lab, Department of Computer Science, ETH Zurich"
+87dd3fd36bccbe1d5f1484ac05f1848b51c6eab5,Spatio-temporal Maximum Average Correlation Height Templates in Action Recognition and Video Summarization,"SPATIO-TEMPORAL MAXIMUM AVERAGE CORRELATION
+HEIGHT TEMPLATES IN ACTION RECOGNITION AND VIDEO
+SUMMARIZATION
+MIKEL RODRIGUEZ
+B.A. Earlham College, Richmond Indiana
+M.S. University of Central Florida
+A dissertation submitted in partial fulﬁllment of the requirements
+for the degree of Doctor of Philosophy
+in the School of Electrical Engineering and Computer Science
+in the College of Engineering and Computer Science
+t the University of Central Florida
+Orlando, Florida
+Summer Term
+Major Professor: Mubarak Shah"
+87bb183d8be0c2b4cfceb9ee158fee4bbf3e19fd,Craniofacial Image Analysis,"Craniofacial Image Analysis
+Ezgi Mercan, Indriyati Atmosukarto, Jia Wu, Shu Liang and Linda G. Shapiro"
+8006219efb6ab76754616b0e8b7778dcfb46603d,Contributions to large-scale learning for image classification. (Contributions à l'apprentissage grande échelle pour la classification d'images),"CONTRIBUTIONSTOLARGE-SCALELEARNINGFORIMAGECLASSIFICATIONZeynepAkataPhDThesisl’´EcoleDoctoraleMath´ematiques,SciencesetTechnologiesdel’Information,InformatiquedeGrenoble"
+804b4c1b553d9d7bae70d55bf8767c603c1a09e3,Subspace clustering with a learned dimensionality reduction projection,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE
+ICASSP 2016"
+800cbbe16be0f7cb921842d54967c9a94eaa2a65,Multimodal Recognition of Emotions Multimodal Recognition of Emotions,"MULTIMODAL RECOGNITION OF
+EMOTIONS"
+80135ed7e34ac1dcc7f858f880edc699a920bf53,Efficient Action and Event Recognition in Videos Using Extreme Learning Machines,"EFFICIENT ACTION AND EVENT RECOGNITION IN VIDEOS USING
+EXTREME LEARNING MACHINES
+G¨ul Varol
+B.S., Computer Engineering, Bo˘gazi¸ci University, 2013
+Submitted to the Institute for Graduate Studies in
+Science and Engineering in partial fulﬁllment of
+the requirements for the degree of
+Master of Science
+Graduate Program in Computer Engineering
+Bo˘gazi¸ci University"
+803c92a3f0815dbf97e30c4ee9450fd005586e1a,Max-Mahalanobis Linear Discriminant Analysis Networks,"Max-Mahalanobis Linear Discriminant Analysis Networks
+Tianyu Pang 1 Chao Du 1 Jun Zhu 1"
+80c8d143e7f61761f39baec5b6dfb8faeb814be9,Local Directional Pattern based Fuzzy Co- occurrence Matrix Features for Face recognition,"Local Directional Pattern based Fuzzy Co-
+occurrence Matrix Features for Face recognition
+Dr. P Chandra Sekhar Reddy
+Professor, CSE Dept.
+Gokaraju Rangaraju Institute of Engineering and Technology, Hyd."
+80345fbb6bb6bcc5ab1a7adcc7979a0262b8a923,Soft Biometrics for a Socially Assistive Robotic Platform,"Research Article
+Pierluigi Carcagnì*, Dario Cazzato, Marco Del Coco, Pier Luigi Mazzeo, Marco Leo, and
+Cosimo Distante
+Soft Biometrics for a Socially Assistive Robotic
+Platform
+Open Access"
+80a6bb337b8fdc17bffb8038f3b1467d01204375,Subspace LDA Methods for Solving the Small Sample Size Problem in Face Recognition,"Proceedings of the International Conference on Computer and Information Science and Technology
+Ottawa, Ontario, Canada, May 11 – 12, 2015
+Paper No. 126
+Subspace LDA Methods for Solving the Small Sample Size
+Problem in Face Recognition
+Ching-Ting Huang, Chaur-Chin Chen
+Department of Computer Science/National Tsing Hua University
+01 KwanFu Rd., Sec. 2, Hsinchu, Taiwan"
+80097a879fceff2a9a955bf7613b0d3bfa68dc23,Active Self-Paced Learning for Cost-Effective and Progressive Face Identification,"Active Self-Paced Learning for Cost-Effective and
+Progressive Face Identiﬁcation
+Liang Lin, Keze Wang, Deyu Meng, Wangmeng Zuo, and Lei Zhang"
+74408cfd748ad5553cba8ab64e5f83da14875ae8,Facial Expressions Tracking and Recognition: Database Protocols for Systems Validation and Evaluation,"Facial Expressions Tracking and Recognition: Database Protocols for Systems Validation
+nd Evaluation"
+74dbe6e0486e417a108923295c80551b6d759dbe,An HMM based Model for Prediction of Emotional Composition of a Facial Expression using both Significant and Insignificant Action Units and Associated Gender Differences,"International Journal of Computer Applications (0975 – 8887)
+Volume 45– No.11, May 2012
+An HMM based Model for Prediction of Emotional
+Composition of a Facial Expression using both
+Significant and Insignificant Action Units and
+Associated Gender Differences
+Suvashis Das
+Koichi Yamada
+Department of Management and Information
+Department of Management and Information
+Systems Science
+603-1 Kamitomioka, Nagaoka
+Niigata, Japan
+Systems Science
+603-1 Kamitomioka, Nagaoka
+Niigata, Japan"
+747c25bff37b96def96dc039cc13f8a7f42dbbc7,EmoNets: Multimodal deep learning approaches for emotion recognition in video,"EmoNets: Multimodal deep learning approaches for emotion
+recognition in video
+Samira Ebrahimi Kahou · Xavier Bouthillier · Pascal Lamblin · Caglar Gulcehre ·
+Vincent Michalski · Kishore Konda · S´ebastien Jean · Pierre Froumenty · Yann
+Dauphin · Nicolas Boulanger-Lewandowski · Raul Chandias Ferrari · Mehdi Mirza ·
+David Warde-Farley · Aaron Courville · Pascal Vincent · Roland Memisevic ·
+Christopher Pal · Yoshua Bengio"
+744fa8062d0ae1a11b79592f0cd3fef133807a03,Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification.,"Aalborg Universitet
+Deep Pain
+Rodriguez, Pau; Cucurull, Guillem; Gonzàlez, Jordi; M. Gonfaus, Josep ; Nasrollahi, Kamal;
+Moeslund, Thomas B.; Xavier Roca, F.
+Published in:
+I E E E Transactions on Cybernetics
+DOI (link to publication from Publisher):
+0.1109/TCYB.2017.2662199
+Publication date:
+Document Version
+Accepted author manuscript, peer reviewed version
+Link to publication from Aalborg University
+Citation for published version (APA):
+Rodriguez, P., Cucurull, G., Gonzàlez, J., M. Gonfaus, J., Nasrollahi, K., Moeslund, T. B., & Xavier Roca, F.
+(2017). Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification. I E E E
+Transactions on Cybernetics, 1-11. DOI: 10.1109/TCYB.2017.2662199
+General rights
+Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners
+nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.
+? Users may download and print one copy of any publication from the public portal for the purpose of private study or research."
+743e582c3e70c6ec07094887ce8dae7248b970ad,Face Recognition based on Deep Neural Network,"International Journal of Signal Processing, Image Processing and Pattern Recognition
+Vol.8, No.10 (2015), pp.29-38
+http://dx.doi.org/10.14257/ijsip.2015.8.10.04
+Face Recognition based on Deep Neural Network
+Li Xinhua,Yu Qian
+Shandong Women’s University"
+74b0095944c6e29837c208307a67116ebe1231c8,Manifold learning using Euclidean k-nearest neighbor graphs [image processing examples],"beindependentandidenticallydis-tributed(i.i.d.)randomvectorswithvaluesinacompactsubsetof.The(-)nearestneighborofinisgivenby!""$%&(*,.%13575where575istheusualEuclidean(<=)distanceinbe-tweenvectorand.Forgeneralinteger?,the-nearestneighborofapointisdeﬁnedinasimilarway.The-NNgraphputsanedgebetweeneachpointinandits-nearestneighbors.LetBCDBCDFHbethesetof-nearestneighborsofin.Thetotaledgelengthofthe-NNgraphisdeﬁnedas:<JDCFHMN
+M%&QRS1575J(1)whereVWXisapowerweightingconstant.2.1.ConvergencetoExtrinsicZ-EntropyThe-NNedgelengthliesinthelargeclassoffunctionalscalledcontinuousquasi-additiveEuclideanfunctionals[7].Othergraphsinthisclassincludetheminimalspanningtree,theminimalmatch-inggraphorthetravelingsalesmantouramongothers.Thesefunc-tionalshaveremarkableasymptoticbehaviorasincreases:Theorem1([7,Theorem8.3])Let
+bei.i.d.randomvectorswithvaluesinacompactsubsetofandLebesgueden-sity\.Let]?_,aVb]anddeﬁneZF]7VHf].Then,withprobability(w.p.)gh""jk<JDCFHmoDJDCp\mFrHtr(2)whereoDJDCisaconstantindependentof\.Furthermore,themeanlengthuv<JDCFHwfmconvergestothesamelimit.Thequantitythatdeterminesthelimit(2)inTheorem1istheex-trinsicR´enyiZ-entropyofthemultivariateLebesguedensity\:yz{mF\H7Zg!pz{\mFrHtr(3)III - 9880-7803-8484-9/04/$20.00 ©2004 IEEEICASSP 2004(cid:224)"
+74156a11c2997517061df5629be78428e1f09cbd,"Preparatory coordination of head, eyes and hands: Experimental study at intersections","Cancún Center, Cancún, México, December 4-8, 2016
+978-1-5090-4846-5/16/$31.00 ©2016 IEEE"
+748e72af01ba4ee742df65e9c030cacec88ce506,Discriminative Regions Selection for Facial Expression Recognition,"Discriminative Regions Selection for Facial Expression
+Recognition
+Hazar Mliki1 and Mohamed Hammami2
+1 MIRACL-FSEG, University of Sfax
+018 Sfax, Tunisia
+MIRACL-FS, University of Sfax
+018 Sfax, Tunisia"
+749d605dd12a4af58de1fae6f5ef5e65eb06540e,Multi-Task Video Captioning with Video and Entailment Generation,"Multi-Task Video Captioning with Video and Entailment Generation
+Ramakanth Pasunuru and Mohit Bansal
+UNC Chapel Hill
+{ram,"
+749382d19bfe9fb8d0c5e94d0c9b0a63ab531cb7,A Modular Framework to Detect and Analyze Faces for Audience Measurement Systems,"A Modular Framework to Detect and Analyze Faces for
+Audience Measurement Systems
+Andreas Ernst, Tobias Ruf, Christian Kueblbeck
+Fraunhofer Institute for Integrated Circuits IIS
+Department Electronic Imaging
+Am Wolfsmantel 33, 91058 Erlangen, Germany
+{andreas.ernst, tobias.ruf,"
+74c19438c78a136677a7cb9004c53684a4ae56ff,RESOUND: Towards Action Recognition without Representation Bias,"RESOUND: Towards Action Recognition
+without Representation Bias
+Yingwei Li, Yi Li, and Nuno Vasconcelos
+UC San Diego"
+74eae724ef197f2822fb7f3029c63014625ce1ca,Feature Extraction based on Local Directional Pattern with SVM Decision-level Fusion for Facial Expression Recognition,"International Journal of Bio-Science and Bio-Technology
+Vol. 5, No. 2, April, 2013
+Feature Extraction based on Local Directional Pattern with SVM
+Decision-level Fusion for Facial Expression Recognition
+Juxiang Zhou1, Tianwei Xu1,2 and Jianhou Gan1
+Key Laboratory of Education Informalization for Nationalities, Ministry of
+Education, Yunnan Normal University, Kunming, China
+College of Information, Yunnan Normal University, Kunming, China"
+7480d8739eb7ab97c12c14e75658e5444b852e9f,MLBoost Revisited: A Faster Metric Learning Algorithm for Identity-Based Face Retrieval,"NEGREL ET AL.: REVISITED MLBOOST FOR FACE RETRIEVAL
+MLBoost Revisited: A Faster Metric
+Learning Algorithm for Identity-Based Face
+Retrieval
+Romain Negrel
+Alexis Lechervy
+Frederic Jurie
+Normandie Univ, UNICAEN,
+ENSICAEN, CNRS
+France"
+74ba4ab407b90592ffdf884a20e10006d2223015,Partial Face Detection in the Mobile Domain,"Partial Face Detection in the Mobile Domain
+Upal Mahbub, Student Member, IEEE, Sayantan Sarkar, Student Member, IEEE,
+nd Rama Chellappa, Fellow, IEEE"
+7405ed035d1a4b9787b78e5566340a98fe4b63a0,Self-Expressive Decompositions for Matrix Approximation and Clustering,"Self-Expressive Decompositions for
+Matrix Approximation and Clustering
+Eva L. Dyer, Member, IEEE, Tom A. Goldstein, Member, IEEE, Raajen Patel, Student Member, IEEE,
+Konrad P. K¨ording, and Richard G. Baraniuk, Fellow, IEEE"
+744db9bd550bf5e109d44c2edabffec28c867b91,FX e-Makeup for Muscle Based Interaction,"FX e-Makeup for Muscle Based Interaction
+Katia Canepa Vega1, Abel Arrieta2, Felipe Esteves3, and Hugo Fuks1
+Department of Informatics, PUC-Rio, Rio de Janeiro, Brazil
+Department of Mechanical Engineering, PUC-Rio, Rio de Janeiro, Brazil
+Department of Administration, PUC-Rio, Rio de Janeiro, Brazil"
+74325f3d9aea3a810fe4eab8863d1a48c099de11,Regression-Based Image Alignment for General Object Categories,"Regression-Based Image Alignment
+for General Object Categories
+Hilton Bristow1 and Simon Lucey2
+Queensland University of Technology (QUT)
+Brisbane QLD 4000, Australia
+Carnegie Mellon University (CMU)
+Pittsburgh PA 15289, USA"
+744d23991a2c48d146781405e299e9b3cc14b731,Aging Face Recognition: A Hierarchical Learning Model Based on Local Patterns Selection,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TIP.2016.2535284, IEEE
+Transactions on Image Processing
+Aging Face Recognition: A Hierarchical Learning
+Model Based on Local Patterns Selection
+Zhifeng Li, Senior Member, IEEE, Dihong Gong, Xuelong Li, Fellow, IEEE, and Dacheng Tao, Fellow, IEEE"
+1a45ddaf43bcd49d261abb4a27977a952b5fff12,LDOP: Local Directional Order Pattern for Robust Face Retrieval,"LDOP: Local Directional Order Pattern for Robust
+Face Retrieval
+Shiv Ram Dubey, Member, IEEE, and Snehasis Mukherjee, Member, IEEE"
+1aa766bbd49bac8484e2545c20788d0f86e73ec2,"Baseline face detection, head pose estimation, and coarse direction detection for facial data in the SHRP2 naturalistic driving study","Baseline Face Detection, Head Pose Estimation, and Coarse
+Direction Detection for Facial Data in the SHRP2 Naturalistic
+Driving Study
+J. Paone, D. Bolme, R. Ferrell, Member, IEEE, D. Aykac,  and
+T. Karnowski, Member, IEEE
+Oak Ridge National Laboratory, Oak Ridge, TN"
+1a849b694f2d68c3536ed849ed78c82e979d64d5,This is a repository copy of Symmetric Shape Morphing for 3 D Face and Head Modelling,"This is a repository copy of Symmetric Shape Morphing for 3D Face and Head Modelling.
+White Rose Research Online URL for this paper:
+http://eprints.whiterose.ac.uk/131760/
+Version: Accepted Version
+Proceedings Paper:
+Dai, Hang, Pears, Nicholas Edwin orcid.org/0000-0001-9513-5634, Smith, William Alfred
+Peter orcid.org/0000-0002-6047-0413 et al. (1 more author) (2018) Symmetric Shape
+Morphing for 3D Face and Head Modelling. In: The 13th IEEE Conference on Automatic
+Face and Gesture Recognition. IEEE .
+Reuse
+Items deposited in White Rose Research Online are protected by copyright, with all rights reserved unless
+indicated otherwise. They may be downloaded and/or printed for private study, or other acts as permitted by
+national copyright laws. The publisher or other rights holders may allow further reproduction and re-use of
+the full text version. This is indicated by the licence information on the White Rose Research Online record
+for the item.
+Takedown
+If you consider content in White Rose Research Online to be in breach of UK law, please notify us by
+emailing including the URL of the record and the reason for the withdrawal request.
+https://eprints.whiterose.ac.uk/"
+1a878e4667fe55170252e3f41d38ddf85c87fcaf,Discriminative Machine Learning with Structure,"Discriminative Machine Learning with Structure
+Simon Lacoste-Julien
+Electrical Engineering and Computer Sciences
+University of California at Berkeley
+Technical Report No. UCB/EECS-2010-4
+http://www.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-4.html
+January 12, 2010"
+1a41831a3d7b0e0df688fb6d4f861176cef97136,A Biological Model of Object Recognition with Feature Learning,"massachusetts institute of technology — artificial intelligence laboratory
+A Biological Model of Object
+Recognition with Feature Learning
+Jennifer Louie
+AI Technical Report 2003-009
+CBCL Memo 227
+June 2003
+© 2 0 0 3   m a s s a c h u s e t t s   i n s t i t u t e   o f
+t e c h n o l o g y, c a m b r i d g e , m a   0 2 1 3 9   u s a   —   w w w. a i . m i t . e d u"
+1a6c3c37c2e62b21ebc0f3533686dde4d0103b3f,Implementation of Partial Face Recognition using Directional Binary Code,"International Journal of Linguistics and Computational Applications (IJLCA)                          ISSN 2394-6385 (Print)
+Volume 4, Issue 1, January – March 2017                                                                                   ISSN 2394-6393 (Online)
+Implementation of Partial Face Recognition
+using Directional Binary Code
+N.Pavithra #1, A.Sivapriya*2, K.Hemalatha*3 , D.Lakshmi*4
+,2,3Final Year, Department of Computer Science and Engineering, PanimalarInstitute of Technology,
+Assistant Professor, Department of Computer Science and Engineering, PanimalarInstitute of Technology, Tamilnadu, India,
+faith
+is  proposed.  It
+face  alignment  and"
+1a3eee980a2252bb092666cf15dd1301fa84860e,PCA Gaussianization for image processing,"PCA GAUSSIANIZATION FOR IMAGE PROCESSING
+Valero Laparra, Gustavo Camps-Valls and Jes´us Malo
+Image Processing Laboratory (IPL), Universitat de Val`encia
+Catedr´atico A. Escardino - 46980 Paterna, Val`encia, Spain"
+1a031378cf1d2b9088a200d9715d87db8a1bf041,D Eep D Ictionary L Earning : S Ynergizing R E - Construction and C Lassification,"Workshop track - ICLR 2018
+DEEP DICTIONARY LEARNING: SYNERGIZING RE-
+CONSTRUCTION AND CLASSIFICATION
+Shahin Mahdizadehaghdam, Ashkan Panahi, Hamid Krim & Liyi Dai"
+1afd481036d57320bf52d784a22dcb07b1ca95e2,Automated Content Metadata Extraction Services Based on MPEG Standards,"The Computer Journal Advance Access published December 6, 2012
+© The Author 2012. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.
+For Permissions, please email:
+doi:10.1093/comjnl/bxs146
+Automated Content Metadata Extraction
+Services Based on MPEG Standards
+D.C. Gibbon∗, Z. Liu, A. Basso and B. Shahraray
+AT&T Labs Research, Middletown, NJ, USA
+Corresponding author:
+This paper is concerned with the generation, acquisition, standardized representation and transport
+of video metadata. The use of MPEG standards in the design and development of interoperable
+media architectures and web services is discussed. A high-level discussion of several algorithms
+for metadata extraction is presented. Some architectural and algorithmic issues encountered when
+designing services for real-time processing of video streams, as opposed to traditional offline media
+processing, are addressed. A prototype real-time video analysis system for generating MPEG-7
+Audiovisual Description Proﬁle from MPEG-2 transport stream encapsulated video is presented.
+Such a capability can enable a range of new services such as content-based personalization of live
+roadcasts given that the MPEG-7 based data models ﬁt in well with speciﬁcations for advanced
+television services such as TV-Anytime andAlliance for Telecommunications Industry Solutions IPTV
+Interoperability Forum."
+1a9a192b700c080c7887e5862c1ec578012f9ed1,Discriminant Subspace Analysis for Face Recognition with Small Number of Training Samples,"IEEE TRANSACTIONS ON SYSTEM, MAN AND CYBERNETICS, PART B
+Discriminant Subspace Analysis for Face
+Recognition with Small Number of Training
+Samples
+Hui Kong, Xuchun Li, Matthew Turk, and Chandra Kambhamettu"
+1a8ccc23ed73db64748e31c61c69fe23c48a2bb1,Extensive Facial Landmark Localization with Coarse-to-Fine Convolutional Network Cascade,"Extensive Facial Landmark Localization
+with Coarse-to-ﬁne Convolutional Network Cascade
+Erjin Zhou Haoqiang Fan Zhimin Cao Yuning Jiang Qi Yin
+Megvii Inc."
+1ad97cce5fa8e9c2e001f53f6f3202bddcefba22,Grassmann Averages for Scalable Robust PCA,"Grassmann Averages for Scalable Robust PCA
+Aasa Feragen
+DIKU and MPIs T¨ubingen∗
+Denmark and Germany
+Søren Hauberg
+DTU Compute∗
+Lyngby, Denmark"
+1a7a2221fed183b6431e29a014539e45d95f0804,Person Identification Using Text and Image Data,"Person Identiﬁcation Using Text and Image Data
+David S. Bolme, J. Ross Beveridge and Adele E. Howe
+Computer Science Department
+Colorado State Univeristy
+Fort Collins, Colorado 80523"
+1a5b39a4b29afc5d2a3cd49087ae23c6838eca2b,Competitive Game Designs for Improving the Cost Effectiveness of Crowdsourcing,"Competitive Game Designs for Improving the Cost
+Effectiveness of Crowdsourcing
+Markus Rokicki, Sergiu Chelaru, Sergej Zerr, Stefan Siersdorfer
+L3S Research Center, Hannover, Germany"
+287795991fad3c61d6058352879c7d7ae1fdd2b6,Biometrics Security: Facial Marks Detection from the Low Quality Images,"International Journal of Computer Applications (0975 – 8887)
+Volume 66– No.8, March 2013
+Biometrics Security: Facial Marks Detection from the
+Low Quality Images
+nd  facial  marks  are  detected  using  LoG  with  morphological
+operator.  This  method  though  was  not  enough  to  detect  the
+facial  marks  from  the  low  quality  images  [7].  But,  facial
+marks  have  been  used  to  speed  up  the  retrieval  process  in
+order to differentiate the human faces [15].
+Ziaul Haque Choudhury                                                      K.M.Mehata
+B.S.Abdur Rahman University                                                     B.S.Abdur Rahman University
+Dept. Of Information Technology                                        Dept. Of Computer Science & Engineering
+Chennai, India                                                                               Chennai, India"
+28d7029cfb73bcb4ad1997f3779c183972a406b4,Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification,"Discriminative Nonlinear Analysis Operator
+Learning: When Cosparse Model Meets Image
+Classiﬁcation
+Zaidao Wen, Biao Hou, Member, IEEE, and Licheng Jiao, Senior Member, IEEE"
+280d59fa99ead5929ebcde85407bba34b1fcfb59,Online Nonnegative Matrix Factorization With Outliers,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE
+ICASSP 2016"
+28cd46a078e8fad370b1aba34762a874374513a5,"cvpaper.challenge in 2016: Futuristic Computer Vision through 1, 600 Papers Survey","CVPAPER.CHALLENGE IN 2016, JULY 2017
+vpaper.challenge in 2016: Futuristic Computer
+Vision through 1,600 Papers Survey
+Hirokatsu Kataoka, Soma Shirak-
+be, Yun He, Shunya Ueta, Teppei Suzuki, Kaori Abe, Asako Kanezaki, Shin’ichiro
+Morita, Toshiyuki Yabe, Yoshihiro Kanehara, Hiroya Yatsuyanagi, Shinya Maruyama, Ryosuke Taka-
+sawa, Masataka Fuchida, Yudai Miyashita, Kazushige Okayasu, Yuta Matsuzaki"
+28b5b5f20ad584e560cd9fb4d81b0a22279b2e7b,A New Fuzzy Stacked Generalization Technique and Analysis of its Performance,"A New Fuzzy Stacked Generalization Technique
+nd Analysis of its Performance
+Mete Ozay, Student Member, IEEE, Fatos T. Yarman Vural, Member, IEEE"
+28bc378a6b76142df8762cd3f80f737ca2b79208,Understanding Objects in Detail with Fine-Grained Attributes,"Understanding Objects in Detail with Fine-grained Attributes
+Andrea Vedaldi1
+Siddharth Mahendran2
+Stavros Tsogkas3
+Subhransu Maji4
+Ross Girshick5
+Juho Kannala6
+Esa Rahtu6
+Matthew B. Blaschko3
+David Weiss7
+Ben Taskar8
+Naomi Saphra2
+Sammy Mohamed9
+Iasonas Kokkinos3
+Karen Simonyan1"
+28bcf31f794dc27f73eb248e5a1b2c3294b3ec9d,Improved Combination of LBP plus LFDA for Facial Expression Recognition using SRC,"International Journal of Computer Applications (0975 – 8887)
+Volume 96– No.13, June 2014
+Improved Combination of LBP plus LFDA for Facial
+Expression Recognition using SRC
+Ritesh Bora
+Research Scholar, CSE Department,
+Government College of Engineering, Aurangabad
+human
+facial
+expression
+recognition"
+28fe6e785b32afdcd2c366c9240a661091b850cf,Facial Expression Recognition using Patch based Gabor Features,"International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
+Foundation of Computer Science FCS, New York, USA
+Volume 10 – No.7, March 2016 – www.ijais.org
+Facial Expression Recognition using Patch based Gabor
+Features
+Electronics & Telecommunication Engg
+Electronics & Telecommunication Engg
+St. Francis Institute of Technology
+St. Francis Institute of Technology
+Vaqar Ansari
+Department
+Mumbai, India
+Anju Chandran
+Department
+Mumbai, India"
+28c9198d30447ffe9c96176805c1cd81615d98c8,No evidence that a range of artificial monitoring cues influence online donations to charity in an MTurk sample,"rsos.royalsocietypublishing.org
+Research
+Cite this article: Saunders TJ, Taylor AH,
+Atkinson QD. 2016 No evidence that a range of
+rtificial monitoring cues influence online
+donations to charity in an MTurk sample.
+R. Soc. open sci. 3: 150710.
+http://dx.doi.org/10.1098/rsos.150710
+Received: 22 December 2015
+Accepted: 13 September 2016
+Subject Category:
+Psychology and cognitive neuroscience
+Subject Areas:
+ehaviour/psychology/evolution
+Keywords:
+prosociality, eye images, charity donation,
+reputation, online behaviour
+Author for correspondence:
+Quentin D. Atkinson
+e-mail:"
+2866cbeb25551257683cf28f33d829932be651fe,A Two-Step Learning Method For Detecting Landmarks on Faces From Different Domains,"In Proceedings of the 2018 IEEE International Conference on Image Processing (ICIP)
+The ﬁnal publication is available at: http://dx.doi.org/10.1109/ICIP.2018.8451026
+A TWO-STEP LEARNING METHOD FOR DETECTING LANDMARKS
+ON FACES FROM DIFFERENT DOMAINS
+Bruna Vieira Frade
+Erickson R. Nascimento
+Universidade Federal de Minas Gerais (UFMG), Brazil
+{brunafrade,"
+28aa89b2c827e5dd65969a5930a0520fdd4a3dc7,Characterization and Classification of Faces across Age Progression,
+28b061b5c7f88f48ca5839bc8f1c1bdb1e6adc68,Predicting User Annoyance Using Visual Attributes,"Predicting User Annoyance Using Visual Attributes
+Gordon Christie
+Virginia Tech
+Amar Parkash
+Goibibo
+Ujwal Krothapalli
+Virginia Tech
+Devi Parikh
+Virginia Tech"
+17a85799c59c13f07d4b4d7cf9d7c7986475d01c,Extending Procrustes Analysis: Building Multi-view 2-D Models from 3-D Human Shape Samples,"ADVERTIMENT.  La  consulta  d’aquesta  tesi  queda  condicionada  a  l’acceptació  de  les  següents
+ondicions  d'ús:  La  difusió  d’aquesta  tesi  per  mitjà  del  servei  TDX  (www.tesisenxarxa.net)  ha
+estat  autoritzada  pels  titulars  dels  drets  de  propietat  intel·lectual  únicament  per  a  usos  privats
+emmarcats en activitats d’investigació i docència. No s’autoritza la seva reproducció amb finalitats
+de lucre ni la seva difusió i posada a disposició des d’un lloc aliè al servei TDX. No s’autoritza la
+presentació  del  seu  contingut  en  una  finestra  o  marc  aliè  a  TDX  (framing).  Aquesta  reserva  de
+drets afecta tant al resum de presentació de la tesi com als seus continguts. En la utilització o cita
+de parts de la tesi és obligat indicar el nom de la persona autora.
+ADVERTENCIA. La consulta de esta tesis queda condicionada a la aceptación de las siguientes
+ondiciones de uso: La difusión de esta tesis por medio del servicio TDR (www.tesisenred.net) ha
+sido autorizada por los titulares de los derechos de propiedad intelectual únicamente para usos
+privados enmarcados en actividades de investigación y docencia. No se autoriza su reproducción
+on finalidades de lucro ni su difusión y puesta a disposición desde un sitio ajeno al servicio TDR.
+No se autoriza la presentación de su contenido en una ventana o marco ajeno a TDR (framing).
+Esta  reserva  de  derechos  afecta  tanto  al  resumen  de  presentación  de  la  tesis  como  a  sus
+ontenidos.  En  la  utilización  o  cita  de  partes  de  la  tesis  es  obligado  indicar  el  nombre  de  la
+persona autora.
+WARNING.  On  having  consulted  this  thesis  you’re  accepting  the  following  use  conditions:
+Spreading  this  thesis  by  the  TDX  (www.tesisenxarxa.net)  service  has  been  authorized  by  the
+titular of the intellectual property rights only for private uses placed in investigation and teaching"
+176f26a6a8e04567ea71677b99e9818f8a8819d0,MEG: Multi-Expert Gender Classification from Face Images in a Demographics-Balanced Dataset,"MEG: Multi-Expert Gender classiﬁcation from
+face images in a demographics-balanced dataset
+Modesto Castrill´on-Santana1, Maria De Marsico2, Michele Nappi3, and
+Daniel Riccio4
+Universidad de Las Palmas de Gran Canaria, Spain. Email:
+Sapienza University of Rome, Italy. Email:
+University of Salerno, Fisciano (SA), Italy. Email:
+University of Naples Federico II, Italy, Email:"
+17cf838720f7892dbe567129dcf3f7a982e0b56e,Global-Local Face Upsampling Network,"Global-Local Face Upsampling Network
+Oncel Tuzel
+Yuichi Taguchi
+John R. Hershey
+Mitsubishi Electric Research Labs (MERL), Cambridge, MA, USA"
+17370f848801871deeed22af152489e39b6e1454,Undersampled face recognition with one-pass dictionary learning,"UNDERSAMPLED FACE RECOGNITION WITH ONE-PASS DICTIONARY LEARNING
+Chia-Po Wei and Yu-Chiang Frank Wang
+Research Center for Information Technology Innovation, Academia Sinica, Taipei, Taiwan
+{cpwei,"
+178a82e3a0541fa75c6a11350be5bded133a59fd,BioHDD: a dataset for studying biometric identification on heavily degraded data,"Techset Composition Ltd, Salisbury
+{IEE}BMT/Articles/Pagination/BMT20140045.3d
+www.ietdl.org
+Received on 15th July 2014
+Revised on 17th September 2014
+Accepted on 23rd September 2014
+doi: 10.1049/iet-bmt.2014.0045
+ISSN 2047-4938
+BioHDD: a dataset for studying biometric
+identification on heavily degraded data
+Gil Santos1, Paulo T. Fiadeiro2, Hugo Proença1
+Department of Computer Science, IT – Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal
+Department of Physics, Remote Sensing Unit – Optics, Optometry and Vision Sciences Group, University of Beira Interior,
+Covilhã, Portugal
+E-mail:"
+17a995680482183f3463d2e01dd4c113ebb31608,Structured Label Inference for Visual Understanding,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. X, NO. Y, MONTH Z
+Structured Label Inference for
+Visual Understanding
+Nelson Nauata, Hexiang Hu, Guang-Tong Zhou, Zhiwei Deng,
+Zicheng Liao and Greg Mori"
+1742ffea0e1051b37f22773613f10f69d2e4ed2c,Interactive Mirror for Smart Home,
+174930cac7174257515a189cd3ecfdd80ee7dd54,Multi-view Face Detection Using Deep Convolutional Neural Networks,"Multi-view Face Detection Using Deep Convolutional
+Neural Networks
+Sachin Sudhakar Farfade
+Yahoo
+Mohammad Saberian
+inc.com
+Yahoo
+Li-Jia Li
+Yahoo"
+1750db78b7394b8fb6f6f949d68f7c24d28d934f,Detecting Facial Retouching Using Supervised Deep Learning,"Detecting Facial Retouching Using Supervised
+Deep Learning
+Aparna Bharati, Richa Singh, Senior Member, IEEE, Mayank Vatsa, Senior Member, IEEE, Kevin W.
+Bowyer, Fellow, IEEE"
+173657da03e3249f4e47457d360ab83b3cefbe63,HKU-Face : A Large Scale Dataset for Deep Face Recognition Final Report,"HKU-Face: A Large Scale Dataset for
+Deep Face Recognition
+Final Report
+Haicheng Wang
+035140108
+COMP4801 Final Year Project
+Project Code: 17007"
+7bbaa09c9e318da4370a83b126bcdb214e7f8428,"FaaSter, Better, Cheaper: The Prospect of Serverless Scientific Computing and HPC","FaaSter, Better, Cheaper: The Prospect of
+Serverless Scientiﬁc Computing and HPC
+Josef Spillner1, Cristian Mateos2, and David A. Monge3
+Zurich University of Applied Sciences, School of Engineering
+Service Prototyping Lab (blog.zhaw.ch/icclab/), 8401 Winterthur, Switzerland
+ISISTAN Research Institute - CONICET - UNICEN
+Campus Universitario, Paraje Arroyo Seco, Tandil (7000), Buenos Aires, Argentina
+ITIC Research Institute, National University of Cuyo
+Padre Jorge Contreras 1300, M5502JMA Mendoza, Argentina"
+7b9961094d3e664fc76b12211f06e12c47a7e77d,Bridging biometrics and forensics,"Bridging Biometrics and Forensics
+Yanjun Yan and Lisa Ann Osadciw
+EECS, Syracuse University, Syracuse, NY, USA
+{yayan,"
+7b9b3794f79f87ca8a048d86954e0a72a5f97758,Passing an Enhanced Turing Test - Interacting with Lifelike Computer Representations of Specific Individuals,"DOI 10.1515/jisys-2013-0016      Journal of Intelligent Systems 2013; 22(4): 365–415
+Avelino J. Gonzalez*, Jason Leigh, Ronald F. DeMara, Andrew
+Johnson, Steven Jones, Sangyoon Lee, Victor Hung, Luc
+Renambot, Carlos Leon-Barth, Maxine Brown, Miguel Elvir,
+James Hollister and Steven Kobosko
+Passing an Enhanced Turing Test –
+Interacting with Lifelike Computer
+Representations of Specific Individuals"
+7bce4f4e85a3bfcd6bfb3b173b2769b064fce0ed,A Psychologically-Inspired Match-Score Fusion Model for Video-Based Facial Expression Recognition,"A Psychologically-Inspired Match-Score Fusion Model
+for Video-Based Facial Expression Recognition
+Albert Cruz, Bir Bhanu, Songfan Yang,
+VISLab, EBUII-216, University of California Riverside,
+Riverside, California, USA, 92521-0425
+{acruz, bhanu,"
+7b0f1fc93fb24630eb598330e13f7b839fb46cce,Learning to Find Eye Region Landmarks for Remote Gaze Estimation in Unconstrained Settings,"Learning to Find Eye Region Landmarks for Remote Gaze
+Estimation in Unconstrained Settings
+Seonwook Park
+ETH Zurich
+Xucong Zhang
+MPI for Informatics
+Andreas Bulling
+MPI for Informatics
+Otmar Hilliges
+ETH Zurich"
+7bdcd85efd1e3ce14b7934ff642b76f017419751,Learning Discriminant Face Descriptor,"Learning Discriminant Face Descriptor
+Zhen Lei, Member, IEEE, Matti Pietika¨ inen, Fellow, IEEE, and Stan Z. Li, Fellow, IEEE"
+7b3b7769c3ccbdf7c7e2c73db13a4d32bf93d21f,"On the design and evaluation of robust head pose for visual user interfaces: algorithms, databases, and comparisons","On the Design and Evaluation of Robust Head Pose for
+Visual User Interfaces: Algorithms, Databases, and
+Comparisons
+Sujitha Martin
+Laboratory of Intelligent and
+Safe Automobiles
+UCSD - La Jolla, CA, USA
+Ashish Tawari
+Laboratory of Intelligent and
+Safe Automobiles
+UCSD - La Jolla, CA, USA
+Erik Murphy-Chutorian
+Laboratory of Intelligent and
+Safe Automobiles
+UCSD - La Jolla, CA, USA
+Shinko Y. Cheng
+Laboratory of Intelligent and
+Safe Automobiles
+UCSD - La Jolla, CA, USA
+Mohan Trivedi"
+8f6d05b8f9860c33c7b1a5d704694ed628db66c7,Non-linear dimensionality reduction and sparse representation models for facial analysis. (Réduction de la dimension non-linéaire et modèles de la représentations parcimonieuse pour l'analyse du visage),"Non-linear dimensionality reduction and sparse
+representation models for facial analysis
+Yuyao Zhang
+To cite this version:
+Yuyao Zhang. Non-linear dimensionality reduction and sparse representation models for facial analysis.
+Medical Imaging. INSA de Lyon, 2014. English. <NNT : 2014ISAL0019>. <tel-01127217>
+HAL Id: tel-01127217
+https://tel.archives-ouvertes.fr/tel-01127217
+Submitted on 7 Mar 2015
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entific research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destinée au dépôt et à la diffusion de documents
+scientifiques de niveau recherche, publiés ou non,
+émanant des établissements d’enseignement et de
+recherche français ou étrangers, des laboratoires"
+8f772d9ce324b2ef5857d6e0b2a420bc93961196,Facial Landmark Point Localization using Coarse-to-Fine Deep Recurrent Neural Network,"MAHPOD et al.: CFDRNN
+Facial Landmark Point Localization using
+Coarse-to-Fine Deep Recurrent Neural Network
+Shahar Mahpod, Rig Das, Emanuele Maiorana, Yosi Keller, and Patrizio Campisi,"
+8fda2f6b85c7e34d3e23927e501a4b4f7fc15b2a,Feature Selection with Annealing for Big Data Learning,"Feature Selection with Annealing for Big Data
+Learning
+Adrian Barbu, Yiyuan She, Liangjing Ding, Gary Gramajo"
+8fa3478aaf8e1f94e849d7ffbd12146946badaba,Attributes for Classifier Feedback,"Attributes for Classiﬁer Feedback
+Amar Parkash1 and Devi Parikh2
+Indraprastha Institute of Information Technology (Delhi, India)
+Toyota Technological Institute (Chicago, US)"
+8f9c37f351a91ed416baa8b6cdb4022b231b9085,Generative Adversarial Style Transfer Networks for Face Aging,"Generative Adversarial Style Transfer Networks for Face Aging
+Sveinn Palsson
+D-ITET, ETH Zurich
+Eirikur Agustsson
+D-ITET, ETH Zurich"
+8f8c0243816f16a21dea1c20b5c81bc223088594,Local Directional Number Based Classification and Recognition of Expressions Using Subspace Methods,
+8f3e3f0f97844d3bfd9e9ec566ac7a54f6931b09,"A Survey on Human Emotion Recognition Approaches, Databases and Applications","Electronic Letters on Computer Vision and Image Analysis 14(2):24-44; 2015
+A Survey on Human Emotion Recognition Approaches,
+Databases and Applications
+C.Vinola*, K.Vimaladevi†
+* Department of Computer Science and Engineering, Francis Xavier Engineering College, Tirunelveli,Tamilnadu,India
+Department of Computer Science and Engineering, P.S.R Engineering College, Sivakasi, Tamilnadu,India
+Received 7th Aug 2015; accepted 30th Nov 2015"
+8f89aed13cb3555b56fccd715753f9ea72f27f05,Attended End-to-end Architecture for Age Estimation from Facial Expression Videos,"Attended End-to-end Architecture for Age
+Estimation from Facial Expression Videos
+Wenjie Pei, Hamdi Dibeklio˘glu, Member, IEEE, Tadas Baltruˇsaitis and David M.J. Tax"
+8fd9c22b00bd8c0bcdbd182e17694046f245335f,Recognizing Facial Expressions in Videos,"Recognizing Facial Expressions in Videos
+Lin Su, Matthew Balazsi"
+8acdc4be8274e5d189fb67b841c25debf5223840,Improving clustering performance using independent component analysis and unsupervised feature learning,"Gultepe and Makrehchi
+Hum. Cent. Comput. Inf. Sci.  (2018) 8:25
+https://doi.org/10.1186/s13673-018-0148-3
+RESEARCH
+Improving clustering performance
+using independent component analysis
+nd unsupervised feature learning
+Open Access
+Eren Gultepe* and Masoud Makrehchi
+*Correspondence:
+Department of Electrical
+nd Computer Engineering,
+University of Ontario Institute
+of Technology, 2000 Simcoe
+St N, Oshawa, ON L1H 7K4,
+Canada"
+8a54f8fcaeeede72641d4b3701bab1fe3c2f730a,What do you think of my picture? Investigating factors of influence in profile images context perception,"What do you think of my picture? Investigating factors
+of influence in profile images context perception
+Filippo Mazza, Matthieu Perreira da Silva, Patrick Le Callet, Ingrid
+Heynderickx
+To cite this version:
+Filippo Mazza, Matthieu Perreira da Silva, Patrick Le Callet, Ingrid Heynderickx. What do you
+think of my picture? Investigating factors of influence in profile images context perception. Human
+Vision and Electronic Imaging XX, Mar 2015, San Francisco, United States. Proc. SPIE 9394, Hu-
+man Vision and Electronic Imaging XX, 9394, <http://spie.org/EI/conferencedetails/human-vision-
+electronic-imaging>. <10.1117/12.2082817>. <hal-01149535>
+HAL Id: hal-01149535
+https://hal.archives-ouvertes.fr/hal-01149535
+Submitted on 7 May 2015
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entific research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est"
+8aae23847e1beb4a6d51881750ce36822ca7ed0b,Comparison Between Geometry-Based and Gabor-Wavelets-Based Facial Expression Recognition Using Multi-Layer Perceptron,"Comparison Between Geometry-Based and Gabor-Wavelets-Based
+Facial Expression Recognition Using Multi-Layer Perceptron
+Zhengyou Zhang
+Shigeru Akamatsu
+ Michael Lyons
+
+ ATR Interpreting Telecommunications Research Laboratories
+-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-02, Japan
+INRIA, 2004 route des Lucioles, BP 93, F-06902 Sophia-Antipolis Cedex, France
+e-mail:"
+8a866bc0d925dfd8bb10769b8b87d7d0ff01774d,WikiArt Emotions: An Annotated Dataset of Emotions Evoked by Art,"WikiArt Emotions: An Annotated Dataset of Emotions Evoked by Art
+Saif M. Mohammad and Svetlana Kiritchenko
+National Research Council Canada"
+8a3bb63925ac2cdf7f9ecf43f71d65e210416e17,ShearFace: Efficient Extraction of Anisotropic Features for Face Recognition,"ShearFace: Efficient Extraction of Anisotropic
+Features for Face Recognition
+Mohamed Anouar Borgi1, Demetrio Labate2
+Research Groups on Intelligent Machines,
+University of Sfax,
+Sfax 3038, Tunisia
+nd  anisotropic"
+8adb2fcab20dab5232099becbd640e9c4b6a905a,Beyond Euclidean Eigenspaces: Bayesian Matching for Visual Recognition,"Beyond Euclidean Eigenspaces:
+Bayesian Matching for Visual Recognition
+Baback Moghaddam
+Alex Pentland
+Mitsubishi Electric Research Laboratory
+MIT Media Laboratory
+
+
+Cambridge, MA 
+Cambridge, MA 
+8a91ad8c46ca8f4310a442d99b98c80fb8f7625f,2D Segmentation Using a Robust Active Shape Model With the EM Algorithm,"D Segmentation Using a Robust Active
+Shape Model With the EM Algorithm
+Carlos Santiago, Jacinto C. Nascimento, Member, IEEE, and Jorge S. Marques"
+8aed6ec62cfccb4dba0c19ee000e6334ec585d70,Localizing and Visualizing Relative Attributes,"Localizing and Visualizing Relative Attributes
+Fanyi Xiao and Yong Jae Lee"
+8a336e9a4c42384d4c505c53fb8628a040f2468e,Detecting Visually Observable Disease Symptoms from Faces,"Wang and Luo EURASIP Journal on Bioinformatics
+nd Systems Biology  (2016) 2016:13
+DOI 10.1186/s13637-016-0048-7
+R ES EAR CH
+Detecting Visually Observable Disease
+Symptoms from Faces
+Kuan Wang* and Jiebo Luo
+Open Access"
+7ed3b79248d92b255450c7becd32b9e5c834a31e,L 1-regularized Logistic Regression Stacking and Transductive CRF Smoothing for Action Recognition in Video,"L1-regularized Logistic Regression Stacking and Transductive CRF Smoothing
+for Action Recognition in Video
+Svebor Karaman
+University of Florence
+Lorenzo Seidenari
+University of Florence
+Andrew D. Bagdanov
+University of Florence
+Alberto Del Bimbo
+University of Florence"
+7e8016bef2c180238f00eecc6a50eac473f3f138,Immersive Interactive Data Mining and Machine Learning Algorithms for Big Data Visualization,"TECHNISCHE UNIVERSIT ¨AT M ¨UNCHEN
+Lehrstuhl f¨ur Mensch-Maschine-Kommunikation
+Immersive Interactive Data Mining and Machine
+Learning Algorithms for Big Data Visualization
+Mohammadreza Babaee
+Vollst¨andiger Abdruck der von der Fakult¨at f¨ur Elektrotechnik und Informationstechnik
+der Technischen Universit¨at M¨unchen zur Erlangung des akademischen Grades eines
+Doktor-Ingenieurs (Dr.-Ing.)
+genehmigten Dissertation.
+Vorsitzender:
+Univ.-Prof. Dr. sc.techn. Andreas Herkersdorf
+Pr¨ufer der Dissertation:
+. Univ.-Prof. Dr.-Ing. habil. Gerhard Rigoll
+. Univ.-Prof. Dr.-Ing. habil. Dirk Wollherr
+. Prof. Dr. Mihai Datcu
+Die Dissertation wurde am 13.08.2015 bei der Technischen Universit¨at M¨unchen eingerei-
+ht und durch die Fakult¨at f¨ur Elektrotechnik und Informationstechnik am 16.02.2016
+ngenommen."
+7e3367b9b97f291835cfd0385f45c75ff84f4dc5,Improved local binary pattern based action unit detection using morphological and bilateral filters,"Improved Local Binary Pattern Based Action Unit Detection Using
+Morphological and Bilateral Filters
+Anıl Y¨uce1, Matteo Sorci2 and Jean-Philippe Thiran1
+Signal Processing Laboratory (LTS5)
+´Ecole Polytechnique F´ed´erale de Lausanne,
+Switzerland
+nViso SA
+Lausanne, Switzerland"
+7ef0cc4f3f7566f96f168123bac1e07053a939b2,Triangular Similarity Metric Learning: a Siamese Architecture Approach. ( L'apprentissage de similarité triangulaire en utilisant des réseaux siamois),"Triangular Similarity Metric Learning: a Siamese
+Architecture Approach
+Lilei Zheng
+To cite this version:
+Lilei Zheng. Triangular Similarity Metric Learning: a Siamese Architecture Approach. Com-
+puter Science [cs]. UNIVERSITE DE LYON, 2016. English. <NNT : 2016LYSEI045>. <tel-
+01314392>
+HAL Id: tel-01314392
+https://hal.archives-ouvertes.fr/tel-01314392
+Submitted on 11 May 2016
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entiﬁc research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destin´ee au d´epˆot et `a la diffusion de documents
+scientiﬁques de niveau recherche, publi´es ou non,
+´emanant des ´etablissements d’enseignement et de"
+7ee53d931668fbed1021839db4210a06e4f33190,What If We Do Not have Multiple Videos of the Same Action? &#x2014; Video Action Localization Using Web Images,"What if we do not have multiple videos of the same action? —
+Video Action Localization Using Web Images
+Center for Research in Computer Vision (CRCV), University of Central Florida (UCF)
+Waqas Sultani, Mubarak Shah"
+7e9df45ece7843fe050033c81014cc30b3a8903a,Audio-visual intent-to-speak detection for human-computer interaction,"AUDIO-VISUAL INTENT-TO-SPEAK DETECTION FOR HUMAN-COMPUTER
+INTERACTION
+Philippe de Cuetos
+Institut Eurecom
+	, route des Cr^etes, BP 	
+
+Chalapathy Neti, Andrew W. Senior
+IBM T.J. Watson Research Center
+Yorktown Heights, NY 
+cneti,aws"
+7ebd323ddfe3b6de8368c4682db6d0db7b70df62,Location-based Face Recognition Using Smart Mobile Device Sensors,"Proceedings of the International Conference on Computer and Information Science and Technology
+Ottawa, Ontario, Canada, May 11 – 12, 2015
+Paper No. 111
+Location-based Face Recognition Using Smart Mobile Device
+Sensors
+Nina Taherimakhsousi, Hausi A. Müller
+Department of Computer Science
+University of Victoria, Victoria, Canada"
+7ed6ff077422f156932fde320e6b3bd66f8ffbcb,State of 3D Face Biometrics for Homeland Security Applications,"State of 3D Face Biometrics for Homeland Security Applications
+Anshuman Razdan1, Gerald Farin2, Myung Soo-Bae3 and Mahesh
+Chaudhari4"
+7e507370124a2ac66fb7a228d75be032ddd083cc,Dynamic Pose-Robust Facial Expression Recognition by Multi-View Pairwise Conditional Random Forests,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TAFFC.2017.2708106, IEEE
+Transactions on Affective Computing
+Dynamic Pose-Robust Facial Expression
+Recognition by Multi-View Pairwise Conditional
+Random Forests
+Arnaud Dapogny1 and Kevin Bailly1 and S´everine Dubuisson1
+Sorbonne Universit´es, UPMC Univ Paris 06
+CNRS, UMR 7222, F-75005, Paris, France"
+10e7dd3bbbfbc25661213155e0de1a9f043461a2,Cross Euclidean-to-Riemannian Metric Learning with Application to Face Recognition from Video,"Cross Euclidean-to-Riemannian Metric Learning
+with Application to Face Recognition from Video
+Zhiwu Huang, Member, IEEE, Ruiping Wang, Member, IEEE, Shiguang Shan, Senior Member, IEEE,
+Luc Van Gool, Member, IEEE and Xilin Chen, Fellow, IEEE"
+10ce3a4724557d47df8f768670bfdd5cd5738f95,Fisher Light-Fields for Face Recognition across Pose and Illumination,"Fihe igh	Fie
+Ac e ad 
+Ra
+The Rbic i	e Caegie e
+5000 Fbe Ave	e ib	gh A 15213
+Abac.  ay face ecgii ak he e ad i
+dii f he be ad ga
+	
+di(cid:11)ee e ad 	de a di(cid:11)ee i
+ecgii a
+	bjec ca	ed a abiay e ad 	de abiay i
+d ay 	be f be iage agai ca	ed a abiay e ad
+de abiay i
+Fihe 
+iage. achig bewee he be ad ga
+he Fihe 
+d	ci
+ ay face ecgii ceai he e f he be ad ga
+di(cid:11)ee. The ga
+The a
+102e374347698fe5404e1d83f441630b1abf62d9,Facial Image Analysis for Fully Automatic Prediction of Difficult Endotracheal Intubation,"Facial Image Analysis for Fully-Automatic
+Prediction of Difﬁcult Endotracheal Intubation
+Gabriel L. Cuendet, Student Member, IEEE, Patrick Schoettker, Anıl Y¨uce Student Member, IEEE, Matteo Sorci,
+Hua Gao, Christophe Perruchoud, Jean-Philippe Thiran, Senior Member, IEEE"
+10e0e6f1ec00b20bc78a5453a00c792f1334b016,Temporal Selective Max Pooling Towards Practical Face Recognition,"Pose-Selective Max Pooling for Measuring Similarity
+Xiang Xiang1 and Trac D. Tran2
+Dept. of Computer Science
+Dept. of Electrical & Computer Engineering
+Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA"
+100641ed8a5472536dde53c1f50fa2dd2d4e9be9,Visual attributes for enhanced human-machine communication,"Visual Attributes for Enhanced Human-Machine Communication*
+Devi Parikh1"
+101569eeef2cecc576578bd6500f1c2dcc0274e2,Multiaccuracy: Black-Box Post-Processing for Fairness in Classification,"Multiaccuracy: Black-Box Post-Processing for Fairness in
+Michael P. Kim∗†
+Classiﬁcation
+Amirata Ghorbani∗
+James Zou"
+106732a010b1baf13c61d0994552aee8336f8c85,Expanded Parts Model for Semantic Description of Humans in Still Images,"Expanded Parts Model for Semantic Description
+of Humans in Still Images
+Gaurav Sharma, Member, IEEE, Fr´ed´eric Jurie, and Cordelia Schmid, Fellow, IEEE"
+102b27922e9bd56667303f986404f0e1243b68ab,Multiscale recurrent regression networks for face alignment,"Wang et al. Appl Inform  (2017) 4:13
+DOI 10.1186/s40535-017-0042-5
+RESEARCH
+Multiscale recurrent regression networks
+for face alignment
+Open Access
+Caixun Wang1,2,3, Haomiao Sun1,2,3, Jiwen Lu1,2,3*, Jianjiang Feng1,2,3 and Jie Zhou1,2,3
+*Correspondence:
+State Key Lab of Intelligent
+Technologies and Systems,
+Beijing 100084, People’s
+Republic of China
+Full list of author information
+is available at the end of the
+rticle"
+10fcbf30723033a5046db791fec2d3d286e34daa,On-Line Cursive Handwriting Recognition: A Survey of Methods and Performances,"On-Line Cursive Handwriting Recognition: A Survey of Methods
+nd Performances
+Dzulkifli Mohamad* ,  2Muhammad Faisal Zafar*,    and  3Razib M. Othman*
+*Faculty of Computer Science & Information Systems, Universiti Teknologi Malaysia (UTM) , 81310
+Skudai, Johor, Malaysia."
+108b2581e07c6b7ca235717c749d45a1fa15bb24,Using Stereo Matching with General Epipolar Geometry for 2D Face Recognition across Pose,"Using Stereo Matching with General Epipolar
+Geometry for 2D Face Recognition
+cross Pose
+Carlos D. Castillo, Student Member, IEEE, and
+David W. Jacobs, Member, IEEE"
+10d334a98c1e2a9e96c6c3713aadd42a557abb8b,Scene Text Recognition Using Part-Based Tree-Structured Character Detection,"Scene Text Recognition using Part-based Tree-structured Character Detection
+Cunzhao Shi, Chunheng Wang, Baihua Xiao, Yang Zhang, Song Gao and Zhong Zhang
+State Key Laboratory of Management and Control for Complex Systems, CASIA, Beijing, China"
+1048c753e9488daa2441c50577fe5fdba5aa5d7c,Recognising faces in unseen modes: A tensor based approach,"Recognising faces in unseen modes: a tensor based approach
+Santu Rana, Wanquan Liu, Mihai Lazarescu and Svetha Venkatesh
+{santu.rana, wanquan, m.lazarescu,
+Dept. of Computing, Curtin University of Technology
+GPO Box U1987, Perth, WA 6845, Australia."
+19841b721bfe31899e238982a22257287b9be66a,Recurrent Neural Networks,"Published as a conference paper at ICLR 2018
+SKIP RNN: LEARNING TO SKIP STATE UPDATES IN
+RECURRENT NEURAL NETWORKS
+V´ıctor Campos∗†, Brendan Jou‡, Xavier Gir´o-i-Nieto§, Jordi Torres†, Shih-Fu ChangΓ
+Barcelona Supercomputing Center, ‡Google Inc,
+§Universitat Polit`ecnica de Catalunya, ΓColumbia University
+{victor.campos,"
+192723085945c1d44bdd47e516c716169c06b7c0,Vision and Attention Theory Based Sampling for Continuous Facial Emotion Recognition,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation
+Vision and Attention Theory Based Sampling
+for Continuous Facial Emotion Recognition
+Albert C. Cruz, Student Member, IEEE, Bir Bhanu, Fellow, IEEE, and
+Ninad S. Thakoor, Member, IEEE"
+19fb5e5207b4a964e5ab50d421e2549ce472baa8,Online emotional facial expression dictionary,"International Conference on Computer Systems and Technologies - CompSysTech’14
+Online Emotional Facial Expression Dictionary
+Léon Rothkrantz"
+1962e4c9f60864b96c49d85eb897141486e9f6d1,Locality preserving embedding for face and handwriting digital recognition,"Neural Comput & Applic (2011) 20:565–573
+DOI 10.1007/s00521-011-0577-7
+O R I G I N A L A R T I C L E
+Locality preserving embedding for face and handwriting digital
+recognition
+Zhihui Lai • MingHua Wan • Zhong Jin
+Received: 3 December 2008 / Accepted: 11 March 2011 / Published online: 1 April 2011
+Ó Springer-Verlag London Limited 2011
+supervised manifold
+the local sub-manifolds."
+191674c64f89c1b5cba19732869aa48c38698c84,Face Image Retrieval Using Attribute - Enhanced Sparse Codewords,"International Journal of Advanced Technology in Engineering and Science                 www.ijates.com
+Volume No.03, Issue No. 03, March 2015                                                   ISSN (online): 2348 – 7550
+FACE IMAGE RETRIEVAL USING ATTRIBUTE -
+ENHANCED SPARSE CODEWORDS
+E.Sakthivel1 , M.Ashok kumar2
+PG scholar, Communication Systems, Adhiyamaan College of Engineeing,Hosur,(India)
+Asst. Prof., Electronics And Communication Engg., Adhiyamaan College of Engg.,Hosur,(India)"
+19af008599fb17bbd9b12288c44f310881df951c,Discriminative Local Sparse Representations for Robust Face Recognition,"Discriminative Local Sparse Representations for
+Robust Face Recognition
+Yi Chen, Umamahesh Srinivas, Thong T. Do, Vishal Monga, and Trac D. Tran"
+19296e129c70b332a8c0a67af8990f2f4d4f44d1,Is that you? Metric learning approaches for face identification,"Metric Learning Approaches for Face Identiﬁcation
+Is that you?
+M. Guillaumin, J. Verbeek and C. Schmid
+LEAR team, INRIA Rhˆone-Alpes, France
+Supplementary Material"
+19666b9eefcbf764df7c1f5b6938031bcf777191,Group Component Analysis for Multiblock Data: Common and Individual Feature Extraction,"Group Component Analysis for Multi-block Data:
+Common and Individual Feature Extraction
+Guoxu Zhou, Andrzej Cichocki Fellow, IEEE, Yu Zhang, and Danilo Mandic Fellow, IEEE"
+19c0c7835dba1a319b59359adaa738f0410263e8,Natural Image Statistics and Low-Complexity Feature Selection,"Natural Image Statistics and
+Low-Complexity Feature Selection
+Manuela Vasconcelos and Nuno Vasconcelos, Senior Member, IEEE"
+19d583bf8c5533d1261ccdc068fdc3ef53b9ffb9,FaceNet: A unified embedding for face recognition and clustering,"FaceNet: A Uniﬁed Embedding for Face Recognition and Clustering
+Florian Schroff
+Dmitry Kalenichenko
+James Philbin
+Google Inc.
+Google Inc.
+Google Inc."
+1910f5f7ac81d4fcc30284e88dee3537887acdf3,Semantic Based Hypergraph Reranking Model for Web Image Search,"Volume 6, Issue 5, May 2016                                   ISSN: 2277 128X
+International Journal of Advanced Research in
+Computer Science and Software Engineering
+Research Paper
+Available online at: www.ijarcsse.com
+Semantic Based Hypergraph Reranking Model for Web
+Image Search
+Amol Darkunde, 2Manoj Jalan, 3Yelmar Mahesh, 4Shivadatta Shinde, 5Dnyanda Patil
+, 2, 3, 4 B. E.  Dept of CSE, 5 Asst. Prof. Dept of CSE
+, 2, 3, 4, 5 Dr.D.Y.Patil College of Engineering, Pune, Maharashtra, India"
+197c64c36e8a9d624a05ee98b740d87f94b4040c,Regularized Greedy Column Subset Selection,"Regularized Greedy Column Subset Selection
+Bruno Ordozgoiti*a, Alberto Mozoa, Jes´us Garc´ıa L´opez de Lacalleb
+Department of Computer Systems, Universidad Polit´ecnica de Madrid
+Department of Applied Mathematics, Universidad Polit´ecnica de Madrid"
+19d4855f064f0d53cb851e9342025bd8503922e2,Learning SURF Cascade for Fast and Accurate Object Detection,"Learning SURF Cascade for Fast and Accurate Object Detection
+Jianguo Li, Yimin Zhang
+Intel Labs China"
+4c6e1840451e1f86af3ef1cb551259cb259493ba,Hand Posture Dataset Creation for Gesture Recognition,"HAND POSTURE DATASET CREATION FOR GESTURE
+RECOGNITION
+Instituto de Sistemas Inteligentes y Aplicaciones Numericas en Ingenieria
+Luis Anton-Canalis
+Campus Universitario de Taﬁra, 35017 Gran Canaria, Spain
+Elena Sanchez-Nielsen
+Departamento de E.I.O. y Computacion
+8271 Universidad de La Laguna, Spain
+Keywords:
+Image understanding, Gesture recognition, Hand dataset."
+4c815f367213cc0fb8c61773cd04a5ca8be2c959,Facial expression recognition using curvelet based local binary patterns,"978-1-4244-4296-6/10/$25.00 ©2010 IEEE
+ICASSP 2010"
+4c4e49033737467e28aa2bb32f6c21000deda2ef,Improving Landmark Localization with Semi-Supervised Learning,"Improving Landmark Localization with Semi-Supervised Learning
+Sina Honari1∗, Pavlo Molchanov2, Stephen Tyree2, Pascal Vincent1,4,5, Christopher Pal1,3, Jan Kautz2
+MILA-University of Montreal, 2NVIDIA, 3Ecole Polytechnique of Montreal, 4CIFAR, 5Facebook AI Research.
+{honaris,
+{pmolchanov, styree,"
+4c4236b62302957052f1bbfbd34dbf71ac1650ec,Semi-supervised face recognition with LDA self-training,"SEMI-SUPERVISED FACE RECOGNITION WITH LDA SELF-TRAINING
+Xuran Zhao, Nicholas Evans and Jean-Luc Dugelay
+Multimedia Communications Department, EURECOM
+229 Route des Crêtes , BP 193, F-06560 Sophia-Antipolis Cedex, France
+{zhaox, evans,"
+4c81c76f799c48c33bb63b9369d013f51eaf5ada,Multi-modal Score Fusion and Decision Trees for Explainable Automatic Job Candidate Screening from Video CVs,"Multi-modal Score Fusion and Decision Trees for Explainable Automatic Job
+Candidate Screening from Video CVs
+Heysem Kaya1, Furkan G¨urpınar2, and Albert Ali Salah2
+Department of Computer Engineering, Namık Kemal University, Tekirda˘g, Turkey
+Department of Computer Engineering, Bo˘gazic¸i University, Istanbul, Turkey"
+4c1ce6bced30f5114f135cacf1a37b69bb709ea1,Gaze direction estimation by component separation for recognition of Eye Accessing Cues,"Gaze Direction Estimation by Component Separation for
+Recognition of Eye Accessing Cues
+Ruxandra Vrˆanceanu
+Image Processing and Analysis Laboratory
+University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313
+Corneliu Florea
+Image Processing and Analysis Laboratory
+University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313
+Laura Florea
+Image Processing and Analysis Laboratory
+University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313
+Constantin Vertan
+Image Processing and Analysis Laboratory
+University ”Politehnica” of Bucharest, Romania, Address Splaiul Independent¸ei 313"
+2661f38aaa0ceb424c70a6258f7695c28b97238a,Multilayer Architectures for Facial Action Unit Recognition,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 42, NO. 4, AUGUST 2012
+Multilayer Architectures for Facial
+Action Unit Recognition
+Tingfan Wu, Nicholas J. Butko, Paul Ruvolo, Jacob Whitehill, Marian S. Bartlett, and Javier R. Movellan"
+264a84f4d27cd4bca94270620907cffcb889075c,Deep motion features for visual tracking,"Deep Motion Features for Visual Tracking
+Susanna Gladh, Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg
+Computer Vision Laboratory, Department of Electrical Engineering, Link¨oping University, Sweden"
+26a72e9dd444d2861298d9df9df9f7d147186bcd,Collecting and annotating the large continuous action dataset,"DOI 10.1007/s00138-016-0768-4
+ORIGINAL PAPER
+Collecting and annotating the large continuous action dataset
+Daniel Paul Barrett1 · Ran Xu2 · Haonan Yu1 · Jeffrey Mark Siskind1
+Received: 18 June 2015 / Revised: 18 April 2016 / Accepted: 22 April 2016 / Published online: 21 May 2016
+© The Author(s) 2016. This article is published with open access at Springerlink.com"
+266766818dbc5a4ca1161ae2bc14c9e269ddc490,Boosting a Low-Cost Smart Home Environment with Usage and Access Control Rules,"Article
+Boosting a Low-Cost Smart Home Environment with
+Usage and Access Control Rules
+Paolo Barsocchi * ID , Antonello Calabrò, Erina Ferro, Claudio Gennaro ID and Eda Marchetti and
+Claudio Vairo
+Institute of Information Science and Technologies of CNR (CNR-ISTI)-Italy, 56124 Pisa, Italy;
+(A.C.); (E.F.); (C.G.);
+(E.M.); (C.V.)
+* Correspondence: Tel.: +39-050-315-2965
+Received: 27 April 2018; Accepted: 31 May 2018; Published: 8 June 2018"
+265af79627a3d7ccf64e9fe51c10e5268fee2aae,A Mixture of Transformed Hidden Markov Models for Elastic Motion Estimation,"A Mixture of Transformed Hidden Markov
+Models for Elastic Motion Estimation
+Huijun Di, Linmi Tao, and Guangyou Xu, Senior Member, IEEE"
+26af867977f90342c9648ccf7e30f94470d40a73,Joint Gender and Face Recognition System for RGB-D Images with Texture and DCT Features,"IJIRST –International Journal for Innovative Research in Science & Technology| Volume 3 | Issue 04 | September 2016
+ISSN (online): 2349-6010
+Joint Gender and Face Recognition System for
+RGB-D Images with Texture and DCT Features
+Jesny Antony
+PG Student
+Department of Computer Science & Information Systems
+Federal Institute of Science and Technology,  Mookkannoor
+PO, Angamaly, Ernakulam, Kerala 683577, India
+Prasad J. C.
+Associate Professor
+Department of Computer Science & Engineering
+Federal Institute of Science and Technology,  Mookkannoor
+PO, Angamaly, Ernakulam, Kerala 683577, India"
+26c884829897b3035702800937d4d15fef7010e4,Facial Expression Recognition by Supervised Independent Component Analysis Using MAP Estimation,"IEICE TRANS. INF. & SYST., VOL.Exx–??, NO.xx XXXX 200x
+PAPER
+Facial Expression Recognition by Supervised Independent
+Component Analysis using MAP Estimation
+Fan CHEN
+, Nonmember and Kazunori KOTANI
+, Member
+SUMMARY Permutation ambiguity of the classical Inde-
+pendent Component Analysis (ICA) may cause problems in fea-
+ture extraction for pattern classiﬁcation. Especially when only a
+small subset of components is derived from data, these compo-
+nents may not be most distinctive for classiﬁcation, because ICA
+is an unsupervised method. We include a selective prior for de-
+mixing coef‌f‌icients into the classical ICA to alleviate the problem.
+Since the prior is constructed upon the classiﬁcation information
+from the training data, we refer to the proposed ICA model with
+selective prior as a supervised ICA (sICA). We formulated the
+learning rule for sICA by taking a Maximum a Posteriori (MAP)
+scheme and further derived a ﬁxed point algorithm for learning
+the de-mixing matrix. We investigate the performance of sICA"
+26ad6ceb07a1dc265d405e47a36570cb69b2ace6,Neural Correlates of Cross-Cultural Adaptation,"RESEARCH AND EXPLOR ATORY
+DEVELOPMENT DEPARTMENT
+REDD-2015-384
+Neural Correlates of Cross-Cultural
+How to Improve the Training and Selection for
+Military Personnel Involved in Cross-Cultural
+Operating Under Grant #N00014-12-1-0629/113056
+Adaptation
+September, 2015
+Interactions
+Jonathon Kopecky
+Jason Spitaletta
+Mike Wolmetz
+Alice Jackson
+Prepared for:
+Office of Naval Research"
+26437fb289cd7caeb3834361f0cc933a02267766,Innovative Assessment Technologies: Comparing ‘Face-to-Face’ and Game-Based Development of Thinking Skills in Classroom Settings,"012 International Conference on Management and Education Innovation
+IPEDR vol.37 (2012) © (2012) IACSIT Press, Singapore
+Innovative Assessment Technologies: Comparing ‘Face-to-Face’ and
+Game-Based Development of Thinking Skills in Classroom Settings
+Gyöngyvér Molnár 1 + and András Lőrincz 2
+University of Szeged, 2 Eötvös Loránd University"
+26e570049aaedcfa420fc8c7b761bc70a195657c,Hybrid Facial Regions Extraction for Micro-expression Recognition System,"J Sign Process Syst
+DOI 10.1007/s11265-017-1276-0
+Hybrid Facial Regions Extraction for Micro-expression
+Recognition System
+Sze-Teng Liong1,2,3 · John See4 · Raphael C.-W. Phan2 · KokSheik Wong5 ·
+Su-Wei Tan2
+Received: 2 February 2016 / Revised: 20 October 2016 / Accepted: 10 August 2017
+© Springer Science+Business Media, LLC 2017"
+21ef129c063bad970b309a24a6a18cbcdfb3aff5,Individual and Inter-related Action Unit Detection in Videos for Affect Recognition,"POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCESacceptée sur proposition du jury:Dr J.-M. Vesin, président du juryProf. J.-Ph. Thiran, Prof. D. Sander, directeurs de thèseProf. M. F. Valstar, rapporteurProf. H. K. Ekenel, rapporteurDr S. Marcel, rapporteurIndividual and Inter-related Action Unit Detection in Videos for Affect RecognitionTHÈSE NO 6837 (2016)ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNEPRÉSENTÉE LE 19 FÉVRIER 2016À LA FACULTÉ DES SCIENCES ET TECHNIQUES DE L'INGÉNIEURLABORATOIRE DE TRAITEMENT DES SIGNAUX 5PROGRAMME DOCTORAL EN GÉNIE ÉLECTRIQUE Suisse2016PARAnıl YÜCE"
+218b2c5c9d011eb4432be4728b54e39f366354c1,Enhancing Training Collections for Image Annotation: An Instance-Weighted Mixture Modeling Approach,"Enhancing Training Collections for Image
+Annotation: An Instance-Weighted Mixture
+Modeling Approach
+Neela Sawant, Student Member, IEEE, James Z. Wang, Senior Member, IEEE, Jia Li, Senior Member, IEEE."
+21a2f67b21905ff6e0afa762937427e92dc5aa0b,Extra Facial Landmark Localization via Global Shape Reconstruction,"Hindawi
+Computational Intelligence and Neuroscience
+Volume 2017, Article ID 8710492, 13 pages
+https://doi.org/10.1155/2017/8710492
+Research Article
+Extra Facial Landmark Localization via
+Global Shape Reconstruction
+Shuqiu Tan, Dongyi Chen, Chenggang Guo, and Zhiqi Huang
+School of Automation Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave,
+West Hi-Tech Zone, Chengdu 611731, China
+Correspondence should be addressed to Dongyi Chen;
+Received 4 January 2017; Revised 26 March 2017; Accepted 4 April 2017; Published 23 April 2017
+Academic Editor: Elio Masciari
+Copyright © 2017 Shuqiu Tan et al. This is an open access article distributed under the Creative Commons Attribution License,
+which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
+Localizing facial landmarks is a popular topic in the field of face analysis. However, problems arose in practical applications such
+s handling pose variations and partial occlusions while maintaining moderate training model size and computational efficiency
+still challenges current solutions. In this paper, we present a global shape reconstruction method for locating extra facial landmarks
+omparing to facial landmarks used in the training phase. In the proposed method, the reduced configuration of facial landmarks
+is first decomposed into corresponding sparse coefficients. Then explicit face shape correlations are exploited to regress between"
+2162654cb02bcd10794ae7e7d610c011ce0fb51b,Joint gaze-correction and beautification of DIBR-synthesized human face via dual sparse coding,"978-1-4799-5751-4/14/$31.00 ©2014 IEEE
+http://www.skype.com/
+http://www.google.com/hangouts/
+tiﬁcation, sparse coding"
+21f3c5b173503185c1e02a3eb4e76e13d7e9c5bc,Rotation Invariant Real-time Face Detection and Recognition System,"m a s s a c h u s e t t s   i n s t i t u t e   o f
+t e c h n o l o g y   — a r t i f i c i a l   i n t e l l i g e n c e   l a b o r a t o r y
+Rotation Invariant Real-time
+Face Detection and
+Recognition System
+Purdy Ho
+AI Memo 2001-010
+CBCL Memo 197
+May 31, 2001
+© 2 0 0 1   m a s s a c h u s e t t s   i n s t i t u t e   o f
+t e c h n o l o g y, c a m b r i d g e , m a   0 2 1 3 9   u s a   —   w w w. a i . m i t . e d u"
+21bd9374c211749104232db33f0f71eab4df35d5,Integrating facial makeup detection into multimodal biometric user verification system,"Integrating Facial Makeup Detection Into
+Multimodal Biometric User Veriﬁcation System
+Ekberjan Derman*
+CuteSafe Technology Inc.
+Gebze, Kocaeli, Turkey
+Chiara Galdi, Jean-Luc Dugelay
+Eurecom Digital Security Department
+06410 Biot, France
+{chiara.galdi,"
+214db8a5872f7be48cdb8876e0233efecdcb6061,Semantic-Aware Co-Indexing for Image Retrieval,"Semantic-aware Co-indexing for Image Retrieval
+Shiliang Zhang2, Ming Yang1, Xiaoyu Wang1, Yuanqing Lin1, Qi Tian2
+NEC Laboratories America, Inc.
+Dept. of CS, Univ. of Texas at San Antonio
+Cupertino, CA 95014
+San Antonio, TX 78249"
+214ac8196d8061981bef271b37a279526aab5024,Face Recognition Using Smoothed High-Dimensional Representation,"Face Recognition Using Smoothed High-Dimensional
+Representation
+Juha Ylioinas, Juho Kannala, Abdenour Hadid, and Matti Pietik¨ainen
+Center for Machine Vision Research, PO Box 4500,
+FI-90014 University of Oulu, Finland"
+213a579af9e4f57f071b884aa872651372b661fd,Automatic and Efficient Human Pose Estimation for Sign Language Videos,"Int J Comput Vis
+DOI 10.1007/s11263-013-0672-6
+Automatic and Efﬁcient Human Pose Estimation for Sign
+Language Videos
+James Charles · Tomas Pﬁster · Mark Everingham ·
+Andrew Zisserman
+Received: 4 February 2013 / Accepted: 29 October 2013
+© Springer Science+Business Media New York 2013"
+21626caa46cbf2ae9e43dbc0c8e789b3dbb420f1,Transductive VIS-NIR face matching,"978-1-4673-2533-2/12/$26.00 ©2012 IEEE
+ICIP 2012"
+4d49c6cff198cccb21f4fa35fd75cbe99cfcbf27,Topological principal component analysis for face encoding and recognition,"Topological Principal Component Analysis for
+face encoding and recognition
+Albert Pujol , Jordi Vitri(cid:18)a, Felipe Lumbreras,
+Juan J. Villanueva
+Computer Vision Center and Departament d’Inform(cid:18)atica, Edi(cid:12)ci O, Universitat
+Aut(cid:18)onoma de Barcelona 
+4da735d2ed0deeb0cae4a9d4394449275e316df2,"The rhythms of head, eyes and hands at intersections","Gothenburg, Sweden, June 19-22, 2016
+978-1-5090-1820-8/16/$31.00 ©2016 IEEE"
+4d530a4629671939d9ded1f294b0183b56a513ef,Facial Expression Classification Method Based on Pseudo Zernike Moment and Radial Basis Function Network,"International Journal of Machine Learning and Computing, Vol. 2, No. 4, August 2012
+Facial Expression Classification Method Based on Pseudo
+Zernike Moment and Radial Basis Function Network
+Tran Binh Long, Le Hoang Thai, and Tran Hanh"
+4d2975445007405f8cdcd74b7fd1dd547066f9b8,Image and Video Processing for Affective Applications,"Image and Video Processing
+for Affective Applications
+Maja Pantic and George Caridakis"
+4db9e5f19366fe5d6a98ca43c1d113dac823a14d,"Are 1, 000 Features Worth A Picture? Combining Crowdsourcing and Face Recognition to Identify Civil War Soldiers","Combining Crowdsourcing and Face Recognition to Identify Civil War Soldiers
+Are 1,000 Features Worth A Picture?
+Vikram Mohanty, David Thames, Kurt Luther
+Department of Computer Science and Center for Human-Computer Interaction
+Virginia Tech, Arlington, VA, USA"
+4dd71a097e6b3cd379d8c802460667ee0cbc8463,Real-time multi-view facial landmark detector learned by the structured output SVM,"Real-time Multi-view Facial Landmark Detector
+Learned by the Structured Output SVM
+Michal Uˇriˇc´aˇr1, Vojtˇech Franc1, Diego Thomas2, Akihiro Sugimoto2, and V´aclav Hlav´aˇc1
+Center for Machine Perception, Department of Cybernetics, Faculty of Electrical Engineering, Czech
+Technical University in Prague, 166 27 Prague 6, Technick´a 2 Czech Republic
+National Institute of Informatics, Tokyo, Japan"
+4d7e1eb5d1afecb4e238ba05d4f7f487dff96c11,Largest center-specific margin for dimension reduction,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE
+ICASSP 2017"
+4d6ad0c7b3cf74adb0507dc886993e603c863e8c,Human Activity Recognition Based on Wearable Sensor Data : A Standardization of the State-ofthe-Art,"Human Activity Recognition Based on Wearable
+Sensor Data: A Standardization of the
+State-of-the-Art
+Artur Jord˜ao, Antonio C. Nazare Jr., Jessica Sena and William Robson Schwartz
+Smart Surveillance Interest Group, Computer Science Department
+Universidade Federal de Minas Gerais, Brazil
+Email: {arturjordao, antonio.nazare, jessicasena,"
+4dca3d6341e1d991c902492952e726dc2a443d1c,Learning towards Minimum Hyperspherical Energy,"Learning towards Minimum Hyperspherical Energy
+Weiyang Liu1,*, Rongmei Lin2,*, Zhen Liu1,*, Lixin Liu3,*, Zhiding Yu4, Bo Dai1,5, Le Song1,6
+Georgia Institute of Technology 2Emory University
+South China University of Technology 4NVIDIA 5Google Brain 6Ant Financial"
+4d0ef449de476631a8d107c8ec225628a67c87f9,Face system evaluation toolkit: Recognition is harder than it seems,"© 2010 IEEE. Personal use of this material is permitted. Permission from IEEE
+must  be  obtained  for  all  other  uses,  in  any  current  or  future  media,  including
+reprinting/republishing  this  material  for  advertising  or  promotional  purposes,
+reating  new  collective  works,  for  resale  or  redistribution  to  servers  or  lists,  or
+reuse of any copyrighted component of this work in other works.
+Pre-print of article that appeared at BTAS 2010.
+The published article can be accessed from:
+http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5634517"
+4d47261b2f52c361c09f7ab96fcb3f5c22cafb9f,Deep multi-frame face super-resolution,"Deep multi-frame face super-resolution
+Evgeniya Ustinova, Victor Lempitsky
+October 17, 2017"
+4df3143922bcdf7db78eb91e6b5359d6ada004d2,The Chicago face database: A free stimulus set of faces and norming data.,"Behav Res (2015) 47:1122–1135
+DOI 10.3758/s13428-014-0532-5
+The Chicago face database: A free stimulus set of faces
+nd norming data
+Debbie S. Ma & Joshua Correll & Bernd Wittenbrink
+Published online: 13 January 2015
+# Psychonomic Society, Inc. 2015"
+75879ab7a77318bbe506cb9df309d99205862f6c,Analysis of emotion recognition from facial expressions using spatial and transform domain methods,"Analysis Of Emotion Recognition From Facial
+Expressions Using Spatial And Transform Domain
+Methods
+Ms. P. Suja* and Dr. Shikha Tripathi"
+75503aff70a61ff4810e85838a214be484a674ba,Improved facial expression recognition via uni-hyperplane classification,"Improved Facial Expression Recognition via Uni-Hyperplane Classiﬁcation
+S.W. Chew∗, S. Lucey†, P. Lucey‡, S. Sridharan∗, and J.F. Cohn‡"
+75308067ddd3c53721430d7984295838c81d4106,Rapid Facial Reactions in Response to Facial Expressions of Emotion Displayed by Real Versus Virtual Faces,"Article
+Rapid Facial Reactions
+in Response to Facial
+Expressions of Emotion
+Displayed by Real Versus
+Virtual Faces
+i-Perception
+018 Vol. 9(4), 1–18
+! The Author(s) 2018
+DOI: 10.1177/2041669518786527
+journals.sagepub.com/home/ipe
+Leonor Philip, Jean-Claude Martin and Ce´ line Clavel
+LIMSI, CNRS, University of Paris-Sud, Orsay, France"
+759a3b3821d9f0e08e0b0a62c8b693230afc3f8d,Attribute and simile classifiers for face verification,"Attribute and Simile Classiﬁers for Face Veriﬁcation
+Neeraj Kumar
+Alexander C. Berg
+Peter N. Belhumeur
+Columbia University∗
+Shree K. Nayar"
+75859ac30f5444f0d9acfeff618444ae280d661d,Multibiometric Cryptosystems Based on Feature-Level Fusion,"Multibiometric Cryptosystems based on Feature
+Level Fusion
+Abhishek Nagar, Student Member, IEEE, Karthik Nandakumar, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
+758d7e1be64cc668c59ef33ba8882c8597406e53,"AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild","IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
+AffectNet: A Database for Facial Expression,
+Valence, and Arousal Computing in the Wild
+Ali Mollahosseini, Student Member, IEEE, Behzad Hasani, Student Member, IEEE,
+nd Mohammad H. Mahoor, Senior Member, IEEE"
+7553fba5c7f73098524fbb58ca534a65f08e91e7,A Practical Approach for Determination of Human Gender & Age,"Harpreet Kaur Bhatia et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.6, June- 2014, pg. 816-824
+Available Online at www.ijcsmc.com
+International Journal of Computer Science and Mobile Computing
+A Monthly Journal of Computer Science and Information Technology
+ISSN 2320–088X
+IJCSMC, Vol. 3, Issue. 6, June 2014, pg.816 – 824
+RESEARCH ARTICLE
+A Practical Approach for Determination
+of Human Gender & Age
+Harpreet Kaur Bhatia1, Ahsan Hussain2
+CSE Dept. & CSVTU University, India
+CSE Dept. & CSVTU University, India"
+75249ebb85b74e8932496272f38af274fbcfd696,Face Identification in Large Galleries,"Face Identiﬁcation in Large Galleries
+Rafael H. Vareto, Filipe Costa, William Robson Schwartz
+Smart Surveillance Interest Group, Department of Computer Science
+Universidade Federal de Minas Gerais, Belo Horizonte, Brazil"
+81a142c751bf0b23315fb6717bc467aa4fdfbc92,Pairwise Trajectory Representation for Action Recognition,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE
+ICASSP 2017"
+81bfe562e42f2eab3ae117c46c2e07b3d142dade,A Hajj And Umrah Location Classification System For Video Crowded Scenes,"A Hajj And Umrah Location Classiﬁcation System For Video
+Crowded Scenes
+Hossam M. Zawbaa†
+Salah A. Aly†‡
+Adnan A. Gutub†
+Center of Research Excellence in Hajj and Umrah, Umm Al-Qura University, Makkah, KSA
+College of Computers and Information Systems, Umm Al-Qura University, Makkah, KSA"
+81695fbbbea2972d7ab1bfb1f3a6a0dbd3475c0f,Comparison of Face Recognition Neural Networks,"UNIVERSITY OF TARTU
+FACULTY OF SCIENCE AND TECHNOLOGY
+Institute of Computer Science
+Computer Science
+Zepp Uibo
+Comparison of Face Recognition
+Neural Networks
+Bachelor's thesis (6 ECST)
+Supervisor: Tambet Matiisen
+Tartu 2016"
+8147ee02ec5ff3a585dddcd000974896cb2edc53,Angular Embedding: A Robust Quadratic Criterion,"Angular Embedding:
+A Robust Quadratic Criterion
+Stella X. Yu, Member,"
+8199803f476c12c7f6c0124d55d156b5d91314b6,The iNaturalist Species Classification and Detection Dataset,"The iNaturalist Species Classiﬁcation and Detection Dataset
+Grant Van Horn1 Oisin Mac Aodha1 Yang Song2 Yin Cui3 Chen Sun2
+Alex Shepard4 Hartwig Adam2
+Pietro Perona1
+Serge Belongie3
+Caltech
+Google
+Cornell Tech
+iNaturalist"
+81b2a541d6c42679e946a5281b4b9dc603bc171c,Semi-supervised learning with committees: exploiting unlabeled data using ensemble learning algorithms,"Universit¨at Ulm | 89069 Ulm | Deutschland
+Fakult¨at f¨ur Ingenieurwissenschaften und Informatik
+Institut f¨ur Neuroinformatik
+Direktor: Prof. Dr. G¨unther Palm
+Semi-Supervised Learning with Committees:
+Exploiting Unlabeled Data Using Ensemble
+Learning Algorithms
+Dissertation zur Erlangung des Doktorgrades
+Doktor der Naturwissenschaften (Dr. rer. nat.)
+der Fakult¨at f¨ur Ingenieurwissenschaften und Informatik
+der Universit¨at Ulm
+vorgelegt von
+Mohamed Farouk Abdel Hady
+us Kairo, ¨Agypten
+Ulm, Deutschland"
+8160b3b5f07deaa104769a2abb7017e9c031f1c1,Exploiting discriminant information in nonnegative matrix factorization with application to frontal face verification,"Exploiting Discriminant Information in Nonnegative
+Matrix Factorization With Application
+to Frontal Face Veriﬁcation
+Stefanos Zafeiriou, Anastasios Tefas, Member, IEEE, Ioan Buciu, and Ioannis Pitas, Senior Member, IEEE"
+814d091c973ff6033a83d4e44ab3b6a88cc1cb66,The EU-Emotion Stimulus Set: A validation study.,"Behav Res (2016) 48:567–576
+DOI 10.3758/s13428-015-0601-4
+The EU-Emotion Stimulus Set: A validation study
+Helen O’Reilly 1,2 & Delia Pigat 1 & Shimrit Fridenson 5 & Steve Berggren 3,4 & Shahar Tal 5 &
+Ofer Golan 5 & Sven Bölte 3,4 & Simon Baron-Cohen 1,6 & Daniel Lundqvist 3
+Published online: 30 September 2015
+# Psychonomic Society, Inc. 2015"
+816eff5e92a6326a8ab50c4c50450a6d02047b5e,fLRR: Fast Low-Rank Representation Using Frobenius Norm,"fLRR: Fast Low-Rank Representation Using
+Frobenius Norm
+Haixian Zhang, Zhang Yi, and Xi Peng
+Low Rank Representation (LRR) intends to ﬁnd the representation
+with lowest-rank of a given data set, which can be formulated as a
+rank minimization problem. Since the rank operator is non-convex and
+discontinuous, most of the recent works use the nuclear norm as a convex
+relaxation. This letter theoretically shows that under some conditions,
+Frobenius-norm-based optimization problem has an unique solution that
+is also a solution of the original LRR optimization problem. In other
+words, it is feasible to apply Frobenius-norm as a surrogate of the
+nonconvex matrix rank function. This replacement will largely reduce the
+time-costs for obtaining the lowest-rank solution. Experimental results
+show that our method (i.e., fast Low Rank Representation, fLRR),
+performs well in terms of accuracy and computation speed in image
+lustering and motion segmentation compared with nuclear-norm-based
+LRR algorithm.
+Introduction: Given a data set X ∈ Rm×n(m < n) composed of column
+vectors, let A be a data set composed of vectors with the same dimension
+s those in X. Both X and A can be considered as matrices. A linear"
+8149c30a86e1a7db4b11965fe209fe0b75446a8c,Semi-supervised multiple instance learning based domain adaptation for object detection,"Semi-Supervised Multiple Instance Learning based
+Domain Adaptation for Object Detection
+Siemens Corporate Research
+Siemens Corporate Research
+Siemens Corporate Research
+Amit Kale
+Bangalore
+Chhaya Methani
+Bangalore
+{chhaya.methani,
+Rahul Thota
+Bangalore
+rahul.thota,"
+81da427270c100241c07143885ba3051ec4a2ecb,Learning the Synthesizability of Dynamic Texture Samples,"Learning the Synthesizability of Dynamic Texture Samples∗
+Feng Yang1, Gui-Song Xia1, Dengxin Dai2, Liangpei Zhang1
+State Key Lab. LIESMARS, Wuhan University, China
+{guisong.xia, fengyang,
+Computer Vision Lab., ETH Zurich, Switzerland
+February 6, 2018"
+86614c2d2f6ebcb9c600d4aef85fd6bf6eab6663,Benchmarks for Cloud Robotics,"Benchmarks for Cloud Robotics
+Arjun Singh
+Electrical Engineering and Computer Sciences
+University of California at Berkeley
+Technical Report No. UCB/EECS-2016-142
+http://www.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-142.html
+August 12, 2016"
+86b69b3718b9350c9d2008880ce88cd035828432,Improving Face Image Extraction by Using Deep Learning Technique,"Improving Face Image Extraction by Using Deep Learning Technique
+Zhiyun Xue, Sameer Antani, L. Rodney Long, Dina Demner-Fushman, George R. Thoma
+National Library of Medicine, NIH, Bethesda, MD"
+86904aee566716d9bef508aa9f0255dc18be3960,Learning Anonymized Representations with Adversarial Neural Networks,"Learning Anonymized Representations with
+Adversarial Neural Networks
+Cl´ement Feutry, Pablo Piantanida, Yoshua Bengio, and Pierre Duhamel"
+867e709a298024a3c9777145e037e239385c0129,Analytical Representation of Undersampled Face Recognition Approach Based on Dictionary Learning and Sparse Representation,"INTERNATIONAL JOURNAL
+OF PROFESSIONAL ENGINEERING STUDIES                                                                                                            Volume VIII /Issue 2 / FEB 2017
+ANALYTICAL REPRESENTATION OF UNDERSAMPLED FACE
+RECOGNITION APPROACH BASED ON DICTIONARY LEARNING
+AND  SPARSE REPRESENTATION
+Murala Sandeep1 A.Mallikarjuna Reddy2 P.Rajashaker Reddy3 Dr. G. Vishnu murthy4
+(M.Tech)1, Assistant Professor2, Assistant Professor3, HOD of CSE Department4
+Anurag group of institutions Ghatkesar, Ranga Reddy, Hyderabad, India"
+86c053c162c08bc3fe093cc10398b9e64367a100,Cascade of forests for face alignment,"Cascade of Forests for Face Alignment
+Heng Yang, Changqing Zou, Ioannis Patras"
+861802ac19653a7831b314cd751fd8e89494ab12,"Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications","Marcin Grzegorzek, Christian Theobalt, Reinhard Koch,
+Andreas Kolb
+Time-of-Flight and Depth Imaging. Sensors, Algorithms
+nd Applications: Dagstuhl Seminar 2012 and GCPR
+Workshop on Imaging New Modalities (Lecture ... Vision,
+Pattern Recognition, and Graphics)
+Publisher: Springer; 2013 edition
+(November 8, 2013)
+Language: English
+Pages: 320
+ISBN: 978-3642449635
+Size: 20.46 MB
+Format: PDF / ePub / Kindle
+Cameras for 3D depth imaging, using
+either time-of-flight (ToF) or
+structured light sensors, have received
+lot of attention recently and have
+een improved considerably over the
+last few years. The present
+techniques..."
+861b12f405c464b3ffa2af7408bff0698c6c9bf0,An Effective Technique for Removal of Facial Dupilcation by SBFA,"International Journal on Recent and Innovation Trends in Computing and Communication                                                     ISSN: 2321-8169
+Volume: 3 Issue: 5
+3337 - 3342
+_______________________________________________________________________________________________
+An Effective Technique for Removal of Facial Dupilcation by SBFA
+Miss. Deepika B. Patil
+Computer Department,
+GHRCEM,
+Pune, India
+Dr. Ayesha Butalia
+Computer Department,
+GHRCEM,
+Pune, India"
+86e1bdbfd13b9ed137e4c4b8b459a3980eb257f6,The Kinetics Human Action Video Dataset,"The Kinetics Human Action Video Dataset
+Will Kay
+Jo˜ao Carreira
+Karen Simonyan
+Brian Zhang
+Chloe Hillier
+Sudheendra Vijayanarasimhan
+Fabio Viola
+Tim Green
+Trevor Back
+Paul Natsev
+Mustafa Suleyman
+Andrew Zisserman"
+86b105c3619a433b6f9632adcf9b253ff98aee87,A Mutual Information based Face Clustering Algorithm for Movies,"424403677/06/$20.00 ©2006 IEEE
+ICME 2006"
+72a87f509817b3369f2accd7024b2e4b30a1f588,Fault diagnosis of a railway device using semi-supervised independent factor analysis with mixing constraints,"Fault diagnosis of a railway device using semi-supervised
+independent factor analysis with mixing constraints
+Etienne Côme, Latifa Oukhellou, Thierry Denoeux, Patrice Aknin
+To cite this version:
+Etienne Côme, Latifa Oukhellou, Thierry Denoeux, Patrice Aknin. Fault diagnosis of a railway device
+using semi-supervised independent factor analysis with mixing constraints. Pattern Analysis and
+Applications, Springer Verlag, 2012, 15 (3), pp.313-326. <hal-00750589>
+HAL Id: hal-00750589
+https://hal.archives-ouvertes.fr/hal-00750589
+Submitted on 11 Nov 2012
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entific research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destinée au dépôt et à la diffusion de documents
+scientifiques de niveau recherche, publiés ou non,
+émanant des établissements d’enseignement et de"
+72a00953f3f60a792de019a948174bf680cd6c9f,Understanding the role of facial asymmetry in human face identification,"Stat Comput (2007) 17:57–70
+DOI 10.1007/s11222-006-9004-9
+Understanding the role of facial asymmetry in human face
+identiﬁcation
+Sinjini Mitra · Nicole A. Lazar · Yanxi Liu
+Received: May 2005 / Accepted: September 2006 / Published online: 30 January 2007
+C(cid:1) Springer Science + Business Media, LLC 2007"
+72ecaff8b57023f9fbf8b5b2588f3c7019010ca7,Facial Keypoints Detection,"Facial Keypoints Detection
+Shenghao Shi"
+72591a75469321074b072daff80477d8911c3af3,Group Component Analysis for Multiblock Data: Common and Individual Feature Extraction,"Group Component Analysis for Multi-block Data:
+Common and Individual Feature Extraction
+Guoxu Zhou, Andrzej Cichocki Fellow, IEEE, Yu Zhang, and Danilo Mandic Fellow, IEEE"
+729a9d35bc291cc7117b924219bef89a864ce62c,Recognizing Material Properties from Images,"Recognizing Material Properties from Images
+Gabriel Schwartz and Ko Nishino, Senior Member, IEEE"
+721d9c387ed382988fce6fa864446fed5fb23173,Assessing Facial Expressions in Virtual Reality Environments,
+72c0c8deb9ea6f59fde4f5043bff67366b86bd66,Age progression in Human Faces : A Survey,"Age progression in Human Faces : A Survey
+Narayanan Ramanathan, Rama Chellappa and Soma Biswas"
+72f4aaf7e2e3f215cd8762ce283988220f182a5b,Active illumination and appearance model for face alignment,"Turk J Elec Eng & Comp Sci, Vol.18, No.4, 2010, c(cid:2) T ¨UB˙ITAK
+doi:10.3906/elk-0906-48
+Active illumination and appearance model for face
+lignment
+Fatih KAHRAMAN1, Muhittin G ¨OKMEN 2, Sune DARKNER3, Rasmus LARSEN3
+Institute of Informatics, ˙Istanbul Technical University, ˙Istanbul, 34469, TURKEY
+Department of Computer Engineering, ˙Istanbul Technical University, ˙Istanbul, 34469, TURKEY
+DTU Informatics, Technical University of Denmark, DK-2800 Kgs. Lyngby, DENMARK
+e-mail:
+e-mail:
+e-mail: {sda,"
+72a55554b816b66a865a1ec1b4a5b17b5d3ba784,Real-Time Face Identification via CNN and Boosted Hashing Forest,"Real-Time Face Identification
+via CNN
+nd Boosted Hashing Forest
+Yury Vizilter, Vladimir Gorbatsevich, Andrey Vorotnikov and Nikita Kostromov
+State Research Institute of Aviation Systems (GosNIIAS), Moscow, Russia
+IEEE Computer Society Workshop on Biometrics
+In conjunction with CVPR 2016, June 26, 2016"
+72bf9c5787d7ff56a1697a3389f11d14654b4fcf,Robust Face Recognition Using Symmetric Shape-from-Shading,"RobustFaceRecognitionUsing
+SymmetricShape-from-Shading
+W.Zhao
+RamaChellappa
+CenterforAutomationResearchand
+ElectricalandComputerEngineeringDepartment
+UniversityofMaryland
+CollegePark,MD
+ThesupportoftheO(cid:14)ceofNavalResearchunderGrantN
+4414a328466db1e8ab9651bf4e0f9f1fe1a163e4,Weighted voting of sparse representation classifiers for facial expression recognition,"© EURASIP, 2010   ISSN 2076-1465
+8th European Signal Processing Conference (EUSIPCO-2010)
+INTRODUCTION"
+4439746eeb7c7328beba3f3ef47dc67fbb52bcb3,YASAMAN HEYDARZADEH at al: AN EFFICIENT FACE DETECTION METHOD USING ADABOOST,"YASAMAN HEYDARZADEH at al: AN EFFICIENT FACE DETECTION METHOD USING ADABOOST . . .
+An Efficient Face Detection Method Using Adaboost and Facial Parts
+Yasaman Heydarzadeh, Abolfazl Toroghi Haghighat
+Computer, IT and Electronic department
+Azad University of Qazvin
+Tehran, Iran
+qiau.ac.ir ,"
+446a99fdedd5bb32d4970842b3ce0fc4f5e5fa03,A Pose-Adaptive Constrained Local Model for Accurate Head Pose Tracking,"A Pose-Adaptive Constrained Local Model For
+Accurate Head Pose Tracking
+Lucas Zamuner
+Eikeo
+1 rue Leon Jouhaux,
+F-75010, Paris, France
+Kevin Bailly
+Sorbonne Universit´es
+UPMC Univ Paris 06
+CNRS UMR 7222, ISIR
+F-75005, Paris, France
+Erwan Bigorgne
+Eikeo
+1 rue Leon Jouhaux,
+F-75010, Paris, France"
+44b1399e8569a29eed0d22d88767b1891dbcf987,Learning Multi-modal Latent Attributes,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.
+IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
+Learning Multi-modal Latent Attributes
+Yanwei Fu, Timothy M. Hospedales, Tao Xiang and Shaogang Gong"
+446dc1413e1cfaee0030dc74a3cee49a47386355,Recent Advances in Zero-shot Recognition,"Recent Advances in Zero-shot Recognition
+Yanwei Fu, Tao Xiang, Yu-Gang Jiang, Xiangyang Xue, Leonid Sigal, and Shaogang Gong"
+44a3ec27f92c344a15deb8e5dc3a5b3797505c06,A Taxonomy of Part and Attribute Discovery Techniques,"A Taxonomy of Part and Attribute Discovery
+Techniques
+Subhransu Maji"
+44dd150b9020b2253107b4a4af3644f0a51718a3,An Analysis of the Sensitivity of Active Shape Models to Initialization When Applied to Automatic Facial Landmarking,"An Analysis of the Sensitivity of Active Shape
+Models to Initialization when Applied to Automatic
+Facial Landmarking
+Keshav Seshadri, Student Member, IEEE and Marios Savvides, Member, IEEE"
+447d8893a4bdc29fa1214e53499ffe67b28a6db5,Electronic Transport in Quantum Confined Systems,"THÈSEPour obtenir le titre deDOCTEUR DE L’UNIVERSITÉSpécialitéSCIENCES DES MATÉRIAUXParMaxime BERTHEElectronic transport in quantum confined systemsSoutenue le 11 décembre 2007 devant la commission d’examen composée de:B. DJAFARI-ROUHANIS. ROUSSETD. RODITCHEVF. CHARRAD. STIÉVENARDH. SHIGEKAWAB. GRANDIDIERPrésidentRapporteurRapporteurExaminateurDirecteur de thèseCo-directeur de thèseCo-directeur de thèsel’Université des Sciences et Technologies de LilleEcole Doctorale Sciences de la Matière, du Rayonnement et de l’EnvironnementPrésentée à"
+44f65e3304bdde4be04823fd7ca770c1c05c2cef,On the use of phase of the Fourier transform for face recognition under variations in illumination,"SIViP
+DOI 10.1007/s11760-009-0125-4
+ORIGINAL PAPER
+On the use of phase of the Fourier transform for face recognition
+under variations in illumination
+Anil Kumar Sao · B. Yegnanarayana
+Received: 17 November 2008 / Revised: 20 February 2009 / Accepted: 7 July 2009
+© Springer-Verlag London Limited 2009"
+447a5e1caf847952d2bb526ab2fb75898466d1bc,Learning Non-linear Transform with Discrim- Inative and Minimum Information Loss Priors,"Under review as a conference paper at ICLR 2018
+LEARNING NON-LINEAR TRANSFORM WITH DISCRIM-
+INATIVE AND MINIMUM INFORMATION LOSS PRIORS
+Anonymous authors
+Paper under double-blind review"
+2a7bca56e2539c8cf1ae4e9da521879b7951872d,Exploiting Unrelated Tasks in Multi-Task Learning,"Exploiting Unrelated Tasks in Multi-Task Learning
+Anonymous Author 1
+Unknown Institution 1
+Anonymous Author 2
+Unknown Institution 2
+Anonymous Author 3
+Unknown Institution 3"
+2a0efb1c17fbe78470acf01e4601a75735a805cc,Illumination-Insensitive Face Recognition Using Symmetric Shape-from-Shading,"Illumination-InsensitiveFaceRecognitionUsing
+SymmetricShape-from-Shading
+WenYiZhao
+RamaChellappa
+CenterforAutomationResearch
+UniversityofMaryland,CollegePark,MD
+2aec012bb6dcaacd9d7a1e45bc5204fac7b63b3c,Robust Registration and Geometry Estimation from Unstructured Facial Scans,"Robust Registration and Geometry Estimation from Unstructured
+Facial Scans
+Maxim Bazik1 and Daniel Crispell2"
+2ae139b247057c02cda352f6661f46f7feb38e45,Combining modality specific deep neural networks for emotion recognition in video,"Combining Modality Speciﬁc Deep Neural Networks for
+Emotion Recognition in Video
+Samira Ebrahimi Kahou1, Christopher Pal1, Xavier Bouthillier2, Pierre Froumenty1,
+Ça˘glar Gülçehre2,∗ , Roland Memisevic2, Pascal Vincent2, Aaron Courville2, & Yoshua Bengio2
+École Polytechique de Montréal, Université de Montréal, Montréal, Canada
+Laboratoire d’Informatique des Systèmes Adaptatifs, Université de Montréal, Montréal, Canada
+{samira.ebrahimi-kahou, christopher.pal,
+{bouthilx, gulcehrc, memisevr, vincentp, courvila,"
+2ad0ee93d029e790ebb50574f403a09854b65b7e,Acquiring linear subspaces for face recognition under variable lighting,"Acquiring Linear Subspaces for Face
+Recognition under Variable Lighting
+Kuang-Chih Lee, Student Member, IEEE, Jeffrey Ho, Member, IEEE, and
+David Kriegman, Senior Member, IEEE"
+2ff9618ea521df3c916abc88e7c85220d9f0ff06,Facial Tic Detection Using Computer Vision,"Facial Tic Detection Using Computer Vision
+Christopher D. Leveille
+Advisor: Prof. Aaron Cass
+March 20, 2014"
+2fda461869f84a9298a0e93ef280f79b9fb76f94,OpenFace: An open source facial behavior analysis toolkit,"OpenFace: an open source facial behavior analysis toolkit
+Tadas Baltruˇsaitis
+Peter Robinson
+Louis-Philippe Morency"
+2ffcd35d9b8867a42be23978079f5f24be8d3e35,Satellite based Image Processing using Data mining,"ISSN XXXX XXXX © 2018 IJESC
+Research Article                                                                                                                            Volume 8 Issue No.6
+Satellite based Image Processing using Data mining
+E.Malleshwari1, S.Nirmal Kumar2, J.Dhinesh3
+Professor1, Assistant Professor2, PG Scholar3
+Department of Information Technology1, 2, Master of Computer Applications3
+Vel Tech High Tech Dr Rangarajan Dr Sakunthala Engineering College, Avadi, Chennai, India"
+2f7e9b45255c9029d2ae97bbb004d6072e70fa79,cvpaper.challenge in 2015 - A review of CVPR2015 and DeepSurvey,"Noname manuscript No.
+(will be inserted by the editor)
+vpaper.challenge in 2015
+A review of CVPR2015 and DeepSurvey
+Hirokatsu Kataoka · Yudai Miyashita · Tomoaki Yamabe · Soma
+Shirakabe · Shin’ichi Sato · Hironori Hoshino · Ryo Kato · Kaori Abe ·
+Takaaki Imanari · Naomichi Kobayashi · Shinichiro Morita · Akio
+Nakamura
+Received: date / Accepted: date"
+2f489bd9bfb61a7d7165a2f05c03377a00072477,Structured Semi-supervised Forest for Facial Landmarks Localization with Face Mask Reasoning,"JIA, YANG: STRUCTURED SEMI-SUPERVISED FOREST
+Structured Semi-supervised Forest for
+Facial Landmarks Localization with Face
+Mask Reasoning
+Department of Computer Science
+The Univ. of Hong Kong, HK
+School of EECS
+Queen Mary Univ. of London, UK
+Xuhui Jia1
+Heng Yang2
+Angran Lin1
+Kwok-Ping Chan1
+Ioannis Patras2"
+2f59f28a1ca3130d413e8e8b59fb30d50ac020e2,Children Gender Recognition Under Unconstrained Conditions Based on Contextual Information,"Children Gender Recognition Under Unconstrained
+Conditions Based on Contextual Information
+Riccardo Satta, Javier Galbally and Laurent Beslay
+Joint Research Centre, European Commission, Ispra, Italy
+Email:"
+2f78e471d2ec66057b7b718fab8bfd8e5183d8f4,An Investigation of a New Social Networks Contact Suggestion Based on Face Recognition Algorithm,"SOFTWARE ENGINEERING
+VOLUME: 14 | NUMBER: 5 | 2016 | DECEMBER
+An Investigation of a New Social Networks
+Contact Suggestion Based on Face Recognition
+Algorithm
+Ivan ZELINKA1,2, Petr SALOUN 2, Jakub STONAWSKI 2, Adam ONDREJKA2
+Modeling Evolutionary Algorithms Simulation and Artiﬁcial Intelligence, Faculty of Electrical & Electronics
+Engineering, Ton Duc Thang University, 19 Nguyen Huu Tho Street, Ho Chi Minh City, Vietman
+Department of Computer Science, Faculty of Electrical Engineering and Computer Science,
+VSB–Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava, Czech Republic
+DOI: 10.15598/aeee.v14i5.1116"
+2f88d3189723669f957d83ad542ac5c2341c37a5,Attribute-correlated local regions for deep relative attributes learning,"Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 9/13/2018
+Terms of Use: https://www.spiedigitallibrary.org/terms-of-use
+Attribute-correlatedlocalregionsfordeeprelativeattributeslearningFenZhangXiangweiKongZeJiaFenZhang,XiangweiKong,ZeJia,“Attribute-correlatedlocalregionsfordeeprelativeattributeslearning,”J.Electron.Imaging27(4),043021(2018),doi:10.1117/1.JEI.27.4.043021."
+2fda164863a06a92d3a910b96eef927269aeb730,Names and faces in the news,"Names and Faces in the News
+Tamara L. Berg, Alexander C. Berg, Jaety Edwards, Michael Maire,
+Ryan White, Yee-Whye Teh, Erik Learned-Miller and D.A. Forsyth
+Computer Science Division
+U.C. Berkeley
+Berkeley, CA 94720"
+2f8ef26bfecaaa102a55b752860dbb92f1a11dc6,A Graph Based Approach to Speaker Retrieval in Talk Show Videos with Transcript-Based Supervision,"A Graph Based Approach to Speaker Retrieval in Talk
+Show Videos with Transcript-Based Supervision
+Yina Han  1, Guizhong Liu, Hichem Sahbi, Gérard Chollet"
+2f17f6c460e02bd105dcbf14c9b73f34c5fb59bd,Robust Face Recognition Using the Deep C2D-CNN Model Based on Decision-Level Fusion,"Article
+Robust Face Recognition Using the Deep C2D-CNN
+Model Based on Decision-Level Fusion
+Jing Li 1,2,†, Tao Qiu 3,†, Chang Wen 3,*, Kai Xie 1,2 and Fang-Qing Wen 1,2
+School of Electronic and Information, Yangtze University, Jingzhou 434023, China;
+(J.L.); (K.X.); (F-Q.W.)
+National Demonstration Center for Experimental Electrical and Electronic Education, Yangtze University,
+Jingzhou 434023, China
+School of Computer Science, Yangtze University, Jingzhou 434023, China;
+* Correspondence: Tel.: +86-136-9731-5482
+These authors contributed equally to this work.
+Received: 20 May 2018; Accepted: 25 June 2018; Published: 28 June 2018"
+2f184c6e2c31d23ef083c881de36b9b9b6997ce9,Polichotomies on Imbalanced Domains by One-per-Class Compensated Reconstruction Rule,"Polichotomies on Imbalanced Domains
+y One-per-Class Compensated Reconstruction Rule
+Roberto D’Ambrosio and Paolo Soda
+Integrated Research Centre, Universit´a Campus Bio-Medico of Rome, Rome, Italy"
+2fa1fc116731b2b5bb97f06d2ac494cb2b2fe475,A novel approach to personal photo album representation and management,"A novel approach to personal photo album representation
+nd management
+Edoardo Ardizzone, Marco La Cascia, and Filippo Vella
+Universit`a di Palermo - Dipartimento di Ingegneria Informatica
+Viale delle Scienze, 90128, Palermo, Italy"
+2f882ceaaf110046e63123b495212d7d4e99f33d,High Frequency Component Compensation based Super-Resolution Algorithm for Face Video Enhancement,"High Frequency Component Compensation based Super-resolution
+Algorithm for Face Video Enhancement
+Junwen Wu, Mohan Trivedi, Bhaskar Rao
+CVRR Lab, UC San Diego, La Jolla, CA 92093, USA"
+2f95340b01cfa48b867f336185e89acfedfa4d92,Face expression recognition with a 2-channel Convolutional Neural Network,"Face Expression Recognition with a 2-Channel
+Convolutional Neural Network
+Dennis Hamester, Pablo Barros, Stefan Wermter
+University of Hamburg — Department of Informatics
+Vogt-K¨olln-Straße 30, 22527 Hamburg, Germany
+http://www.informatik.uni-hamburg.de/WTM/"
+2faa09413162b0a7629db93fbb27eda5aeac54ca,Quantifying how lighting and focus affect face recognition performance,"NISTIR 7674
+Quantifying How Lighting and Focus
+Affect Face Recognition Performance
+Phillips, P. J.
+Beveridge, J. R.
+Draper, B.
+Bolme, D.
+Givens, G. H.
+Lui, Y. M."
+433bb1eaa3751519c2e5f17f47f8532322abbe6d,Face Recognition,
+43bb20ccfda7b111850743a80a5929792cb031f0,Discrimination of Computer Generated versus Natural Human Faces,"PhD Dissertation
+International Doctorate School in Information and
+Communication Technologies
+DISI - University of Trento
+Discrimination of Computer Generated
+versus Natural Human Faces
+Duc-Tien Dang-Nguyen
+Advisor:
+Prof. Giulia Boato
+Universit`a degli Studi di Trento
+Co-Advisor:
+Prof. Francesco G. B. De Natale
+Universit`a degli Studi di Trento
+February 2014"
+439ac8edfa1e7cbc65474cab544a5b8c4c65d5db,Face authentication with undercontrolled pose and illumination,"SIViP (2011) 5:401–413
+DOI 10.1007/s11760-011-0244-6
+ORIGINAL PAPER
+Face authentication with undercontrolled pose and illumination
+Maria De Marsico · Michele Nappi · Daniel Riccio
+Received: 15 September 2010 / Revised: 14 December 2010 / Accepted: 17 February 2011 / Published online: 7 August 2011
+© Springer-Verlag London Limited 2011"
+43f6953804964037ff91a4f45d5b5d2f8edfe4d5,Multi-feature fusion in advanced robotics applications,"Multi-Feature Fusion in Advanced Robotics Applications
+Zahid Riaz, Christoph Mayer, Michael Beetz,
+Bernd Radig
+Institut für Informatik
+Technische Universität München
+D-85748 Garching, Germany"
+439ec47725ae4a3660e509d32828599a495559bf,Facial Expressions Tracking and Recognition: Database Protocols for Systems Validation and Evaluation,"Facial Expressions Tracking and Recognition: Database Protocols for Systems Validation
+nd Evaluation"
+43a03cbe8b704f31046a5aba05153eb3d6de4142,Towards Robust Face Recognition from Video,"Towards Robust Face Recognition from Video
+Jeffery R. Price
+Timothy F. Gee
+Image Science and Machine Vision Group
+Oak Ridge National Laboratory
+Oak Ridge, TN 37831-6010
+{pricejr,"
+434bf475addfb580707208618f99c8be0c55cf95,DeXpression: Deep Convolutional Neural Network for Expression Recognition,"UNDER CONSIDERATION FOR PUBLICATION IN PATTERN RECOGNITION LETTERS
+DeXpression: Deep Convolutional Neural
+Network for Expression Recognition
+Peter Burkert∗‡, Felix Trier∗‡, Muhammad Zeshan Afzal†‡,
+Andreas Dengel†‡ and Marcus Liwicki‡
+German Research Center for Artiﬁcial Intelligence (DFKI), Kaiserslautern, Germany
+University of Kaiserslautern, Gottlieb-Daimler-Str., Kaiserslautern 67663, Germany"
+43836d69f00275ba2f3d135f0ca9cf88d1209a87,Effective hyperparameter optimization using Nelder-Mead method in deep learning,"Ozaki et al. IPSJ Transactions on Computer Vision and
+Applications  (2017) 9:20
+DOI 10.1186/s41074-017-0030-7
+IPSJ Transactions on Computer
+Vision and Applications
+RESEARCH PAPER
+Open Access
+Effective hyperparameter optimization
+using Nelder-Mead method in deep learning
+Yoshihiko Ozaki1,2, Masaki Yano1,2 and Masaki Onishi1,2*"
+4362368dae29cc66a47114d5ffeaf0534bf0159c,"Performance Analysis of FDA Based Face Recognition Using Correlation, ANN and SVM","UACEE International Journal of Artificial Intelligence and Neural Networks ISSN:- 2250-3749 (online)
+Performance Analysis of FDA Based Face
+Recognition Using Correlation, ANN and SVM
+Mahesh Goyani
+Akash Dhorajiya
+Ronak Paun
+Department of Computer Engineering
+Department of Computer Engineering
+Department of Computer Engineering
+GCET, Sardar Patel University
+GCET, Sardar Patel University
+GCET, Sardar Patel University
+Anand, INDIA
+Anand, INDIA
+Anand, INDIA
+e- mail :
+e- mail :
+e- mail :"
+4350bb360797a4ade4faf616ed2ac8e27315968e,Edge Suppression by Gradient Field Transformation Using Cross-Projection Tensors,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES
+http://www.merl.com
+Edge Suppression by Gradient Field
+Transformation using Cross-Projection
+Tensors
+Amit Agrawal, Ramesh Raskar, Rama Chellappa
+TR2006-058
+June 2006"
+43476cbf2a109f8381b398e7a1ddd794b29a9a16,A Practical Transfer Learning Algorithm for Face Verification,"A Practical Transfer Learning Algorithm for Face Veriﬁcation
+Xudong Cao
+David Wipf
+Fang Wen
+Genquan Duan
+Jian Sun"
+4353d0dcaf450743e9eddd2aeedee4d01a1be78b,Learning Discriminative LBP-Histogram Bins for Facial Expression Recognition,"Learning Discriminative LBP-Histogram Bins
+for Facial Expression Recognition
+Caifeng Shan and Tommaso Gritti
+Philips Research, High Tech Campus 36, Eindhoven 5656 AE, The Netherlands
+{caifeng.shan,"
+43b8b5eeb4869372ef896ca2d1e6010552cdc4d4,Large-scale Supervised Hierarchical Feature Learning for Face Recognition,"Large-scale Supervised Hierarchical Feature Learning for Face Recognition
+Jianguo Li, Yurong Chen
+Intel Labs China"
+43ae4867d058453e9abce760ff0f9427789bab3a,Graph Embedded Nonparametric Mutual Information for Supervised Dimensionality Reduction,"Graph Embedded Nonparametric Mutual
+Information For Supervised
+Dimensionality Reduction
+Dimitrios Bouzas, Nikolaos Arvanitopoulos, Student Member, IEEE, and Anastasios Tefas, Member, IEEE"
+438b88fe40a6f9b5dcf08e64e27b2719940995e0,Building a classification cascade for visual identification from one example,"Building a Classi(cid:2)cation Cascade for Visual Identi(cid:2)cation from One Example
+Andras Ferencz
+Erik G. Learned-Miller
+Computer Science, U.C. Berkeley
+Computer Science, UMass Amherst
+Jitendra Malik
+Computer Science, U.C. Berkeley"
+43fb9efa79178cb6f481387b7c6e9b0ca3761da8,Mixture of parts revisited: Expressive part interactions for Pose Estimation,"Mixture of Parts Revisited: Expressive Part Interactions for Pose Estimation
+Anoop R Katti
+IIT Madras
+Chennai, India
+Anurag Mittal
+IIT Madras
+Chennai, India"
+43ed518e466ff13118385f4e5d039ae4d1c000fb,Classification of Occluded Objects Using Fast Recurrent Processing,"Classiﬁcation of Occluded Objects using Fast Recurrent
+Processing
+Ozgur Yilmaza,∗
+Turgut Ozal University, Department of Computer Engineering, Ankara Turkey"
+43d7d0d0d0e2d6cf5355e60c4fe5b715f0a1101a,Playlist Generation using Facial Expression Analysis and Task Extraction,"Pobrane z czasopisma Annales AI- Informatica http://ai.annales.umcs.pl
+Data: 04/05/2018 16:53:32
+U M CS"
+88c6d4b73bd36e7b5a72f3c61536c8c93f8d2320,Image patch modeling in a light field,"Image patch modeling in a light field
+Zeyu Li
+Electrical Engineering and Computer Sciences
+University of California at Berkeley
+Technical Report No. UCB/EECS-2014-81
+http://www.eecs.berkeley.edu/Pubs/TechRpts/2014/EECS-2014-81.html
+May 15, 2014"
+889bc64c7da8e2a85ae6af320ae10e05c4cd6ce7,Using Support Vector Machines to Enhance the Performance of Bayesian Face Recognition,"Using Support Vector Machines to Enhance the
+Performance of Bayesian Face Recognition
+Zhifeng Li, Member, IEEE, and Xiaoou Tang, Senior Member, IEEE"
+88a898592b4c1dfd707f04f09ca58ec769a257de,MobileFace: 3D Face Reconstruction with Efficient CNN Regression,"MobileFace: 3D Face Reconstruction
+with Ef‌f‌icient CNN Regression
+Nikolai Chinaev1, Alexander Chigorin1, and Ivan Laptev1,2
+VisionLabs, Amsterdam, The Netherlands
+{n.chinaev,
+Inria, WILLOW, Departement d’Informatique de l’Ecole Normale Superieure, PSL
+Research University, ENS/INRIA/CNRS UMR 8548, Paris, France"
+8812aef6bdac056b00525f0642702ecf8d57790b,A Unified Features Approach to Human Face Image Analysis and Interpretation,"A Uniﬁed Features Approach to Human Face Image
+Analysis and Interpretation
+Zahid Riaz, Suat Gedikli, Micheal Beetz and Bernd Radig
+Department of Informatics,
+Technische Universit¨at M¨unchen
+85748 Garching, Germany"
+881066ec43bcf7476479a4146568414e419da804,From Traditional to Modern: Domain Adaptation for Action Classification in Short Social Video Clips,"From Traditional to Modern : Domain Adaptation for
+Action Classiﬁcation in Short Social Video Clips
+Aditya Singh, Saurabh Saini, Rajvi Shah, and P J Narayanan
+Center for Visual Information Technology, IIIT Hyderabad, India"
+8813368c6c14552539137aba2b6f8c55f561b75f,Trunk-Branch Ensemble Convolutional Neural Networks for Video-Based Face Recognition,"Trunk-Branch Ensemble Convolutional Neural
+Networks for Video-based Face Recognition
+Changxing Ding, Student Member, IEEE, Dacheng Tao, Fellow, IEEE"
+88e2574af83db7281c2064e5194c7d5dfa649846,A Robust Shape Reconstruction Method for Facial Feature Point Detection,"Hindawi Publishing Corporation
+Computational Intelligence and Neuroscience
+Volume 2017, Article ID 4579398, 11 pages
+http://dx.doi.org/10.1155/2017/4579398
+Research Article
+A Robust Shape Reconstruction Method for Facial Feature
+Point Detection
+Shuqiu Tan, Dongyi Chen, Chenggang Guo, and Zhiqi Huang
+School of Automation Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave,
+West Hi-Tech Zone, Chengdu 611731, China
+Correspondence should be addressed to Shuqiu Tan; and Dongyi Chen;
+Received 24 October 2016; Revised 18 January 2017; Accepted 30 January 2017; Published 19 February 2017
+Academic Editor: Ezequiel L´opez-Rubio
+Copyright © 2017 Shuqiu Tan et al. This is an open access article distributed under the Creative Commons Attribution License,
+which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
+Facial feature point detection has been receiving great research advances in recent years. Numerous methods have been developed
+nd applied in practical face analysis systems. However, it is still a quite challenging task because of the large variability in expression
+nd gestures and the existence of occlusions in real-world photo shoot. In this paper, we present a robust sparse reconstruction
+method for the face alignment problems. Instead of a direct regression between the feature space and the shape space, the concept
+of shape increment reconstruction is introduced. Moreover, a set of coupled overcomplete dictionaries termed the shape increment"
+883006c0f76cf348a5f8339bfcb649a3e46e2690,Weakly supervised pain localization using multiple instance learning,"Weakly Supervised Pain Localization using Multiple Instance Learning
+Karan Sikka, Abhinav Dhall and Marian Bartlett"
+88850b73449973a34fefe491f8836293fc208580,XBeats-An Emotion Based Music Player,"www.ijaret.org                                                                                                                                                     Vol. 2, Issue I, Jan. 2014
+ISSN 2320-6802
+INTERNATIONAL JOURNAL FOR ADVANCE RESEARCH IN
+ENGINEERING AND TECHNOLOGY
+WINGS TO YOUR THOUGHTS…..
+XBeats-An Emotion Based Music Player
+Sayali Chavan1, Ekta Malkan2, Dipali Bhatt3, Prakash H. Paranjape4
+U.G. Student, Dept. of Computer Engineering,
+D.J. Sanghvi College of Engineering,
+Vile Parle (W), Mumbai-400056.
+U.G. Student, Dept. of Computer Engineering,
+D.J. Sanghvi College of Engineering,
+Vile Parle (W), Mumbai-400056.
+U.G. Student, Dept. of Computer Engineering,
+D.J. Sanghvi College of Engineering,
+Vile Parle (W), Mumbai-400056.
+Assistant Professor, Dept. of Computer Engineering,
+D.J. Sanghvi College of Engineering,
+Vile Parle (W), Mumbai-400056."
+88f2952535df5859c8f60026f08b71976f8e19ec,A neural network framework for face recognition by elastic bunch graph matching,"A neural network framework for face
+recognition by elastic bunch graph matching
+Francisco A. Pujol López, Higinio Mora Mora*, José A. Girona Selva"
+8818b12aa0ff3bf0b20f9caa250395cbea0e8769,Fashion Conversation Data on Instagram_ICWSM 2017,"Fashion Conversation Data on Instagram
+Yu-I Ha∗
+Sejeong Kwon∗
+Meeyoung Cha∗
+Jungseock Joo†
+Graduate School of Culture Technology, KAIST, South Korea
+Department of Communication Studies, UCLA, USA"
+887b7676a4efde616d13f38fcbfe322a791d1413,Deep Temporal Appearance-Geometry Network for Facial Expression Recognition,"Deep Temporal Appearance-Geometry Network
+for Facial Expression Recognition
+Injae Lee‡ Chunghyun Ahn‡
+Junmo Kim†
+Heechul Jung† Sihaeng Lee† Sunjeong Park†
+Korea Advanced Institute of Science and Technology†
+Electronics and Telecommunications Research Institute‡
+{heechul, haeng, sunny0414, {ninja,"
+8878871ec2763f912102eeaff4b5a2febfc22fbe,Human Action Recognition in Unconstrained Videos by Explicit Motion Modeling,"Human Action Recognition in Unconstrained
+Videos by Explicit Motion Modeling
+Yu-Gang Jiang, Qi Dai, Wei Liu, Xiangyang Xue, and Chong-Wah Ngo"
+8855d6161d7e5b35f6c59e15b94db9fa5bbf2912,COGNITION IN PREGNANCY AND THE POSTPARTUM PERIOD COGNITIVE REORGANIZATION AND PROTECTIVE MECHANISMS IN PREGNANCY AND THE POSTPARTUM PERIOD By,COGNITION IN PREGNANCY AND THE POSTPARTUM PERIOD
+88bee9733e96958444dc9e6bef191baba4fa6efa,Extending Face Identification to Open-Set Face Recognition,"Extending Face Identiﬁcation to
+Open-Set Face Recognition
+Cassio E. dos Santos Jr., William Robson Schwartz
+Department of Computer Science
+Universidade Federal de Minas Gerais
+Belo Horizonte, Brazil"
+88fd4d1d0f4014f2b2e343c83d8c7e46d198cc79,Joint action recognition and summarization by sub-modular inference,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE
+ICASSP 2016"
+9fa1be81d31fba07a1bde0275b9d35c528f4d0b8,Identifying Persons by Pictorial and Contextual Cues,"Identifying Persons by Pictorial and
+Contextual Cues
+Nicholas Leonard Pi¨el
+Thesis submitted for the degree of Master of Science
+Supervisor:
+Prof. dr. Theo Gevers
+April 2009"
+9f094341bea610a10346f072bf865cb550a1f1c1,Recognition and volume estimation of food intake using a mobile device,"Recognition and Volume Estimation of Food Intake using a Mobile Device
+Manika Puri Zhiwei Zhu Qian Yu Ajay Divakaran Harpreet Sawhney
+Sarnoff Corporation
+01 Washington Rd,
+Princeton, NJ, 08540
+{mpuri, zzhu, qyu, adivakaran,"
+6bcfcc4a0af2bf2729b5bc38f500cfaab2e653f0,Facial Expression Recognition in the Wild Using Improved Dense Trajectories and Fisher Vector Encoding,"Facial expression recognition in the wild using improved dense trajectories and
+Fisher vector encoding
+Sadaf Afshar1
+Albert Ali Salah2
+Computational Science and Engineering Program, Bo˘gazic¸i University, Istanbul, Turkey
+Department of Computer Engineering, Bo˘gazic¸i University, Istanbul, Turkey
+{sadaf.afshar,"
+6b089627a4ea24bff193611e68390d1a4c3b3644,Cross-Pollination of Normalization Techniques From Speaker to Face Authentication Using Gaussian Mixture Models,"CROSS-POLLINATION OF NORMALISATION
+TECHNIQUES FROM SPEAKER TO FACE
+AUTHENTICATION USING GAUSSIAN
+MIXTURE MODELS
+Roy Wallace        Mitchell McLaren        Chris McCool
+Sébastien Marcel
+Idiap-RR-03-2012
+JANUARY 2012
+Centre du Parc, Rue Marconi 19, P.O. Box 592, CH - 1920 Martigny
+T +41 27 721 77 11  F +41 27 721 77 12   www.idiap.ch"
+6be0ab66c31023762e26d309a4a9d0096f72a7f0,Enhance Visual Recognition under Adverse Conditions via Deep Networks,"Enhance Visual Recognition under Adverse
+Conditions via Deep Networks
+Ding Liu, Student Member, IEEE, Bowen Cheng, Zhangyang Wang, Member, IEEE,
+Haichao Zhang, Member, IEEE, and Thomas S. Huang, Life Fellow, IEEE"
+6b18628cc8829c3bf851ea3ee3bcff8543391819,Face recognition based on subset selection via metric learning on manifold,"Hong Shao, Shuang Chen, Jie-yi Zhao, Wen-cheng Cui, Tian-shu Yu, 2015.
+Face recognition based on subset selection via metric learning on manifold.
+058.  [doi:10.1631/FITEE.1500085]
+Face recognition based on subset
+selection via metric learning on manifold
+Key words: Face recognition, Sparse representation, Manifold structure,
+Metric learning, Subset selection
+Contact: Shuang Chen
+E-mail:
+ORCID: http://orcid.org/0000-0001-7441-4749
+Front Inform Technol & Electron Eng"
+6b6493551017819a3d1f12bbf922a8a8c8cc2a03,Pose Normalization for Local Appearance-Based Face Recognition,"Pose Normalization for Local Appearance-Based
+Face Recognition
+Hua Gao, Hazım Kemal Ekenel, and Rainer Stiefelhagen
+Computer Science Department, Universit¨at Karlsruhe (TH)
+Am Fasanengarten 5, Karlsruhe 76131, Germany
+http://isl.ira.uka.de/cvhci"
+0728f788107122d76dfafa4fb0c45c20dcf523ca,The Best of BothWorlds: Combining Data-Independent and Data-Driven Approaches for Action Recognition,"The Best of Both Worlds: Combining Data-independent and Data-driven
+Approaches for Action Recognition
+Zhenzhong Lan, Dezhong Yao, Ming Lin, Shoou-I Yu, Alexander Hauptmann
+{lanzhzh, minglin, iyu,"
+071099a4c3eed464388c8d1bff7b0538c7322422,Facial expression recognition in the wild using rich deep features,"FACIAL EXPRESSION RECOGNITION IN THE WILD USING RICH DEEP FEATURES
+Abubakrelsedik Karali, Ahmad Bassiouny and Motaz El-Saban
+Microsoft Advanced Technology labs, Microsoft Technology and Research, Cairo, Egypt"
+07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1,Large scale unconstrained open set face database,"Large Scale Unconstrained Open Set Face Database
+Archana Sapkota
+University of Colorado at Colorado Springs
+2Terrance E. Boult
+Securics Inc, Colorado Springs"
+070ab604c3ced2c23cce2259043446c5ee342fd6,An Active Illumination and Appearance (AIA) Model for Face Alignment,"AnActiveIlluminationandAppearance(AIA)ModelforFaceAlignment
+FatihKahraman,MuhittinGokmen
+IstanbulTechnicalUniversity,
+ComputerScienceDept.,Turkey
+{fkahraman,
+InformaticsandMathematicalModelling,Denmark
+SuneDarkner,RasmusLarsen
+TechnicalUniversityofDenmark"
+071135dfb342bff884ddb9a4d8af0e70055c22a1,Temporal 3D ConvNets: New Architecture and Transfer Learning for Video Classification,"New Architecture and Transfer Learning for Video Classiﬁcation
+Temporal 3D ConvNets:
+Ali Diba1,4,(cid:63), Mohsen Fayyaz2,(cid:63), Vivek Sharma3, Amir Hossein Karami4, Mohammad Mahdi Arzani4,
+Rahman Yousefzadeh4, Luc Van Gool1,4
+ESAT-PSI, KU Leuven, 2University of Bonn, 3CV:HCI, KIT, Karlsruhe, 4Sensifai"
+0754e769eb613fd3968b6e267a301728f52358be,Towards a Watson that sees: Language-guided action recognition for robots,"Towards a Watson That Sees: Language-Guided Action Recognition for
+Robots
+Ching L. Teo, Yezhou Yang, Hal Daum´e III, Cornelia Ferm¨uller and Yiannis Aloimonos"
+07c83f544d0604e6bab5d741b0bf9a3621d133da,Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition,"Learning Spatio-Temporal Features with 3D Residual Networks
+for Action Recognition
+Kensho Hara, Hirokatsu Kataoka, Yutaka Satoh
+National Institute of Advanced Industrial Science and Technology (AIST)
+Tsukuba, Ibaraki, Japan
+{kensho.hara, hirokatsu.kataoka,"
+0717b47ab84b848de37dbefd81cf8bf512b544ac,Robust Face Recognition and Tagging in Visual Surveillance System,"International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622
+International Conference on Humming Bird ( 01st March 2014)
+RESEARCH ARTICLE
+OPEN ACCESS
+Robust Face Recognition and Tagging in Visual Surveillance
+Kavitha MS 1, Siva Pradeepa S2
+System
+Kavitha MS Author is currently pursuing M.E(CSE)in VINS Christian college of Engineering,Nagercoil.
+Siva pradeepa,Assistant Lecturer in VINS Christian college of Engineering"
+0750a816858b601c0dbf4cfb68066ae7e788f05d,CosFace: Large Margin Cosine Loss for Deep Face Recognition,"CosFace: Large Margin Cosine Loss for Deep Face Recognition
+Hao Wang, Yitong Wang, Zheng Zhou, Xing Ji, Dihong Gong, Jingchao Zhou,
+Zhifeng Li∗, and Wei Liu∗
+Tencent AI Lab"
+078d507703fc0ac4bf8ca758be101e75ea286c80,Large - Scale Content Based Face Image Retrieval using Attribute Enhanced,"ISSN: 2321-8169
+International Journal on Recent and Innovation Trends in Computing and Communication
+Volume: 3 Issue: 8
+5287 - 5296
+________________________________________________________________________________________________________________________________
+Large- Scale Content Based Face Image Retrieval using Attribute Enhanced
+Sparse Codewords.
+Chaitra R,
+Mtech Digital Coomunication Engineering
+Acharya Institute Of Technology
+Bangalore"
+0716e1ad868f5f446b1c367721418ffadfcf0519,Interactively Guiding Semi-Supervised Clustering via Attribute-Based Explanations,"Interactively Guiding Semi-Supervised
+Clustering via Attribute-Based Explanations
+Shrenik Lad and Devi Parikh
+Virginia Tech, Blacksburg, VA, USA"
+0726a45eb129eed88915aa5a86df2af16a09bcc1,Introspective perception: Learning to predict failures in vision systems,"Introspective Perception: Learning to Predict Failures in Vision Systems
+Shreyansh Daftry, Sam Zeng, J. Andrew Bagnell and Martial Hebert"
+0742d051caebf8a5d452c03c5d55dfb02f84baab,Real-time geometric motion blur for a deforming polygonal mesh,"Real-Time Geometric Motion Blur for a Deforming Polygonal Mesh
+Nathan Jones
+Formerly: Texas A&M University
+Currently: The Software Group"
+38d56ddcea01ce99902dd75ad162213cbe4eaab7,Sense Beauty by Label Distribution Learning,Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
+389334e9a0d84bc54bcd5b94b4ce4c5d9d6a2f26,Facial parameter extraction system based on active contours,"FACIAL PARAMETER EXTRACTION SYSTEM BASED ON ACTIVE CONTOURS
+Montse Pardàs, Marcos Losada
+Universitat Politècnica de Catalunya, Barcelona, Spain"
+38f7f3c72e582e116f6f079ec9ae738894785b96,A New Technique for Face Matching after Plastic Surgery in Forensics,"IJARCCE
+ISSN (Online) 2278-1021
+ISSN (Print) 2319 5940
+International Journal of Advanced Research in Computer and Communication Engineering
+Vol. 4, Issue 11, November 2015
+A New Technique for Face Matching after
+Plastic Surgery in Forensics
+Anju Joseph1, Nilu Tressa Thomas2, Neethu C. Sekhar3
+Student, Dept. of CSE, Amal Jyothi College of Engineering, Kanjirappally, India 1,2
+Asst. Professor, Dept. of CSE, Amal Jyothi College of Engineering, Kanjirappally, India 3
+I.  INTRODUCTION
+Facial  recognition  is  one  of  the  most  important    task  that
+forensic  examiners  execute
+their
+investigation. This work focuses on analysing the effect of
+plastic  surgery  in  face  recognition  algorithms.  It  is
+imperative for the subsequent facial recognition systems to
+e  capable  of  addressing  this  significant  issue  and
+ccordingly  there  is  a  need  for  more  research  in  this
+important area."
+38679355d4cfea3a791005f211aa16e76b2eaa8d,Evolutionary Cross-Domain Discriminative Hessian Eigenmaps,"Title
+Evolutionary cross-domain discriminative Hessian Eigenmaps
+Author(s)
+Si, S; Tao, D; Chan, KP
+Citation
+Issued Date
+http://hdl.handle.net/10722/127357
+Rights
+This work is licensed under a Creative Commons Attribution-
+NonCommercial-NoDerivatives 4.0 International License.; ©2010
+IEEE. Personal use of this material is permitted. However,
+permission to reprint/republish this material for advertising or
+promotional purposes or for creating new collective works for
+resale or redistribution to servers or lists, or to reuse any
+opyrighted component of this work in other works must be
+obtained from the IEEE."
+38682c7b19831e5d4f58e9bce9716f9c2c29c4e7,Movie Character Identification Using Graph Matching Algorithm,"International Journal of Computer Trends and Technology (IJCTT) – Volume 18 Number 5 – Dec 2014
+Movie Character Identification Using Graph Matching
+Algorithm
+Shaik. Kartheek.*1, A.Srinivasa Reddy*2
+M.Tech Scholar, Dept of CSE, QISCET, ONGOLE, Dist: Prakasam, AP, India.
+Associate Professor, Department of CSE, QISCET, ONGOLE, Dist: Prakasam, AP, India"
+3803b91e784922a2dacd6a18f61b3100629df932,Temporal Multimodal Fusion for Video Emotion Classification in the Wild,"Temporal Multimodal Fusion
+for Video Emotion Classification in the Wild
+Valentin Vielzeuf∗
+Orange Labs
+Cesson-Sévigné, France
+Stéphane Pateux
+Orange Labs
+Cesson-Sévigné, France
+Frédéric Jurie
+Normandie Univ., UNICAEN,
+ENSICAEN, CNRS
+Caen, France"
+38eea307445a39ee7902c1ecf8cea7e3dcb7c0e7,Multi-distance Support Matrix Machines,"Noname manuscript No.
+(will be inserted by the editor)
+Multi-distance Support Matrix Machine
+Yunfei Ye1
+· Dong Han1
+Received: date / Accepted: date"
+384f972c81c52fe36849600728865ea50a0c4670,"Multi-Fold Gabor, PCA and ICA Filter Convolution Descriptor for Face Recognition","Multi-Fold Gabor, PCA and ICA Filter
+Convolution Descriptor for Face Recognition
+Cheng Yaw Low, Andrew Beng Jin Teoh, Senior Member, IEEE, Cong Jie Ng"
+38f1fac3ed0fd054e009515e7bbc72cdd4cf801a,Finding Person Relations in Image Data of the Internet Archive,"Finding Person Relations in Image Data of the
+Internet Archive
+Eric M¨uller-Budack1,2[0000−0002−6802−1241],
+Kader Pustu-Iren1[0000−0003−2891−9783], Sebastian Diering1, and
+Ralph Ewerth1,2[0000−0003−0918−6297]
+Leibniz Information Centre for Science and Technology (TIB), Hannover, Germany
+L3S Research Center, Leibniz Universit¨at Hannover, Germany"
+380d5138cadccc9b5b91c707ba0a9220b0f39271,Deep Imbalanced Learning for Face Recognition and Attribute Prediction,"Deep Imbalanced Learning for Face Recognition
+nd Attribute Prediction
+Chen Huang, Yining Li, Chen Change Loy, Senior Member, IEEE and Xiaoou Tang, Fellow, IEEE"
+38215c283ce4bf2c8edd597ab21410f99dc9b094,The SEMAINE Database: Annotated Multimodal Records of Emotionally Colored Conversations between a Person and a Limited Agent,"The SEMAINE Database: Annotated Multimodal Records of
+Emotionally Colored Conversations between a Person and a Limited
+Agent
+McKeown, G., Valstar, M., Cowie, R., Pantic, M., & Schröder, M. (2012). The SEMAINE Database: Annotated
+Multimodal Records of Emotionally Colored Conversations between a Person and a Limited Agent. IEEE
+Transactions on Affective Computing, 3(1), 5-17. DOI: 10.1109/T-AFFC.2011.20
+Published in:
+Document Version:
+Peer reviewed version
+Queen's University Belfast - Research Portal:
+Link to publication record in Queen's University Belfast Research Portal
+General rights
+Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other
+opyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated
+with these rights.
+Take down policy
+The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to
+ensure that content in the Research Portal does not infringe any person's rights, or applicable UK laws. If you discover content in the
+Research Portal that you believe breaches copyright or violates any law, please contact
+Download date:05. Nov. 2018"
+38183fe28add21693729ddeaf3c8a90a2d5caea3,Scale-Aware Face Detection,"Scale-Aware Face Detection
+Zekun Hao1, Yu Liu1, Hongwei Qin2, Junjie Yan2, Xiu Li2, Xiaolin Hu2
+SenseTime, 2Tsinghua University
+{haozekun,"
+3802da31c6d33d71b839e260f4022ec4fbd88e2d,Deep Attributes for One-Shot Face Recognition,"Deep Attributes for One-Shot Face Recognition
+Aishwarya Jadhav1,3, Vinay P. Namboodiri2, and K. S. Venkatesh 3
+Xerox Research Center India, 2Department of Computer Science,
+Department of Electrical Engineering, IIT Kanpur"
+00fb2836068042c19b5197d0999e8e93b920eb9c,Genetic Algorithm for Weight Optimization in Descriptor based Face Recognition Methods,
+0077cd8f97cafd2b389783858a6e4ab7887b0b6b,Face Image Reconstruction from Deep Templates,"MAI et al.: ON THE RECONSTRUCTION OF DEEP FACE TEMPLATES
+On the Reconstruction of Deep Face Templates
+Guangcan Mai, Kai Cao, Pong C. Yuen, Senior Member, IEEE, and Anil K. Jain, Life Fellow, IEEE"
+00214fe1319113e6649435cae386019235474789,Face Recognition using Distortion Models,"Bachelorarbeit im Fach Informatik
+Face Recognition using
+Distortion Models
+Mathematik, Informatik und Naturwissenschaften der
+RHEINISCH-WESTFÄLISCHEN TECHNISCHEN HOCHSCHULE AACHEN
+Der Fakultät für
+Lehrstuhl für Informatik VI
+Prof. Dr.-Ing. H. Ney
+vorgelegt von:
+Harald Hanselmann
+Matrikelnummer 252400
+Gutachter:
+Prof. Dr.-Ing. H. Ney
+Prof. Dr. B. Leibe
+Betreuer:
+Dipl.-Inform. Philippe Dreuw
+September 2009"
+004e3292885463f97a70e1f511dc476289451ed5,Quadruplet-Wise Image Similarity Learning,"Quadruplet-wise Image Similarity Learning
+Marc T. Law
+Nicolas Thome
+Matthieu Cord
+LIP6, UPMC - Sorbonne University, Paris, France
+{Marc.Law, Nicolas.Thome,"
+00f0ed04defec19b4843b5b16557d8d0ccc5bb42,Modeling Spatial and Temporal Cues for Multi-label Facial Action Unit Detection,
+0037bff7be6d463785d4e5b2671da664cd7ef746,Multiple Instance Metric Learning from Automatically Labeled Bags of Faces,"Author manuscript, published in ""European Conference on Computer Vision (ECCV '10) 6311 (2010) 634--647""
+DOI : 10.1007/978-3-642-15549-9_46"
+00d9d88bb1bdca35663946a76d807fff3dc1c15f,Subjects and Their Objects: Localizing Interactees for a Person-Centric View of Importance,"Subjects and Their Objects: Localizing Interactees for a
+Person-Centric View of Importance
+Chao-Yeh Chen · Kristen Grauman"
+00a3cfe3ce35a7ffb8214f6db15366f4e79761e3,Using Kinect for real-time emotion recognition via facial expressions,"Qi-rong Mao, Xin-yu Pan, Yong-zhao Zhan, Xiang-jun Shen, 2015. Using
+Kinect for real-time emotion recognition via facial expressions. Frontiers of
+Information Technology & Electronic Engineering, 16(4):272-282.
+[doi:10.1631/FITEE.1400209]
+Using Kinect for real-time emotion
+recognition via facial expressions
+Key words: Kinect, Emotion recognition, Facial expression, Real-time
+lassification, Fusion algorithm, Support vector machine (SVM)
+Contact: Qi-rong Mao
+E-mail:
+ORCID: http://orcid.org/0000-0002-5021-9057
+Front Inform Technol & Electron Eng"
+004a1bb1a2c93b4f379468cca6b6cfc6d8746cc4,Balanced k-Means and Min-Cut Clustering,"Balanced k-Means and Min-Cut Clustering
+Xiaojun Chang, Feiping Nie, Zhigang Ma, and Yi Yang"
+00d94b35ffd6cabfb70b9a1d220b6823ae9154ee,Discriminative Bayesian Dictionary Learning for Classification,"Discriminative Bayesian Dictionary Learning
+for Classiﬁcation
+Naveed Akhtar, Faisal Shafait, and Ajmal Mian"
+006f283a50d325840433f4cf6d15876d475bba77,Preserving Structure in Model-Free Tracking,"Preserving Structure in Model-Free Tracking
+Lu Zhang and Laurens van der Maaten"
+00d931eccab929be33caea207547989ae7c1ef39,The Natural Input Memory Model,"The Natural Input Memory Model
+Joyca P.W. Lacroix
+Department of Computer Science, IKAT, Universiteit Maastricht, St. Jacobsstraat 6, 6211 LB Maastricht, The Netherlands
+Department of Psychology, Universiteit van Amsterdam, Roeterstraat 15, 1018 WB Amsterdam, The Netherlands
+Jaap M.J. Murre
+Department of Computer Science, IKAT, Universiteit Maastricht, St. Jacobsstraat 6, 6211 LB Maastricht, The Netherlands
+Eric O. Postma
+H. Jaap van den Herik"
+0052de4885916cf6949a6904d02336e59d98544c,Generalized Low Rank Approximations of Matrices,"005 Springer Science + Business Media, Inc. Manufactured in The Netherlands.
+DOI: 10.1007/s10994-005-3561-6
+Generalized Low Rank Approximations of Matrices
+JIEPING YE
+Department of Computer Science & Engineering,University of Minnesota-Twin Cities, Minneapolis,
+MN 55455, USA
+Editor:
+Peter Flach
+Published online: 12 August 2005"
+6e198f6cc4199e1c4173944e3df6f39a302cf787,MORPH-II: Inconsistencies and Cleaning Whitepaper,"MORPH-II: Inconsistencies and Cleaning Whitepaper
+Participants: G. Bingham, B. Yip, M. Ferguson, and C. Nansalo
+Mentors: C. Chen, Y. Wang, and T. Kling
+NSF-REU Site at UNC Wilmington, Summer 2017"
+6eba25166fe461dc388805cc2452d49f5d1cdadd,"ALBANIE, VEDALDI: LEARNING GRIMACES BY WATCHING TV 1 Learning Grimaces by Watching TV","Pages 122.1-122.12
+DOI: https://dx.doi.org/10.5244/C.30.122"
+6e8a81d452a91f5231443ac83e4c0a0db4579974,Illumination robust face representation based on intrinsic geometrical information,"Illumination robust face representation based on intrinsic geometrical
+information
+Soyel, H; Ozmen, B; McOwan, PW
+This is a pre-copyedited, author-produced PDF of an article accepted for publication in IET
+Conference on Image Processing (IPR 2012). The version of record is available
+http://ieeexplore.ieee.org/document/6290632/?arnumber=6290632&tag=1
+For additional information about this publication click this link.
+http://qmro.qmul.ac.uk/xmlui/handle/123456789/16147
+Information about this research object was correct at the time of download; we occasionally
+make corrections to records, please therefore check the published record when citing. For
+more information contact"
+6ecd4025b7b5f4894c990614a9a65e3a1ac347b2,Automatic Naming of Character using Video Streaming for Face Recognition with Graph Matching,"International Journal on Recent and Innovation Trends in Computing and Communication
+ISSN: 2321-8169
+Volume: 2 Issue: 5
+1275– 1281
+_______________________________________________________________________________________________
+Automatic Naming of Character using Video Streaming for Face
+Recognition with Graph Matching
+Nivedita.R.Pandey
+Ranjan.P.Dahake
+PG Student at MET’s IOE Bhujbal Knowledge City,
+PG Student at MET’s IOE Bhujbal Knowledge City,
+Nasik, Maharashtra, India,
+Nasik, Maharashtra, India,"
+6e9a8a34ab5b7cdc12ea52d94e3462225af2c32c,Fusing Aligned and Non-aligned Face Information for Automatic Affect Recognition in the Wild: A Deep Learning Approach,"Fusing Aligned and Non-Aligned Face Information
+for Automatic Affect Recognition in the Wild: A Deep Learning Approach
+Bo-Kyeong Kim, Suh-Yeon Dong, Jihyeon Roh, Geonmin Kim, Soo-Young Lee
+Computational NeuroSystems Laboratory (CNSL)
+Korea Advanced Institute of Science and Technology (KAIST)
+{bokyeong1015, {rohleejh, gmkim90,"
+6e3a181bf388dd503c83dc324561701b19d37df1,Finding a low-rank basis in a matrix subspace,"Finding a low-rank basis in a matrix subspace
+Yuji Nakatsukasa · Tasuku Soma ·
+Andr´e Uschmajew"
+6ef1996563835b4dfb7fda1d14abe01c8bd24a05,Nonparametric Part Transfer for Fine-Grained Recognition,"Nonparametric Part Transfer for Fine-grained Recognition
+Christoph G¨oring, Erik Rodner, Alexander Freytag, and Joachim Denzler∗
+Computer Vision Group, Friedrich Schiller University Jena
+www.inf-cv.uni-jena.de"
+6e8c3b7d25e6530a631ea01fbbb93ac1e8b69d2f,"Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution","Deep Episodic Memory: Encoding, Recalling, and Predicting
+Episodic Experiences for Robot Action Execution
+Jonas Rothfuss∗†, Fabio Ferreira∗†, Eren Erdal Aksoy ‡, You Zhou† and Tamim Asfour†"
+6e911227e893d0eecb363015754824bf4366bdb7,Wasserstein Divergence for GANs,"Wasserstein Divergence for GANs
+Jiqing Wu1, Zhiwu Huang1, Janine Thoma1, Dinesh Acharya1, and
+Luc Van Gool1,2
+Computer Vision Lab, ETH Zurich, Switzerland
+VISICS, KU Leuven, Belgium"
+6ee8a94ccba10062172e5b31ee097c846821a822,How to solve classification and regression problems on high-dimensional data with a supervised extension of slow feature analysis,"Submitted 3/13; Revised 10/13; Published 12/13
+How to Solve Classiﬁcation and Regression Problems on
+High-Dimensional Data with a Supervised
+Extension of Slow Feature Analysis
+Alberto N. Escalante-B.
+Laurenz Wiskott
+Institut f¨ur Neuroinformatik
+Ruhr-Universit¨at Bochum
+Bochum D-44801, Germany
+Editor: David Dunson"
+6e379f2d34e14efd85ae51875a4fa7d7ae63a662,A New Multi-modal Biometric System Based on Fingerprint and Finger Vein Recognition,"A NEW MULTI-MODAL BIOMETRIC SYSTEM
+BASED ON FINGERPRINT AND FINGER
+VEIN RECOGNITION
+Naveed AHMED
+Master's Thesis
+Department of Software Engineering
+Advisor: Prof. Dr. Asaf VAROL
+JULY-2014"
+6e0a05d87b3cc7e16b4b2870ca24cf5e806c0a94,Random Graphs for Structure Discovery in High-dimensional Data,"RANDOM GRAPHS FOR STRUCTURE
+DISCOVERY IN HIGH-DIMENSIONAL DATA
+Jos¶e Ant¶onio O. Costa
+A dissertation submitted in partial fulflllment
+of the requirements for the degree of
+Doctor of Philosophy
+(Electrical Engineering: Systems)
+in The University of Michigan
+Doctoral Committee:
+Professor Alfred O. Hero III, Chair
+Professor Jeﬁrey A. Fessler
+Professor Susan A. Murphy
+Professor David L. Neuhoﬁ"
+6e1802874ead801a7e1072aa870681aa2f555f35,Exploring Feature Descritors for Face Recognition,"424407281/07/$20.00 ©2007 IEEE
+I  629
+ICASSP 2007
+*22+),)164,7+616DAIK??AIIB=B=?AHA?CEJE=CHEJDCHA=JOHAEAI.EIDAHB=?A -*/ 4A?AJO?=*E=HO2=JJAH*22+),)"
+6ed22b934e382c6f72402747d51aa50994cfd97b,Customized expression recognition for performance-driven cutout character animation,"Customized Expression Recognition for Performance-Driven
+Cutout Character Animation
+Xiang Yu†
+NEC Laboratories America
+Jianchao Yang‡ Wilmot Li§
+Snapchat"
+6e93fd7400585f5df57b5343699cb7cda20cfcc2,Comparing a novel model based on the transferable belief model with humans during the recognition of partially occluded facial expressions.,"http://journalofvision.org/9/2/22/
+Comparing a novel model based on the transferable
+elief model with humans during the recognition of
+partially occluded facial expressions
+Zakia Hammal
+Martin Arguin
+Frédéric Gosselin
+Département de Psychologie, Université de Montréal,
+Canada
+Département de Psychologie, Université de Montréal,
+Canada
+Département de Psychologie, Université de Montréal,
+Canada
+Humans recognize basic facial expressions effortlessly. Yet, despite a considerable amount of research, this task remains
+elusive for computer vision systems. Here, we compared the behavior of one of the best computer models of facial
+expression recognition (Z. Hammal, L. Couvreur, A. Caplier, & M. Rombaut, 2007) with the behavior of human observers
+during the M. Smith, G. Cottrell, F. Gosselin, and P. G. Schyns (2005) facial expression recognition task performed on
+stimuli randomly sampled using Gaussian apertures. The modelVwhich we had to signiﬁcantly modify in order to give the
+bility to deal with partially occluded stimuliVclassiﬁes the six basic facial expressions (Happiness, Fear, Sadness,
+Surprise, Anger, and Disgust) plus Neutral from static images based on the permanent facial feature deformations and the"
+9ab463d117219ed51f602ff0ddbd3414217e3166,Weighted Transmedia Relevance Feedback for Image Retrieval and Auto-annotation,"Weighted Transmedia
+Relevance Feedback for
+Image Retrieval and
+Auto-annotation
+Thomas Mensink, Jakob Verbeek, Gabriela Csurka
+TECHNICAL
+REPORT
+N° 0415
+December 2011
+Project-Teams LEAR - INRIA
+nd TVPA - XRCE"
+9ac82909d76b4c902e5dde5838130de6ce838c16,Recognizing Facial Expressions Automatically from Video,"Recognizing Facial Expressions Automatically
+from Video
+Caifeng Shan and Ralph Braspenning
+Introduction
+Facial expressions, resulting from movements of the facial muscles, are the face
+hanges in response to a person’s internal emotional states, intentions, or social
+ommunications. There is a considerable history associated with the study on fa-
+ial expressions. Darwin (1872) was the ﬁrst to describe in details the speciﬁc fa-
+ial expressions associated with emotions in animals and humans, who argued that
+ll mammals show emotions reliably in their faces. Since that, facial expression
+nalysis has been a area of great research interest for behavioral scientists (Ekman,
+Friesen, and Hager, 2002). Psychological studies (Mehrabian, 1968; Ambady and
+Rosenthal, 1992) suggest that facial expressions, as the main mode for non-verbal
+ommunication, play a vital role in human face-to-face communication. For illus-
+tration, we show some examples of facial expressions in Fig. 1.
+Computer recognition of facial expressions has many important applications in
+intelligent human-computer interaction, computer animation, surveillance and se-
+urity, medical diagnosis, law enforcement, and awareness systems (Shan, 2007).
+Therefore, it has been an active research topic in multiple disciplines such as psy-
+hology, cognitive science, human-computer interaction, and pattern recognition."
+9ac15845defcd0d6b611ecd609c740d41f0c341d,Robust Color-based Vision for Mobile Robots,"Copyright
+Juhyun Lee"
+9af1cf562377b307580ca214ecd2c556e20df000,International Journal of Advanced Studies in Computer Science and Engineering,"Feb. 28
+International Journal of Advanced Studies in Computer Science and Engineering
+IJASCSE, Volume 4, Issue 2, 2015
+Video-Based Facial Expression Recognition
+Using Local Directional Binary Pattern
+Sahar Hooshmand, Ali Jamali Avilaq, Amir Hossein Rezaie
+Electrical Engineering Dept., AmirKabir Univarsity of Technology
+Tehran, Iran"
+9a23a0402ae68cc6ea2fe0092b6ec2d40f667adb,High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs,"High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
+Ting-Chun Wang1 Ming-Yu Liu1
+Jun-Yan Zhu2 Andrew Tao1
+Jan Kautz1 Bryan Catanzaro1
+NVIDIA Corporation
+UC Berkeley
+Figure 1: We propose a generative adversarial framework for synthesizing 2048 × 1024 images from semantic label maps
+(lower left corner in (a)). Compared to previous work [5], our results express more natural textures and details. (b) We can
+hange labels in the original label map to create new scenes, like replacing trees with buildings. (c) Our framework also
+llows a user to edit the appearance of individual objects in the scene, e.g. changing the color of a car or the texture of a road.
+Please visit our website for more side-by-side comparisons as well as interactive editing demos."
+9a7858eda9b40b16002c6003b6db19828f94a6c6,Mooney face classification and prediction by learning across tone,"MOONEY FACE CLASSIFICATION AND PREDICTION BY LEARNING ACROSS TONE
+Tsung-Wei Ke(cid:63)†
+Stella X. Yu(cid:63)†
+David Whitney(cid:63)
+(cid:63) UC Berkeley / †ICSI"
+9a276c72acdb83660557489114a494b86a39f6ff,Emotion Classification through Lower Facial Expressions using Adaptive Support Vector Machines,"Emotion Classification through Lower Facial Expressions using Adaptive
+Support Vector Machines
+Porawat Visutsak
+Department of Information Technology, Faculty of Industrial Technology and Management,
+King Mongkut’s University of Technology North Bangkok,"
+9a42c519f0aaa68debbe9df00b090ca446d25bc4,Face Recognition via Centralized Coordinate Learning,"Face Recognition via Centralized Coordinate
+Learning
+Xianbiao Qi, Lei Zhang"
+9aad8e52aff12bd822f0011e6ef85dfc22fe8466,Temporal-Spatial Mapping for Action Recognition,"Temporal-Spatial Mapping for Action Recognition
+Xiaolin Song, Cuiling Lan, Wenjun Zeng, Junliang Xing, Jingyu Yang, and Xiaoyan Sun"
+363ca0a3f908859b1b55c2ff77cc900957653748,Local Binary Patterns and Linear Programming using Facial Expression,"International Journal of Computer Trends and Technology (IJCTT) – volume 1 Issue 3 Number 4 – Aug 2011
+Local Binary Patterns and Linear Programming using
+Facial Expression
+Ms.P.Jennifer
+#MCA Department, Bharath Institute of Science and Technology
++B.Tech (C.S.E), Bharath University , Chennai – 73.
+Dr. A. Muthu kumaravel
+#MCA Department, Bharath Institute of Science and Technology
++B.Tech (C.S.E), Bharath University , Chennai – 73."
+36939e6a365e9db904d81325212177c9e9e76c54,"Assessing the Accuracy of Four Popular Face Recognition Tools for Inferring Gender, Age, and Race","Assessing the Accuracy of Four Popular Face Recognition Tools for
+Inferring Gender, Age, and Race
+Soon-Gyo Jung, Jisun An, Haewoon Kwak, Joni Salminen, Bernard J. Jansen
+Qatar Computing Research Institute, HBKU
+HBKU Research Complex, Doha, P.O. Box 34110, Qatar"
+3646b42511a6a0df5470408bc9a7a69bb3c5d742,Detection of Facial Parts based on ABLATA,"International Journal of Computer Applications (0975 – 8887)
+Applications of Computers and Electronics for the Welfare of Rural Masses (ACEWRM) 2015
+Detection of Facial Parts based on ABLATA
+Siddhartha Choubey
+Shri Shankaracharya
+Technical Campus, Bhilai
+Vikas Singh
+Shri Shankaracharya
+Technical Campus, Bhilai
+Abha Choubey
+Shri Shankaracharya
+Technical Campus, Bhilai"
+36fe39ed69a5c7ff9650fd5f4fe950b5880760b0,Tracking von Gesichtsmimik mit Hilfe von Gitterstrukturen zur Klassifikation von schmerzrelevanten Action Units,"Tracking von Gesichtsmimik
+mit Hilfe von Gitterstrukturen
+zur Klassiﬁkation von schmerzrelevanten Action
+Units
+Christine Barthold1, Anton Papst1, Thomas Wittenberg1
+Christian K¨ublbeck1, Stefan Lautenbacher2, Ute Schmid2, Sven Friedl1,3
+Fraunhofer-Institut f¨ur Integrierte Schaltungen IIS, Erlangen,
+Otto-Friedrich-Universit¨at Bamberg, 3Universit¨atsklinkum Erlangen
+Kurzfassung. In der Schmerzforschung werden schmerzrelevante Mi-
+mikbewegungen von Probanden mittels des Facial Action Coding System
+klassiﬁziert. Die manuelle Klassiﬁkation hierbei ist aufw¨andig und eine
+utomatische (Vor-)klassiﬁkation k¨onnte den diagnostischen Wert dieser
+Analysen erh¨ohen sowie den klinischen Workflow unterst¨utzen. Der hier
+vorgestellte regelbasierte Ansatz erm¨oglicht eine automatische Klassiﬁka-
+tion ohne große Trainingsmengen vorklassiﬁzierter Daten. Das Verfahren
+erkennt und verfolgt Mimikbewegungen, unterst¨utzt durch ein Gitter,
+und ordnet diese Bewegungen bestimmten Gesichtsarealen zu. Mit die-
+sem Wissen kann aus den Bewegungen auf die zugeh¨origen Action Units
+geschlossen werden.
+Einleitung"
+36fc4120fc0638b97c23f97b53e2184107c52233,Introducing Celebrities in an Images using HAAR Cascade algorithm,"National Conference on Innovative Paradigms in Engineering & Technology (NCIPET-2013)
+Proceedings published by International Journal of Computer Applications® (IJCA)
+Introducing Celebrities in an Images using HAAR
+Cascade algorithm
+Jaya M. Jadhav
+Deipali V. Gore
+Asst. Professor
+Rashmi R. Tundalwar
+PES Modern College of Engg.
+PES Modern College of Engg.
+PES Modern College of Engg.
+Shivaji Nagar, Pune
+Shivaji Nagar, Pune
+Shivaji Nagar, Pune"
+36ce0b68a01b4c96af6ad8c26e55e5a30446f360,Facial expression recognition based on a mlp neural network using constructive training algorithm,"Multimed Tools Appl
+DOI 10.1007/s11042-014-2322-6
+Facial expression recognition based on a mlp neural
+network using constructive training algorithm
+Hayet Boughrara · Mohamed Chtourou ·
+Chokri Ben Amar · Liming Chen
+Received: 5 February 2014 / Revised: 22 August 2014 / Accepted: 13 October 2014
+© Springer Science+Business Media New York 2014"
+3674f3597bbca3ce05e4423611d871d09882043b,Facial Expression Spacial Charts for Describing Dynamic Diversity of Facial Expressions,"ISSN 1796-2048
+Volume 7, Number 4, August 2012
+Contents
+Special Issue: Multimedia Contents Security in Social Networks Applications
+Guest Editors: Zhiyong Zhang and Muthucumaru Maheswaran
+Guest Editorial
+Zhiyong Zhang and Muthucumaru Maheswaran
+SPECIAL ISSUE PAPERS
+DRTEMBB: Dynamic Recommendation Trust Evaluation Model Based on Bidding
+Gang Wang and Xiao-lin Gui
+Block-Based Parallel Intra Prediction Scheme for HEVC
+Jie Jiang, Baolong, Wei Mo, and Kefeng Fan
+Optimized LSB Matching Steganography Based on Fisher Information
+Yi-feng Sun, Dan-mei Niu, Guang-ming Tang, and Zhan-zhan Gao
+A Novel Robust Zero-Watermarking Scheme Based on Discrete Wavelet Transform
+Yu Yang, Min Lei, Huaqun Liu, Yajian Zhou, and Qun Luo
+Stego Key Estimation in LSB Steganography
+Jing Liu and Guangming Tang
+REGULAR PAPERS
+Facial Expression Spacial Charts for Describing Dynamic Diversity of Facial Expressions"
+365866dc937529c3079a962408bffaa9b87c1f06,Facial Feature Expression Based Approach for Human Face Recognition: A Review,"IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 1 Issue 3, May 2014.
+www.ijiset.com
+ISSN 2348 – 7968
+Facial Feature Expression Based Approach for Human Face
+Recognition: A Review
+Jageshvar K. Keche1, Mahendra P. Dhore2
+Department of Computer Science, SSESA, Science College, Congress Nagar, Nagpur, (MS)-India,
+Department of Electronics & Computer Science, RTM Nagpur University, Campus Nagpur, (MS)-India.
+required
+extraction  of"
+362a70b6e7d55a777feb7b9fc8bc4d40a57cde8c,A partial least squares based ranker for fast and accurate age estimation,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE
+ICASSP 2016"
+3630324c2af04fd90f8668f9ee9709604fe980fd,Image Classification With Tailored Fine-Grained Dictionaries,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSVT.2016.2607345, IEEE
+Transactions on Circuits and Systems for Video Technology
+Image Classiﬁcation with Tailored Fine-Grained
+Dictionaries
+Xiangbo Shu, Jinhui Tang, Guo-Jun Qi, Zechao Li, Yu-Gang Jiang and Shuicheng Yan"
+36cf96fe11a2c1ea4d999a7f86ffef6eea7b5958,RGB-D Face Recognition With Texture and Attribute Features,"RGB-D Face Recognition with Texture and
+Attribute Features
+Gaurav Goswami, Student Member, IEEE, Mayank Vatsa, Senior Member, IEEE, and Richa Singh, Senior
+Member, IEEE"
+36018404263b9bb44d1fddaddd9ee9af9d46e560,Occluded Face Recognition by Using Gabor Features,"OCCLUDED FACE RECOGNITION BY USING GABOR
+FEATURES
+Burcu Kepenekci 1,2, F. Boray Tek 1,2, Gozde Bozdagi Akar 1
+Department of Electrical And Electronics Engineering, METU, Ankara, Turkey
+7h%ł7$.(cid:3)%ł/7(1(cid:15)(cid:3)$QNDUD(cid:15)(cid:3)7XUNH\"
+366595171c9f4696ec5eef7c3686114fd3f116ad,Algorithms and Representations for Visual Recognition,"Algorithms and Representations for Visual
+Recognition
+Subhransu Maji
+Electrical Engineering and Computer Sciences
+University of California at Berkeley
+Technical Report No. UCB/EECS-2012-53
+http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-53.html
+May 1, 2012"
+3634b4dd263c0f330245c086ce646c9bb748cd6b,Temporal Localization of Fine-Grained Actions in Videos by Domain Transfer from Web Images,"Temporal Localization of Fine-Grained Actions in Videos
+y Domain Transfer from Web Images
+Chen Sun* Sanketh Shetty† Rahul Sukthankar† Ram Nevatia*
+*University of Southern California
+Google, Inc."
+5c6de2d9f93b90034f07860ae485a2accf529285,Compensating for pose and illumination in unconstrained periocular biometrics,"Int. J. Biometrics, Vol. X, No. Y, xxxx
+Compensating for pose and illumination in
+unconstrained periocular biometrics
+Chandrashekhar N. Padole and
+Hugo Proença*
+Department of Computer Science,
+IT – Instituto de Telecomunicações,
+University of Beira Interior,
+6200-Covilhã, Portugal
+Fax: +351-275-319899
+E-mail:
+E-mail:
+*Corresponding author"
+5cbe1445d683d605b31377881ac8540e1d17adf0,On 3D face reconstruction via cascaded regression in shape space,"On 3D Face Reconstruction via Cascaded Regression in Shape Space
+Feng Liu, Dan Zeng, Jing Li, Qijun Zhao
+College of Computer Science, Sichuan University, Chengdu, China"
+5c2e264d6ac253693469bd190f323622c457ca05,Improving large-scale face image retrieval using multi-level features,"978-1-4799-2341-0/13/$31.00 ©2013 IEEE
+ICIP 2013"
+5c5e1f367e8768a9fb0f1b2f9dbfa060a22e75c0,Reference Face Graph for Face Recognition,"Reference Face Graph for Face Recognition
+Mehran Kafai, Member, IEEE, Le An, Student Member, IEEE, and Bir Bhanu, Fellow, IEEE"
+5c35ac04260e281141b3aaa7bbb147032c887f0c,Face Detection and Tracking Control with Omni Car,"Face Detection and Tracking Control with Omni Car
+Jheng-Hao Chen, Tung-Yu Wu
+CS 231A Final Report
+June 31, 2016"
+5c435c4bc9c9667f968f891e207d241c3e45757a,"""How old are you?"" : Age Estimation with Tensors of Binary Gaussian Receptive Maps","RUIZ-HERNANDEZ, CROWLEY, LUX: HOW OLD ARE YOU?
+""How old are you?"" : Age Estimation with
+Tensors of Binary Gaussian Receptive Maps
+John A. Ruiz-Hernandez
+James L. Crowley
+Augustin Lux
+INRIA Grenoble Rhones-Alpes
+Research Center and Laboratoire
+d’Informatique de Grenoble (LIG)
+655 avenue de l’Europe
+8 334 Saint Ismier Cedex, France"
+5c02bd53c0a6eb361972e8a4df60cdb30c6e3930,Multimedia stimuli databases usage patterns: a survey report,"Multimedia stimuli databases usage patterns: a
+survey report
+M. Horvat1, S. Popović1 and K. Ćosić1
+University of Zagreb, Faculty of Electrical Engineering and Computing
+Department of Electric Machines, Drives and Automation
+Zagreb, Croatia"
+5c717afc5a9a8ccb1767d87b79851de8d3016294,A novel eye region based privacy protection scheme,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE
+ICASSP 2012"
+096eb8b4b977aaf274c271058feff14c99d46af3,Multi-observation visual recognition via joint dynamic sparse representation,"REPORT DOCUMENTATION PAGE
+Form Approved OMB NO. 0704-0188
+including
+for  reviewing
+information,
+this  collection  of
+information
+is  estimated
+to  average  1 hour  per  response,
+the  data  needed,  and  completing  and  reviewing
+this  collection  of
+instructions,
+The  public  reporting  burden
+Send  comments
+searching  existing  data  sources,  gathering  and  maintaining
+to  Washington
+regarding
+this  burden  estimate  or  any  other  aspect  of
+Information  Operations  and  Reports,  1215 Jefferson  Davis  Highway,  Suite  1204,  Arlington  VA,  22202-4302.
+Headquarters  Services,  Directorate"
+09137e3c267a3414314d1e7e4b0e3a4cae801f45,Two Birds with One Stone: Transforming and Generating Facial Images with Iterative GAN,"Noname manuscript No.
+(will be inserted by the editor)
+Two Birds with One Stone: Transforming and Generating
+Facial Images with Iterative GAN
+Dan Ma · Bin Liu · Zhao Kang · Jiayu Zhou · Jianke Zhu · Zenglin Xu
+Received: date / Accepted: date"
+09926ed62511c340f4540b5bc53cf2480e8063f8,Tubelet Detector for Spatio-Temporal Action Localization,"Action Tubelet Detector for Spatio-Temporal Action Localization
+Vicky Kalogeiton1,2
+Philippe Weinzaepfel3
+Vittorio Ferrari2
+Cordelia Schmid1"
+097340d3ac939ce181c829afb6b6faff946cdce0,Adding New Tasks to a Single Network with Weight Trasformations using Binary Masks,"Adding New Tasks to a Single Network with
+Weight Transformations using Binary Masks
+Massimiliano Mancini1,2, Elisa Ricci2,3, Barbara Caputo1,4, Samuel Rota Bul`o5
+Sapienza University of Rome, 2Fondazione Bruno Kessler,3University of Trento,
+Italian Institute of Technology, 5Mapillary Research"
+09718bf335b926907ded5cb4c94784fd20e5ccd8,"Recognizing partially occluded, expression variant faces from single training image per person with SOM and soft k-NN ensemble","Recognizing Partially Occluded, Expression Variant
+Faces From Single Training Image per Person
+With SOM and Soft k-NN Ensemble
+Xiaoyang Tan, Songcan Chen, Zhi-Hua Zhou, Member, IEEE, and Fuyan Zhang"
+0903bb001c263e3c9a40f430116d1e629eaa616f,An Empirical Study of Context in Object Detection,"CVPR 2009 Submission #987. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
+An Empirical Study of Context in Object Detection
+Anonymous CVPR submission
+Paper ID 987"
+09df62fd17d3d833ea6b5a52a232fc052d4da3f5,Mejora de Contraste y Compensación en Cambios de la Iluminación,"ISSN: 1405-5546
+Instituto Politécnico Nacional
+México
+Rivas Araiza, Edgar A.; Mendiola Santibañez, Jorge D.; Herrera Ruiz, Gilberto; González Gutiérrez,
+Carlos A.; Trejo Perea, Mario; Ríos Moreno, G. J.
+Mejora de Contraste y Compensación en Cambios de la Iluminación
+Instituto Politécnico Nacional
+Distrito Federal, México
+Disponible en: http://www.redalyc.org/articulo.oa?id=61509703
+Cómo citar el artículo
+Número completo
+Más información del artículo
+Página de la revista en redalyc.org
+Sistema de Información Científica
+Red de Revistas Científicas de América Latina, el Caribe, España y Portugal
+Proyecto académico sin fines de lucro, desarrollado bajo la iniciativa de acceso abierto"
+09f853ce12f7361c4b50c494df7ce3b9fad1d221,Random Forests for Real Time 3D Face Analysis,"myjournal manuscript No.
+(will be inserted by the editor)
+Random forests for real time 3D face analysis
+Gabriele Fanelli · Matthias Dantone · Juergen Gall · Andrea Fossati ·
+Luc Van Gool
+Received: date / Accepted: date"
+09750c9bbb074bbc4eb66586b20822d1812cdb20,Estimation of the neutral face shape using Gaussian Mixture Models,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE
+ICASSP 2012"
+097f674aa9e91135151c480734dda54af5bc4240,Face Recognition Based on Multiple Region Features,"Proc. VIIth Digital Image Computing: Techniques and Applications, Sun C., Talbot H., Ourselin S. and Adriaansen T. (Eds.), 10-12 Dec. 2003, Sydney
+Face Recognition Based on Multiple Region Features
+Jiaming Li, Geoff  Poulton, Ying Guo,  Rong-Yu Qiao
+CSIRO Telecommunications & Industrial Physics
+Australia
+Tel: 612 9372 4104, Fax: 612 9372 4411, Email:"
+5da740682f080a70a30dc46b0fc66616884463ec,Real-Time Head Pose Estimation Using Multi-variate RVM on Faces in the Wild,"Real-Time Head Pose Estimation Using
+Multi-Variate RVM on Faces in the Wild
+Mohamed Selim, Alain Pagani, Didier Stricker
+Augmented Vision Research Group,
+German Research Center for Artiﬁcial Intelligence (DFKI),
+Tripstaddterstr. 122, 67663 Kaiserslautern, Germany
+Technical University of Kaiserslautern
+http://www.av.dfki.de"
+5de5848dc3fc35e40420ffec70a407e4770e3a8d,WebVision Database: Visual Learning and Understanding from Web Data,"WebVision Database: Visual Learning and Understanding from Web Data
+Wen Li1, Limin Wang1, Wei Li2, Eirikur Agustsson1, Luc Van Gool1
+Computer Vision Laboratory, ETH Zurich
+Google Switzerland"
+5da139fc43216c86d779938d1c219b950dd82a4c,A Generalized Multiple Instance Learning Algorithm for Iterative Distillation and Cross-Granular Propagation of Video Annotations,"-4244-1437-7/07/$20.00 ©2007 IEEE
+II - 205
+ICIP 2007"
+5d185d82832acd430981ffed3de055db34e3c653,A Fuzzy Reasoning Model for Recognition of Facial Expressions,"A Fuzzy Reasoning Model for Recognition
+of Facial Expressions
+Oleg Starostenko1, Renan Contreras1, Vicente Alarcón Aquino1, Leticia Flores Pulido1,
+Jorge Rodríguez Asomoza1, Oleg Sergiyenko2, and Vira Tyrsa3
+Research Center CENTIA, Department of Computing, Electronics and Mechatronics,
+Universidad de las Américas, 72820, Puebla, Mexico
+{oleg.starostenko; renan.contrerasgz; vicente.alarcon; leticia.florespo;
+Engineering Institute, Autonomous University of Baja California, Blvd. Benito Juárez,
+Insurgentes Este, 21280, Mexicali, Baja California, Mexico
+Universidad Politécnica de Baja California, Mexicali, Baja California, Mexico"
+5d233e6f23b1c306cf62af49ce66faac2078f967,Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions,"RESEARCH ARTICLE
+Optimal Geometrical Set for Automated
+Marker Placement to Virtualized Real-Time
+Facial Emotions
+Vasanthan Maruthapillai, Murugappan Murugappan*
+School of Mechatronic Engineering, Universiti Malaysia Perlis, 02600, Ulu Pauh, Arau, Perlis, West Malaysia"
+5db075a308350c083c3fa6722af4c9765c4b8fef,The Novel Method of Moving Target Tracking Eyes Location based on SIFT Feature Matching and Gabor Wavelet Algorithm,"The Novel Method of Moving Target Tracking Eyes
+Location based on SIFT Feature Matching and Gabor
+Wavelet Algorithm
+* Jing Zhang, Caixia Yang, Kecheng Liu
+College of Computer and Information Engineering, Nanyang Institute of Technology,
+Henan Nanyang, 473004, China
+* Tel.: 0086+13838972861
+* E-mail:
+Sensors & Transducers, Vol. 154, Issue 7, July 2013, pp. 129-137
+SSSeeennnsssooorrrsss   &&&   TTTrrraaannnsssddduuuccceeerrrsss
+© 2013 by IFSA
+http://www.sensorsportal.com
+Received: 28 April 2013   /Accepted: 19 July 2013   /Published: 31 July 2013"
+5d7f8eb73b6a84eb1d27d1138965eb7aef7ba5cf,Robust Registration of Dynamic Facial Sequences,"Robust Registration of Dynamic Facial Sequences
+Evangelos Sariyanidi, Hatice Gunes, and Andrea Cavallaro"
+5db4fe0ce9e9227042144758cf6c4c2de2042435,Recognition of Facial Expression Using Haar Wavelet Transform,"INTERNATIONAL JOURNAL OF ELECTRICAL AND ELECTRONIC SYSTEMS RESEARCH, VOL.3, JUNE 2010
+Recognition of Facial Expression Using Haar
+Wavelet Transform
+M. Satiyan,  M.Hariharan,  R.Nagarajan
+paper
+features
+investigates"
+5d5cd6fa5c41eb9d3d2bab3359b3e5eb60ae194e,Face Recognition Algorithms,"Face Recognition Algorithms
+Proyecto Fin de Carrera
+June 16, 2010
+Ion Marqu´es
+Supervisor:
+Manuel Gra˜na"
+5d09d5257139b563bd3149cfd5e6f9eae3c34776,Pattern recognition with composite correlation filters designed with multi-objective combinatorial optimization,"Optics Communications 338 (2015) 77–89
+Contents lists available at ScienceDirect
+Optics Communications
+journal homepage: www.elsevier.com/locate/optcom
+Pattern recognition with composite correlation ﬁlters designed with
+multi-objective combinatorial optimization
+Victor H. Diaz-Ramirez a,n, Andres Cuevas a, Vitaly Kober b, Leonardo Trujillo c,
+Abdul Awwal d
+Instituto Politécnico Nacional – CITEDI, Ave. del Parque 1310, Mesade Otay, Tijuana B.C. 22510, México
+Department of Computer Science, CICESE, Carretera Ensenada-Tijuana 3918, Ensenada B.C. 22860, México
+Instituto Tecnológico de Tijuana, Blvd. Industrial y Ave. ITR TijuanaS/N, Mesa de Otay, Tijuana B.C. 22500, México
+d National Ignition Facility, Lawrence Livermore National Laboratory, Livermore, CA 94551, USA
+r t i c l e i n f o
+b s t r a c t
+Article history:
+Received 12 July 2014
+Accepted 16 November 2014
+Available online 23 October 2014
+Keywords:
+Object recognition"
+5d197c8cd34473eb6cde6b65ced1be82a3a1ed14,A Face Image Database for Evaluating Out-of-Focus Blur,"0AFaceImageDatabaseforEvaluatingOut-of-FocusBlurQiHan,QiongLiandXiamuNiuHarbinInstituteofTechnologyChina1.IntroductionFacerecognitionisoneofthemostpopularresearchﬁeldsofcomputervisionandmachinelearning(Tores(2004);Zhaoetal.(2003)).Alongwithinvestigationoffacerecognitionalgorithmsandsystems,manyfaceimagedatabaseshavebeencollected(Gross(2005)).Facedatabasesareimportantfortheadvancementoftheresearchﬁeld.Becauseofthenonrigidityandcomplex3Dstructureofface,manyfactorsinfluencetheperformanceoffacedetectionandrecognitionalgorithmssuchaspose,expression,age,brightness,contrast,noise,blurandetc.Someearlyfacedatabasesgatheredunderstrictlycontrolledenvironment(Belhumeuretal.(1997);Samaria&Harter(1994);Turk&Pentland(1991))onlyallowslightexpressionvariation.Toinvestigatetherelationshipsbetweenalgorithms’performanceandtheabovefactors,morefacedatabaseswithlargerscaleandvariouscharacterswerebuiltinthepastyears(Bailly-Bailliereetal.(2003);Flynnetal.(2003);Gaoetal.(2008);Georghiadesetal.(2001);Hallinan(1995);Phillipsetal.(2000);Simetal.(2003)).Forinstance,The""CAS-PEAL"",""FERET"",""CMUPIE"",and""YaleB""databasesincludevariousposes(Gaoetal.(2008);Georghiadesetal.(2001);Phillipsetal.(2000);Simetal.(2003));The""HarvardRL"",""CMUPIE""and""YaleB""databasesinvolvemorethan40differentconditionsinillumination(Georghiadesetal.(2001);Hallinan(1995);Simetal.(2003));Andthe""BANCA"",and""NDHID""databasescontainover10timesgathering(Bailly-Bailliereetal.(2003);Flynnetal.(2003)).Thesedatabaseshelpresearcherstoevaluateandimprovetheiralgorithmsaboutfacedetection,recognition,andotherpurposes.Blurisnotthemostimportantbutstillanotablefactoraffectingtheperformanceofabiometricsystem(Fronthaleretal.(2006);Zamanietal.(2007)).Themainreasonsleadingblurconsistinout-of-focusofcameraandmotionofobject,andtheout-of-focusblurismoresigniﬁcantintheapplicationenvironmentoffacerecognition(Eskicioglu&Fisher(1995);Kimetal.(1998);Tanakaetal.(2007);Yitzhaky&Kopeika(1996)).Toinvestigatetheinfluenceofbluronafacerecognitionsystem,afaceimagedatabasewithdifferentconditionsofclarityandefﬁcientblurevaluatingalgorithmsareneeded.Thischapterintroducesanewfacedatabasebuiltforthepurposeofblurevaluation.Theapplicationenvironmentsoffacerecognitionareanalyzedﬁrstly,thenaimagegatheringschemeisdesigned.Twotypicalgatheringfacilitiesareusedandthefocusstatusaredividedinto11steps.Further,theblurassessmentalgorithmsaresummarizedandthecomparisonbetweenthemisraisedonthevarious-claritydatabase.The7www.intechopen.com"
+5da2ae30e5ee22d00f87ebba8cd44a6d55c6855e,"When facial expressions do and do not signal minds: The role of face inversion, expression dynamism, and emotion type.","This is an Open Access document downloaded from ORCA, Cardiff University's institutional
+repository: http://orca.cf.ac.uk/111659/
+This is the author’s version of a work that was submitted to / accepted for publication.
+Citation for final published version:
+Krumhuber, Eva G, Lai, Yukun, Rosin, Paul and Hugenberg, Kurt 2018. When facial expressions
+Publishers page:
+Please note:
+Changes made as a result of publishing processes such as copy-editing, formatting and page
+numbers may not be reflected in this version. For the definitive version of this publication, please
+refer to the published source. You are advised to consult the publisher’s version if you wish to cite
+this paper.
+This version is being made available in accordance with publisher policies. See
+http://orca.cf.ac.uk/policies.html for usage policies. Copyright and moral rights for publications
+made available in ORCA are retained by the copyright holders."
+31625522950e82ad4dffef7ed0df00fdd2401436,Motion Representation with Acceleration Images,"Motion Representation with Acceleration Images
+Hirokatsu Kataoka, Yun He, Soma Shirakabe, Yutaka Satoh
+National Institute of Advanced Industrial Science and Technology (AIST)
+Tsukuba, Ibaraki, Japan
+{hirokatsu.kataoka, yun.he, shirakabe-s,"
+318e7e6daa0a799c83a9fdf7dd6bc0b3e89ab24a,Sparsity in Dynamics of Spontaneous Subtle Emotions: Analysis and Application,"Sparsity in Dynamics of Spontaneous
+Subtle Emotions: Analysis & Application
+Anh Cat Le Ngo, Member, IEEE, John See, Member, IEEE, Raphael C.-W. Phan, Member, IEEE"
+31c0968fb5f587918f1c49bf7fa51453b3e89cf7,Deep Transfer Learning for Person Re-identification,"Deep Transfer Learning for Person Re-identiﬁcation
+Mengyue Geng
+Yaowei Wang
+Tao Xiang
+Yonghong Tian"
+316e67550fbf0ba54f103b5924e6537712f06bee,Multimodal semi-supervised learning for image classification,"Multimodal semi-supervised learning
+for image classiﬁcation
+Matthieu Guillaumin, Jakob Verbeek, Cordelia Schmid
+LEAR team, INRIA Grenoble, France"
+31ef5419e026ef57ff20de537d82fe3cfa9ee741,Facial Expression Analysis Based on High Dimensional Binary Features,"Facial Expression Analysis Based on
+High Dimensional Binary Features
+Samira Ebrahimi Kahou, Pierre Froumenty, and Christopher Pal
+´Ecole Polytechique de Montr´eal, Universit´e de Montr´eal, Montr´eal, Canada
+{samira.ebrahimi-kahou, pierre.froumenty,"
+3176ee88d1bb137d0b561ee63edf10876f805cf0,Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation,"Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation
+Sina Honari1, Jason Yosinski2, Pascal Vincent1,4, Christopher Pal3
+University of Montreal, 2Cornell University, 3Ecole Polytechnique of Montreal, 4CIFAR
+{honaris,"
+31ace8c9d0e4550a233b904a0e2aabefcc90b0e3,Learning Deep Face Representation,"Learning Deep Face Representation
+Haoqiang Fan
+Megvii Inc.
+Zhimin Cao
+Megvii Inc.
+Yuning Jiang
+Megvii Inc.
+Qi Yin
+Megvii Inc.
+Chinchilla Doudou
+Megvii Inc."
+91811203c2511e919b047ebc86edad87d985a4fa,Expression Subspace Projection for Face Recognition from Single Sample per Person,"Expression Subspace Projection for Face
+Recognition from Single Sample per Person
+Hoda Mohammadzade, Student Member, IEEE, and Dimitrios Hatzinakos, Senior Member, IEEE"
+9117fd5695582961a456bd72b157d4386ca6a174,Recognition Using Dee Networks,"Facial Expression
+n Recognition Using Dee
+ep Neural
+Networks
+Junnan Li and Edmund Y. Lam
+Departm
+ment of Electrical and Electronic Engineering
+he University of Hong Kong, Pokfulam,
+Hong Kong"
+91067f298e1ece33c47df65236853704f6700a0b,Local Binary Pattern and Local Linear Regression for Pose Invariant Face Recognition,"IJSTE - International Journal of Science Technology & Engineering | Volume 2 | Issue 11 | May 2016
+ISSN (online): 2349-784X
+Local Binary Pattern and Local Linear
+Regression for Pose Invariant Face Recognition
+Raju Dadasab Patil
+M. Tech Student
+Shreekumar T
+Associate Professor
+Department of Computer Science & Engineering
+Department of Computer Science & Engineering
+Mangalore Institute of Engineering & Technology, Badaga
+Mangalore Institute of Engineering & Technology, Badaga
+Mijar, Moodbidri, Mangalore
+Mijar, Moodbidri, Mangalore
+Karunakara K
+Professor & Head of Dept.
+Department of Information Science & Engineering
+Sri SidarthaInstitute of Technology, Tumkur"
+919d3067bce76009ce07b070a13728f549ebba49,Time Based Re-ranking for Web Image Search,"International Journal of Scientific and Research Publications, Volume 4, Issue 6, June 2014
+ISSN 2250-3153
+Time Based Re-ranking for Web Image Search
+Ms. A.Udhayabharadhi *, Mr. R.Ramachandran **
+* MCA Student, Sri Manakula Vinayagar Engineering College, Pondicherry-605106
+** Assistant Professor dept of MCA, Sri Manakula Vinayagar Engineering College, Pondicherry-605106"
+91e57667b6fad7a996b24367119f4b22b6892eca,Probabilistic Corner Detection for Facial Feature,"Probabilistic  Corner  Detection  for  Facial  Feature
+Extraction
+Article
+Accepted version
+E. Ardizzone, M. La Cascia, M. Morana
+In Lecture Notes in Computer Science Volume 5716, 2009
+It  is  advisable  to  refer  to  the  publisher's  version  if  you  intend  to  cite
+from the work.
+Publisher: Springer
+http://link.springer.com/content/pdf/10.1007%2F978-3-
+642-04146-4_50.pdf"
+917bea27af1846b649e2bced624e8df1d9b79d6f,Ultra Power-Efficient CNN Domain Specific Accelerator with 9.3TOPS/Watt for Mobile and Embedded Applications,"Ultra Power-Efﬁcient CNN Domain Speciﬁc Accelerator with 9.3TOPS/Watt for
+Mobile and Embedded Applications
+Baohua Sun,
+Lin Yang,
+Patrick Dong, Wenhan Zhang,
+Gyrfalcon Technology Inc.
+Jason Dong, Charles Young
+900 McCarthy Blvd. Milpitas, CA 95035"
+91b1a59b9e0e7f4db0828bf36654b84ba53b0557,Simultaneous Hallucination and Recognition of Low-Resolution Faces Based on Singular Value Decomposition,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
+> REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) <
+Simultaneous Hallucination and Recognition of
+Low-Resolution Faces Based on Singular Value
+Decomposition
+Muwei Jian,  Kin-Man Lam*, Senior Member, IEEE
+(SVD)
+for  performing  both"
+911bef7465665d8b194b6b0370b2b2389dfda1a1,Learning Human Optical Flow,"RANJAN, ROMERO, BLACK: LEARNING HUMAN OPTICAL FLOW
+Learning Human Optical Flow
+MPI for Intelligent Systems
+Tübingen, Germany
+Amazon Inc.
+Anurag Ranjan1
+Javier Romero∗,2
+Michael J. Black1"
+91ead35d1d2ff2ea7cf35d15b14996471404f68d,Combining and Steganography of 3D Face Textures,"Combining and Steganography of 3D Face Textures
+Mohsen Moradi and Mohammad-Reza Rafsanjani-Sadeghi"
+91d513af1f667f64c9afc55ea1f45b0be7ba08d4,Automatic Face Image Quality Prediction,"Automatic Face Image Quality Prediction
+Lacey Best-Rowden, Student Member, IEEE, and Anil K. Jain, Life Fellow, IEEE"
+91e58c39608c6eb97b314b0c581ddaf7daac075e,Pixel-wise Ear Detection with Convolutional Encoder-Decoder Networks,"Pixel-wise Ear Detection with Convolutional
+Encoder-Decoder Networks
+ˇZiga Emerˇsiˇc 1, Luka Lan Gabriel 2, Vitomir ˇStruc 3 and Peter Peer 1"
+9131c990fad219726eb38384976868b968ee9d9c,Deep Facial Expression Recognition: A Survey,"Deep Facial Expression Recognition: A Survey
+Shan Li and Weihong Deng∗, Member, IEEE"
+911505a4242da555c6828509d1b47ba7854abb7a,Improved Active Shape Model for Facial Feature Localization,"IMPROVED ACTIVE SHAPE MODEL FOR FACIAL FEATURE LOCALIZATION
+Hui-Yu Huang and Shih-Hang Hsu
+National Formosa University, Taiwan
+Email:"
+915d4a0fb523249ecbc88eb62cb150a60cf60fa0,Comparison of Feature Extraction Techniques in Automatic Face Recognition Systems for Security Applications,"Comparison of Feature Extraction Techniques in Automatic
+Face Recognition Systems for Security Applications
+S .  Cruz-Llanas, J. Ortega-Garcia, E. Martinez-Torrico, J. Gonzalez-Rodriguez
+Dpto. Ingenieria Audiovisual y Comunicaciones, EUIT Telecomunicacion, Univ. PolitCcnica de Madrid, Spain
+{cruzll, jortega, etorrico,
+http://www.atvs.diac.upm.es"
+6582f4ec2815d2106957215ca2fa298396dde274,Discriminative Learning and Recognition of Image Set Classes Using Canonical Correlations,"JUNE 2007
+Discriminative Learning and Recognition
+of Image Set Classes Using
+Canonical Correlations
+Tae-Kyun Kim, Josef Kittler, Member, IEEE, and Roberto Cipolla, Member, IEEE"
+655d9ba828eeff47c600240e0327c3102b9aba7c,Kernel pooled local subspaces for classification,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 35, NO. 3, JUNE 2005
+Kernel Pooled Local Subspaces for Classiﬁcation
+Peng Zhang, Student Member, IEEE, Jing Peng, Member, IEEE, and Carlotta Domeniconi"
+656a59954de3c9fcf82ffcef926af6ade2f3fdb5,Convolutional Network Representation for Visual Recognition,"Convolutional Network Representation
+for Visual Recognition
+ALI SHARIF RAZAVIAN
+Doctoral Thesis
+Stockholm, Sweden, 2017"
+656aeb92e4f0e280576cbac57d4abbfe6f9439ea,Use of Image Enhancement Techniques for Improving Real Time Face Recognition Efficiency on Wearable Gadgets,"Journal of Engineering Science and Technology
+Vol. 12, No. 1 (2017) 155 - 167
+© School of Engineering, Taylor’s University
+USE OF IMAGE ENHANCEMENT TECHNIQUES
+FOR IMPROVING REAL TIME FACE RECOGNITION EFFICIENCY
+ON WEARABLE GADGETS
+MUHAMMAD EHSAN RANA1,*, AHMAD AFZAL ZADEH2,
+AHMAD MOHAMMAD MAHMOOD ALQURNEH3
+, 3Asia Pacific University of Technology & Innovation, Kuala Lumpur 57000, Malaysia
+Staffordshire University, Beaconside Stafford ST18 0AB, United Kingdom
+*Corresponding Author:"
+656f05741c402ba43bb1b9a58bcc5f7ce2403d9a,Supervised Learning Approaches for Automatic Structuring of Videos. (Méthodes d'apprentissage supervisé pour la structuration automatique de vidéos),"THÈSEPour obtenir le grade deDOCTEUR DE L’UNIVERSITÉ GRENOBLE ALPESSpécialité : Mathématiques et InformatiqueArrêté ministériel : 7 août 2006Présentée parDanila POTAPOVThèse dirigée par Cordelia SCHMID et codirigée par Zaid HARCHAOUIpréparée au sein de Inria Grenoble Rhône-Alpesdans l'École Doctorale Mathématiques, Sciences et technologies de l'information, InformatiqueSupervised Learning Approaches for Automatic Structuring of VideosThèse soutenue publiquement le « 22 Juillet 2015 »,devant le jury composé de : Prof. Cordelia SCHMID Inria Grenoble Rhône-Alpes, France, Directeur de thèseDr. Zaid HARCHAOUIInria Grenoble Rhône-Alpes, France, Co-encadrant de thèse Prof. Patrick PEREZTechnicolor Rennes, France, RapporteurProf. Ivan LAPTEVInria Paris Rocquencourt, France, Rapporteur, PrésidentDr. Florent PERRONNINFacebook AI Research, Paris, France, ExaminateurDr. Matthijs DOUZEInria Grenoble Rhône-Alpes, France, Examinateur"
+65817963194702f059bae07eadbf6486f18f4a0a,WhittleSearch: Interactive Image Search with Relative Attribute Feedback,"http://dx.doi.org/10.1007/s11263-015-0814-0
+WhittleSearch: Interactive Image Search with Relative Attribute
+Feedback
+Adriana Kovashka · Devi Parikh · Kristen Grauman
+Received: date / Accepted: date"
+6581c5b17db7006f4cc3575d04bfc6546854a785,Contextual Person Identification in Multimedia Data,"Contextual Person Identiﬁcation
+in Multimedia Data
+zur Erlangung des akademischen Grades eines
+Doktors der Ingenieurwissenschaften
+der Fakultät für Informatik
+des Karlsruher Instituts für Technologie (KIT)
+genehmigte
+Dissertation
+Dipl.-Inform. Martin Bäuml
+us Erlangen
+Tag der mündlichen Prüfung:
+8. November 2014
+Hauptreferent:
+Korreferent:
+Prof. Dr. Rainer Stiefelhagen
+Karlsruher Institut für Technologie
+Prof. Dr. Gerhard Rigoll
+Technische Universität München
+KIT – Universität des Landes Baden-Württemberg und nationales Forschungszentrum in der Helmholtz-Gemeinschaft
+www.kit.edu"
+653d19e64bd75648cdb149f755d59e583b8367e3,"Decoupling ""when to update"" from ""how to update""","Decoupling “when to update” from “how to
+update”
+Eran Malach and Shai Shalev-Shwartz
+School of Computer Science, The Hebrew University, Israel"
+65babb10e727382b31ca5479b452ee725917c739,Label Distribution Learning,"Label Distribution Learning
+Xin Geng*, Member, IEEE"
+62dccab9ab715f33761a5315746ed02e48eed2a0,A Short Note about Kinetics-600,"A Short Note about Kinetics-600
+Jo˜ao Carreira
+Eric Noland
+Andras Banki-Horvath
+Chloe Hillier
+Andrew Zisserman"
+62d1a31b8acd2141d3a994f2d2ec7a3baf0e6dc4,Noise-resistant network: a deep-learning method for face recognition under noise,"Ding et al. EURASIP Journal on Image and Video Processing  (2017) 2017:43
+DOI 10.1186/s13640-017-0188-z
+EURASIP Journal on Image
+nd Video Processing
+R ES EAR CH
+Noise-resistant network: a deep-learning
+method for face recognition under noise
+Yuanyuan Ding1,2, Yongbo Cheng1,2, Xiaoliu Cheng1, Baoqing Li1*, Xing You1 and Xiaobing Yuan1
+Open Access"
+62694828c716af44c300f9ec0c3236e98770d7cf,Identification of Action Units Related to Affective States in a Tutoring System for Mathematics,"Padrón-Rivera, G., Rebolledo-Mendez, G., Parra, P. P., & Huerta-Pacheco, N. S. (2016). Identification of Action Units Related to
+Identification of  Action Units Related to Affective States in a Tutoring System
+Gustavo Padrón-Rivera1, Genaro Rebolledo-Mendez1*, Pilar Pozos Parra2 and N. Sofia
+Facultad de Estadística e Informática, Universidad Veracruzana, Mexico // 2Universidad Juárez Autónoma de
+Tabasco, Mexico // // // //
+for Mathematics
+Huerta-Pacheco1
+*Corresponding author"
+62f0d8446adee6a5e8102053a63a61af07ac4098,Facial point detection using convolutional neural network transferred from a heterogeneous task,"FACIAL POINT DETECTION USING CONVOLUTIONAL NEURAL NETWORK
+TRANSFERRED FROM A HETEROGENEOUS TASK
+Takayoshi Yamashita* Taro Watasue** Yuji Yamauchi* Hironobu Fujiyoshi*
+**Tome R&D
+*Chubu University,
+200, Matsumoto-cho, Kasugai, AICHI"
+628a3f027b7646f398c68a680add48c7969ab1d9,Plan for Final Year Project : HKU-Face : A Large Scale Dataset for Deep Face Recognition,"Plan for Final Year Project:
+HKU-Face: A Large Scale Dataset for Deep Face
+Recognition
+Haicheng Wang
+035140108
+Haoyu Li
+035141841
+Introduction
+Face recognition has been one of the most successful techniques in the ﬁeld of artiﬁcial intelligence
+ecause of its surpassing human-level performance in academic experiments and broad application in
+the industrial world. Gaussian-face[1] and Facenet[2] hold state-of-the-art record using statistical
+method and deep-learning method respectively. What’s more, face recognition has been applied
+in various areas like authority checking and recording, fostering a large number of start-ups like
+Face++.
+Our ﬁnal year project will deal with the face recognition task by building a large-scaled and carefully-
+ﬁltered dataset. Our project plan speciﬁes our roadmap and current research process. This plan ﬁrst
+illustrates the signiﬁcance and potential enhancement in constructing large-scale face dataset for
+oth academics and companies. Then objectives to accomplish and related literature review will be
+expressed in detail. Next, methodologies used, scope of our project and challenges faced by us are
+described. The detailed timeline for this project follows as well as a small summary."
+62374b9e0e814e672db75c2c00f0023f58ef442c,Frontal face authentication using discriminating,"Frontalfaceauthenticationusingdiscriminatinggridswith
+morphologicalfeaturevectors
+A.Tefas
+C.Kotropoulos
+I.Pitas
+DepartmentofInformatics,AristotleUniversityofThessaloniki
+Box,Thessaloniki
+EDICSnumbers:-KNOWContentRecognitionandUnderstanding
+-MODAMultimodalandMultimediaEnvironments
+Anovelelasticgraphmatchingprocedurebasedonmultiscalemorphologicaloperations,thesocalled
+morphologicaldynamiclinkarchitecture,isdevelopedforfrontalfaceauthentication.Fastalgorithms
+forimplementingmathematicalmorphologyoperationsarepresented.Featureselectionbyemploying
+linearprojectionalgorithmsisproposed.Discriminatorypowercoe(cid:14)cientsthatweighthematching
+errorateachgridnodearederived.Theperformanceofmorphologicaldynamiclinkarchitecturein
+frontalfaceauthenticationisevaluatedintermsofthereceiveroperatingcharacteristicontheMVTS
+faceimagedatabase.Preliminaryresultsforfacerecognitionusingtheproposedtechniquearealso
+presented.
+Correspondingauthor:I.Pitas
+DRAFT
+September
+626859fe8cafd25da13b19d44d8d9eb6f0918647,Activity Recognition Based on a Magnitude-Orientation Stream Network,"Activity Recognition based on a
+Magnitude-Orientation Stream Network
+Carlos Caetano, Victor H. C. de Melo, Jefersson A. dos Santos, William Robson Schwartz
+Smart Surveillance Interest Group, Department of Computer Science
+Universidade Federal de Minas Gerais, Belo Horizonte, Brazil"
+62007c30f148334fb4d8975f80afe76e5aef8c7f,Eye In-Painting with Exemplar Generative Adversarial Networks,"Eye In-Painting with Exemplar Generative Adversarial Networks
+Brian Dolhansky, Cristian Canton Ferrer
+Facebook Inc.
+Hacker Way, Menlo Park (CA), USA
+{bdol,"
+62a30f1b149843860938de6dd6d1874954de24b7,Fast Algorithm for Updating the Discriminant Vectors of Dual-Space LDA,"Fast Algorithm for Updating the Discriminant Vectors
+of Dual-Space LDA
+Wenming Zheng, Member, IEEE, and Xiaoou Tang, Fellow, IEEE"
+62e0380a86e92709fe2c64e6a71ed94d152c6643,Facial emotion recognition with expression energy,"Facial Emotion Recognition With Expression Energy
+Albert Cruz
+Center for Research in
+Intelligent Systems
+16 Winston Chung Hall
+Bir Bhanu
+Center for Research in
+Intelligent Systems
+16 Winston Chung Hall
+Ninad Thakoor
+Center for Research in
+Intelligent Systems
+16 Winston Chung Hall
+Riverside, CA, 92521-0425,
+Riverside, CA, 92521-0425,
+Riverside, CA, 92521-0425,"
+961a5d5750f18e91e28a767b3cb234a77aac8305,Face Detection without Bells and Whistles,"Face Detection without Bells and Whistles
+Markus Mathias1, Rodrigo Benenson2, Marco Pedersoli1, and Luc Van Gool1,3
+ESAT-PSI/VISICS, iMinds, KU Leuven, Belgium
+MPI Informatics, Saarbrücken, Germany
+D-ITET/CVL, ETH Zürich, Switzerland"
+9626bcb3fc7c7df2c5a423ae8d0a046b2f69180c,A deep learning approach for action classification in American football video sequences,"UPTEC STS 17033
+Examensarbete 30 hp
+November 2017
+A deep learning approach for
+ction classification in American
+football video sequences
+Jacob Westerberg"
+9696b172d66e402a2e9d0a8d2b3f204ad8b98cc4,Region-Based Facial Expression Recognition in Still Images,"J Inf Process Syst, Vol.9, No.1, March 2013
+pISSN 1976-913X
+eISSN 2092-805X
+Region-Based Facial Expression Recognition in
+Still Images
+Gawed M. Nagi*, Rahmita Rahmat*, Fatimah Khalid* and Muhamad Taufik*"
+96f4a1dd1146064d1586ebe86293d02e8480d181,Comparative Analysis of Reranking Techniques for Web Image Search,"COMPARATIVE ANALYSIS OF RERANKING
+TECHNIQUES FOR WEB IMAGE SEARCH
+Suvarna V. Jadhav1, A.M.Bagade2
+,2Department of Information Technology, Pune Institute of Computer Technology, Pune,( India)"
+9606b1c88b891d433927b1f841dce44b8d3af066,Principal Component Analysis with Tensor Train Subspace,"Principal Component Analysis with Tensor Train
+Subspace
+Wenqi Wang, Vaneet Aggarwal, and Shuchin Aeron"
+966e36f15b05ef8436afecf57a97b73d6dcada94,Dimensionality Reduction using Relative Attributes,"Dimensionality Reduction using Relative
+Attributes
+Mohammadreza Babaee1, Stefanos Tsoukalas1, Maryam Babaee2
+Gerhard Rigoll1, and Mihai Datcu3
+Institute for Human-Machine Communication, Technische Universit¨at M¨unchen
+Computer Engineering Dept. University of Isfahan, Iran
+The Remote Sensing Technology Institute (IMF), German Aerospace Center
+Introduction
+Visual attributes are high-level semantic description of visual data that are close
+to the language of human. They have been intensively used in various appli-
+ations such as image classiﬁcation [1,2], active learning [3,4], and interactive
+search [5]. However, the usage of attributes in dimensionality reduction has not
+een considered yet. In this work, we propose to utilize relative attributes as
+semantic cues in dimensionality reduction. To this end, we employ Non-negative
+Matrix Factorization (NMF) [6] constrained by embedded relative attributes to
+ome up with a new algorithm for dimensionality reduction, namely attribute
+regularized NMF (ANMF).
+Approach
+We assume that X ∈ RD×N denotes N data points (e.g., images) represented by
+D dimensional low-level feature vectors. The NMF decomposes the non-negative"
+96b1000031c53cd4c1c154013bb722ffd87fa7da,ContextVP: Fully Context-Aware Video Prediction,"ContextVP: Fully Context-Aware Video
+Prediction
+Wonmin Byeon1,2,3,4, Qin Wang2,
+Rupesh Kumar Srivastava4, and Petros Koumoutsakos2
+NVIDIA, Santa Clara, CA, USA
+ETH Zurich, Zurich, Switzerland
+The Swiss AI Lab IDSIA, Manno, Switzerland
+NNAISENSE, Lugano, Switzerland"
+968f472477a8afbadb5d92ff1b9c7fdc89f0c009,Firefly-based Facial Expression Recognition,Firefly-based Facial Expression Recognition
+9686dcf40e6fdc4152f38bd12b929bcd4f3bbbcc,Emotion Based Music Player,"International Journal of Engineering Research and General Science Volume 3, Issue 1,  January-February, 2015
+ISSN 2091-2730
+Emotion Based Music Player
+Hafeez Kabani1, Sharik Khan2, Omar Khan3, Shabana Tadvi4
+Department of Computer Science and Engineering
+Department of Computer Science and Engineering
+Department of Computer Science and Engineering
+Asst. Professor, Department of Computer Science and Engineering
+M.H Saboo Siddik College of Engineering, University of Mumbai, India"
+3a2fc58222870d8bed62442c00341e8c0a39ec87,Probabilistic Local Variation Segmentation,"Probabilistic Local Variation
+Segmentation
+Michael Baltaxe
+Technion - Computer Science Department - M.Sc. Thesis  MSC-2014-02 - 2014"
+3a76e9fc2e89bdd10a9818f7249fbf61d216efc4,Face Sketch Matching via Coupled Deep Transform Learning,"Face Sketch Matching via Coupled Deep Transform Learning
+Shruti Nagpal1, Maneet Singh1, Richa Singh1
+, Mayank Vatsa1
+, Afzel Noore2, and Angshul Majumdar1
+IIIT-Delhi, India, 2West Virginia University
+{shrutin, maneets, rsingh, mayank,"
+3a804cbf004f6d4e0b041873290ac8e07082b61f,A Corpus-Guided Framework for Robotic Visual Perception,"Language-Action Tools for Cognitive Artificial Agents: Papers from the 2011 AAAI Workshop (WS-11-14)
+A Corpus-Guided Framework for Robotic Visual Perception
+Ching L. Teo, Yezhou Yang, Hal Daum´e III, Cornelia Ferm¨uller, Yiannis Aloimonos
+University of Maryland Institute for Advanced Computer Studies, College Park, MD 20742-3275
+{cteo, yzyang, hal, fer,"
+3a04eb72aa64760dccd73e68a3b2301822e4cdc3,Scalable Sparse Subspace Clustering,"Scalable Sparse Subspace Clustering
+Machine Intelligence Laboratory, College of Computer Science, Sichuan University,
+Xi Peng, Lei Zhang and Zhang Yi
+{leizhang,
+Chengdu, 610065, China."
+3abc833f4d689f37cc8a28f47fb42e32deaa4b17,Large Scale Retrieval and Generation of Image Descriptions,"Noname manuscript No.
+(will be inserted by the editor)
+Large Scale Retrieval and Generation of Image Descriptions
+Vicente Ordonez · Xufeng Han · Polina Kuznetsova · Girish Kulkarni ·
+Margaret Mitchell · Kota Yamaguchi · Karl Stratos · Amit Goyal ·
+Jesse Dodge · Alyssa Mensch · Hal Daum´e III · Alexander C. Berg ·
+Yejin Choi · Tamara L. Berg
+Received: date / Accepted: date"
+3a60678ad2b862fa7c27b11f04c93c010cc6c430,A Multimodal Database for Affect Recognition and Implicit Tagging,"JANUARY-MARCH 2012
+A Multimodal Database for
+Affect Recognition and Implicit Tagging
+Mohammad Soleymani, Member, IEEE, Jeroen Lichtenauer,
+Thierry Pun, Member, IEEE, and Maja Pantic, Fellow, IEEE"
+3a591a9b5c6d4c62963d7374d58c1ae79e3a4039,Driver Cell Phone Usage Detection from HOV/HOT NIR Images,"Driver Cell Phone Usage Detection From HOV/HOT NIR Images
+Yusuf Artan, Orhan Bulan, Robert P. Loce, and Peter Paul
+Xerox Research Center Webster
+800 Phillips Rd. Webster NY 14580"
+3aa9c8c65ce63eb41580ba27d47babb1100df8a3,Differentiating Duchenne from non-Duchenne smiles using active appearance models,"Annals of the
+University of North Carolina Wilmington
+Master of Science in
+Computer Science and Information Systems"
+3a0a839012575ba455f2b84c2d043a35133285f9,Corpus-Guided Sentence Generation of Natural Images,"Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pages 444–454,
+Edinburgh, Scotland, UK, July 27–31, 2011. c(cid:13)2011 Association for Computational Linguistics"
+3a9681e2e07be7b40b59c32a49a6ff4c40c962a2,"Comparing treatment means : overlapping standard errors , overlapping confidence intervals , and tests of hypothesis","Biometrics & Biostatistics International Journal
+Comparing treatment means: overlapping standard
+errors, overlapping confidence intervals, and tests of
+hypothesis"
+3a846704ef4792dd329a5c7a2cb8b330ab6b8b4e,FACE-GRAB: Face recognition with General Region Assigned to Binary operator,"in  any  current  or
+future  media,
+for  all  other  uses,
+© 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be
+obtained
+including
+reprinting/republishing  this  material  for  advertising  or  promotional  purposes,  creating
+new  collective  works,  for  resale  or  redistribution  to  servers  or  lists,  or  reuse  of  any
+opyrighted component of this work in other works.
+Pre-print of article that appeared at the IEEE Computer Society Workshop on Biometrics
+010.
+The published article can be accessed from:
+http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5544597"
+3a95eea0543cf05670e9ae28092a114e3dc3ab5c,Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering,"Constructing the L2-Graph for Robust Subspace
+Learning and Subspace Clustering
+Xi Peng, Zhiding Yu, Huajin Tang, Member, IEEE, and Zhang Yi, Senior Member, IEEE"
+3a4f522fa9d2c37aeaed232b39fcbe1b64495134,Face Recognition and Retrieval Using Cross-Age Reference Coding With Cross-Age Celebrity Dataset,"ISSN (Online) 2321 – 2004
+ISSN (Print) 2321 – 5526
+INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN ELECTRICAL, ELECTRONICS, INSTRUMENTATION AND CONTROL ENGINEERING
+Vol. 4, Issue 5, May 2016
+IJIREEICE
+Face Recognition and Retrieval Using Cross
+Age Reference Coding
+Sricharan H S1, Srinidhi K S1, Rajath D N1, Tejas J N1, Chandrakala B M2
+BE, DSCE, Bangalore1
+Assistant Professor, DSCE, Bangalore2"
+540b39ba1b8ef06293ed793f130e0483e777e278,Biologically Inspired Emotional Expressions for Artificial Agents,"ORIGINAL RESEARCH
+published: 13 July 2018
+doi: 10.3389/fpsyg.2018.01191
+Biologically Inspired Emotional
+Expressions for Artiﬁcial Agents
+Beáta Korcsok 1*, Veronika Konok 2, György Persa 3, Tamás Faragó 2, Mihoko Niitsuma 4,
+Ádám Miklósi 2,5, Péter Korondi 1, Péter Baranyi 6 and Márta Gácsi 2,5
+Department of Mechatronics, Optics and Engineering Informatics, Budapest University of Technology and Economics,
+Budapest, Hungary, 2 Department of Ethology, Eötvös Loránd University, Budapest, Hungary, 3 Institute for Computer Science
+nd Control, Hungarian Academy of Sciences, Budapest, Hungary, 4 Department of Precision Mechanics, Chuo University,
+Tokyo, Japan, 5 MTA-ELTE Comparative Ethology Research Group, Budapest, Hungary, 6 Department of Telecommunications
+nd Media Informatics, Budapest University of Technology and Economics, Budapest, Hungary
+A special area of human-machine interaction,
+the expression of emotions gains
+importance with the continuous development of artiﬁcial agents such as social robots or"
+543f21d81bbea89f901dfcc01f4e332a9af6682d,Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks,"Published as a conference paper at ICLR 2016
+UNSUPERVISED AND SEMI-SUPERVISED LEARNING
+WITH CATEGORICAL GENERATIVE ADVERSARIAL
+NETWORKS
+Jost Tobias Springenberg
+University of Freiburg
+79110 Freiburg, Germany"
+54969bcd728b0f2d3285866c86ef0b4797c2a74d,Learning for Video Compression,"IEEE TRANSACTION SUBMISSION
+Learning for Video Compression
+Zhibo Chen, Senior Member, IEEE, Tianyu He, Xin Jin, Feng Wu, Fellow, IEEE"
+5456166e3bfe78a353df988897ec0bd66cee937f,Improved Boosting Performance by Exclusion of Ambiguous Positive Examples,"Improved Boosting Performance by Exclusion
+of Ambiguous Positive Examples
+Miroslav Kobetski, Josephine Sullivan
+Computer Vision and Active Perception, KTH, Stockholm 10800, Sweden
+{kobetski,
+Keywords:
+Boosting, Image Classiﬁcation, Algorithm Evaluation, Dataset Pruning, VOC2007."
+54aacc196ffe49b3450059fccdf7cd3bb6f6f3c3,A joint learning framework for attribute models and object descriptions,"A Joint Learning Framework for Attribute Models and Object Descriptions
+Dhruv Mahajan
+Yahoo! Labs, Bangalore, India
+Sundararajan Sellamanickam
+Vinod Nair"
+541bccf19086755f8b5f57fd15177dc49e77d675,A few days of a robot's life in the human's world: toward incremental individual recognition,"Computer Science and ArtificialIntelligence LaboratoryTechnical Reportmassachusetts institute of technology, cambridge, ma 02139 usa — www.csail.mit.eduMIT-CSAIL-TR-2007-022April 3, 2007A Few Days of A Robot’s Life in the Human’s World: Toward Incremental Individual RecognitionLijin Aryananda"
+54756f824befa3f0c2af404db0122f5b5bbf16e0,Computer Vision — Visual Recognition,"Research Statement
+Computer Vision — Visual Recognition
+Alexander C. Berg
+Computational visual recognition concerns identifying what is in an image, video, or other visual data, enabling
+pplications such as measuring location, pose, size, activity, and identity as well as indexing for search by content.
+Recent progress in making economical sensors and improvements in network, storage, and computational power
+make visual recognition practical and relevant in almost all experimental sciences and commercial applications
+such as image search. My work in visual recognition brings together machine learning, insights from psychology
+nd physiology, computer graphics, algorithms, and a great deal of computation.
+While I am best known for my work on general object category detection – creating techniques and building
+systems for some of the best performing approaches to categorizing and localizing objects in images, recognizing
+ction in video, and searching large collections of video and images – my research extends widely across visual
+recognition including:
+• Creating low-level image descriptors – procedures for converting pixel values to features that can be used
+to model appearance for recognition. These include widely used descriptors for category recognition in
+images [4, 2], object detection in images and video [11, 10, 2], and optical flow based descriptors for action
+recognition in video [8].
+• Developing models for recognition – ranging from what is becoming seminal work in recognizing human
+ctions in video [8], to formulating object localization as approximate subgraph isomorphism [2], to models
+for parsing architectural images [3], to a novel approach for face recognition based on high level describable"
+549c719c4429812dff4d02753d2db11dd490b2ae,YouTube-BoundingBoxes: A Large High-Precision Human-Annotated Data Set for Object Detection in Video,"YouTube-BoundingBoxes: A Large High-Precision
+Human-Annotated Data Set for Object Detection in Video
+Esteban Real
+Google Brain
+Jonathon Shlens
+Google Brain
+Stefano Mazzocchi
+Google Research
+Xin Pan
+Google Brain
+Vincent Vanhoucke
+Google Brain"
+988d1295ec32ce41d06e7cf928f14a3ee079a11e,Semantic Deep Learning,"Semantic Deep Learning
+Hao Wang
+September 29, 2015"
+98c548a4be0d3b62971e75259d7514feab14f884,Deep generative-contrastive networks for facial expression recognition,"Deep generative-contrastive networks for facial expression recognition
+Youngsung Kim†, ByungIn Yoo‡,†, Youngjun Kwak†, Changkyu Choi†, and Junmo Kim‡
+Samsung Advanced Institute of Technology (SAIT), ‡KAIST
+hangkyu"
+981449cdd5b820268c0876477419cba50d5d1316,Learning Deep Features for One-Class Classification,"Learning Deep Features for One-Class
+Classiﬁcation
+Pramuditha Perera, Student Member, IEEE, and Vishal M. Patel, Senior Member , IEEE"
+9854145f2f64d52aac23c0301f4bb6657e32e562,An Improved Face Verification Approach Based on Speedup Robust Features and Pairwise Matching,"An Improved Face Veriﬁcation Approach based on
+Speedup Robust Features and Pairwise Matching
+Eduardo Santiago Moura, Herman Martins Gomes and Jo˜ao Marques de Carvalho
+Center for Electrical Engineering and Informatics (CEEI)
+Federal University of Campina Grande (UFCG)
+Campina Grande, Para´ıba, Brazil
+Email:"
+98127346920bdce9773aba6a2ffc8590b9558a4a,Efficient human action recognition using histograms of motion gradients and VLAD with descriptor shape information,"Noname manuscript No.
+(will be inserted by the editor)
+Ef‌f‌icient Human Action Recognition using
+Histograms of Motion Gradients and
+VLAD with Descriptor Shape Information
+Ionut C. Duta · Jasper R.R. Uijlings ·
+Bogdan Ionescu · Kiyoharu Aizawa ·
+Alexander G. Hauptmann · Nicu Sebe
+Received: date / Accepted: date"
+98519f3f615e7900578bc064a8fb4e5f429f3689,Dictionary-Based Domain Adaptation Methods for the Re-identification of Faces,"Dictionary-based Domain Adaptation Methods
+for the Re-identiﬁcation of Faces
+Qiang Qiu, Jie Ni, and Rama Chellappa"
+9825aa96f204c335ec23c2b872855ce0c98f9046,Face and Facial Expression Recognition in 3-d Using Masked Projection under Occlusion,"International Journal of Ethics in Engineering & Management Education
+Website: www.ijeee.in (ISSN: 2348-4748, Volume 1, Issue 5, May2014)
+FACE AND FACIAL EXPRESSION
+RECOGNITION IN 3-D USING MASKED
+PROJECTION UNDER OCCLUSION
+Jyoti patil *
+M.Tech (CSE)
+GNDEC Bidar-585401
+BIDAR, INDIA
+Gouri Patil
+M.Tech (CSE)
+GNDEC Bidar- 585401
+BIDAR, INDIA
+Snehalata Patil
+M.Tech (CSE)
+VKIT, Bangalore- 560040
+BANGALORE, INDIA"
+53e081f5af505374c3b8491e9c4470fe77fe7934,Unconstrained realtime facial performance capture,"Unconstrained Realtime Facial Performance Capture
+Pei-Lun Hsieh⇤
+⇤ University of Southern California
+Chongyang Ma⇤
+Jihun Yu†
+Hao Li⇤
+Industrial Light & Magic
+Figure 1: Calibration-free realtime facial performance capture on highly occluded subjects using an RGB-D sensor."
+53c36186bf0ffbe2f39165a1824c965c6394fe0d,I Know How You Feel: Emotion Recognition with Facial Landmarks,"I Know How You Feel: Emotion Recognition with Facial Landmarks
+Tooploox 2Polish-Japanese Academy of Information Technology 3Warsaw University of Technology
+Ivona Tautkute1,2, Tomasz Trzcinski1,3 and Adam Bielski1"
+5366573e96a1dadfcd4fd592f83017e378a0e185,"Server, server in the cloud. Who is the fairest in the crowd?","Böhlen, Chandola and Salunkhe
+Server, server in the cloud.
+Who is the fairest in the crowd?"
+53a41c711b40e7fe3dc2b12e0790933d9c99a6e0,Recurrent Memory Addressing for Describing Videos,"Recurrent Memory Addressing for describing videos
+Arnav Kumar Jain∗ Abhinav Agarwalla∗
+Kumar Krishna Agrawal∗
+Pabitra Mitra
+{arnavkj95, abhinavagarawalla, kumarkrishna,
+Indian Institute of Technology Kharagpur"
+533bfb82c54f261e6a2b7ed7d31a2fd679c56d18,Unconstrained Face Recognition: Identifying a Person of Interest From a Media Collection,"Technical Report MSU-CSE-14-1
+Unconstrained Face Recognition: Identifying a
+Person of Interest from a Media Collection
+Lacey Best-Rowden, Hu Han, Member, IEEE, Charles Otto, Brendan Klare, Member, IEEE, and
+Anil K. Jain, Fellow, IEEE"
+3fbd68d1268922ee50c92b28bd23ca6669ff87e5,A shape- and texture-based enhanced Fisher classifier for face recognition,"IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 10, NO. 4, APRIL 2001
+A Shape- and Texture-Based Enhanced Fisher
+Classifier for Face Recognition
+Chengjun Liu, Member, IEEE, and Harry Wechsler, Fellow, IEEE"
+3f22a4383c55ceaafe7d3cfed1b9ef910559d639,Robust Kronecker Component Analysis,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
+Robust Kronecker Component Analysis
+Mehdi Bahri, Student Member, IEEE, Yannis Panagakis, and Stefanos Zafeiriou, Member, IEEE"
+3fdcc1e2ebcf236e8bb4a6ce7baf2db817f30001,A Top-Down Approach for a Synthetic Autobiographical Memory System,"A top-down approach for a synthetic
+utobiographical memory system
+Andreas Damianou1,2, Carl Henrik Ek3, Luke Boorman1, Neil D. Lawrence2,
+nd Tony J. Prescott1
+Shef‌f‌ield Centre for Robotics (SCentRo), Univ. of Shef‌f‌ield, Shef‌f‌ield, S10 2TN, UK
+Dept. of Computer Science, Univ. of Shef‌f‌ield, Shef‌f‌ield, S1 4DP, UK
+CVAP Lab, KTH, Stockholm, Sweden"
+3f848d6424f3d666a1b6dd405a48a35a797dd147,Is 2D Information Enough For Viewpoint Estimation?,"GHODRATI et al.: IS 2D INFORMATION ENOUGH FOR VIEWPOINT ESTIMATION?
+Is 2D Information Enough For Viewpoint
+Estimation?
+Amir Ghodrati
+Marco Pedersoli
+Tinne Tuytelaars
+KU Leuven, ESAT - PSI, iMinds
+Leuven, Belgium"
+3fa738ab3c79eacdbfafa4c9950ef74f115a3d84,DaMN - Discriminative and Mutually Nearest: Exploiting Pairwise Category Proximity for Video Action Recognition,"DaMN – Discriminative and Mutually Nearest:
+Exploiting Pairwise Category Proximity
+for Video Action Recognition
+Rui Hou1, Amir Roshan Zamir1, Rahul Sukthankar2, and Mubarak Shah1
+Center for Research in Computer Vision at UCF, Orlando, USA
+Google Research, Mountain View, USA
+http://crcv.ucf.edu/projects/DaMN/"
+3fb98e76ffd8ba79e1c22eda4d640da0c037e98a,Convolutional Neural Networks for Crop Yield Prediction using Satellite Images,"Convolutional Neural Networks for Crop Yield Prediction using Satellite Images
+H. Russello"
+3f14b504c2b37a0e8119fbda0eff52efb2eb2461,Joint Facial Action Unit Detection and Feature Fusion: A Multi-Conditional Learning Approach,"Joint Facial Action Unit Detection and Feature
+Fusion: A Multi-Conditional Learning Approach
+Stefanos Eleftheriadis, Ognjen Rudovic, Member, IEEE, and Maja Pantic, Fellow, IEEE"
+3fac7c60136a67b320fc1c132fde45205cd2ac66,Remarks on Computational Facial Expression Recognition from HOG Features Using Quaternion Multi-layer Neural Network,"Remarks on Computational Facial Expression
+Recognition from HOG Features Using
+Quaternion Multi-layer Neural Network
+Kazuhiko Takahashi1, Sae Takahashi1, Yunduan Cui2,
+nd Masafumi Hashimoto3
+Information Systems Design, Doshisha University, Kyoto, Japan
+Graduate School of Doshisha University, Kyoto, Japan
+Intelligent Information Engineering and Science, Doshisha University, Kyoto, Japan"
+3f9a7d690db82cf5c3940fbb06b827ced59ec01e,VIP: Finding important people in images,"VIP: Finding Important People in Images
+Clint Solomon Mathialagan
+Virginia Tech
+Andrew C. Gallagher
+Google Inc.
+Dhruv Batra
+Virginia Tech
+Project: https://computing.ece.vt.edu/~mclint/vip/
+Demo: http://cloudcv.org/vip/"
+3fd90098551bf88c7509521adf1c0ba9b5dfeb57,Attribute-Based Classification for Zero-Shot Visual Object Categorization,"Page 1 of 21
+*****For Peer Review Only*****
+Attribute-Based Classiﬁcation for Zero-Shot
+Visual Object Categorization
+Christoph H. Lampert, Hannes Nickisch and Stefan Harmeling"
+3f7723ab51417b85aa909e739fc4c43c64bf3e84,Improved Performance in Facial Expression Recognition Using 32 Geometric Features,"Improved Performance in Facial Expression
+Recognition Using 32 Geometric Features
+Giuseppe Palestra1(B), Adriana Pettinicchio2, Marco Del Coco2,
+Pierluigi Carcagn`ı2, Marco Leo2, and Cosimo Distante2
+Department of Computer Science, University of Bari, Bari, Italy
+National Institute of Optics, National Research Council, Arnesano, LE, Italy"
+3f63f9aaec8ba1fa801d131e3680900680f14139,Facial Expression recognition using Local Binary Patterns and Kullback Leibler divergence,"Facial Expression Recognition using Local Binary
+Patterns and Kullback Leibler Divergence
+AnushaVupputuri, SukadevMeher
+divergence."
+3f0e0739677eb53a9d16feafc2d9a881b9677b63,Efficient Two-Stream Motion and Appearance 3D CNNs for Video Classification,"Efﬁcient Two-Stream Motion and Appearance 3D CNNs for
+Video Classiﬁcation
+Ali Diba
+ESAT-KU Leuven
+Ali Pazandeh
+Sharif UTech
+Luc Van Gool
+ESAT-KU Leuven, ETH Zurich"
+30b15cdb72760f20f80e04157b57be9029d8a1ab,Face Aging with Identity-Preserved Conditional Generative Adversarial Networks,"Face Aging with Identity-Preserved
+Conditional Generative Adversarial Networks
+Zongwei Wang
+Shanghaitech University
+Xu Tang
+Baidu
+Weixin Luo, Shenghua Gao∗
+Shanghaitech University
+{luowx,"
+30870ef75aa57e41f54310283c0057451c8c822b,Overcoming catastrophic forgetting with hard attention to the task,"Overcoming Catastrophic Forgetting with Hard Attention to the Task
+Joan Serr`a 1 D´ıdac Sur´ıs 1 2 Marius Miron 1 3 Alexandros Karatzoglou 1"
+305346d01298edeb5c6dc8b55679e8f60ba97efb,Fine-Grained Face Annotation Using Deep Multi-Task CNN,"Article
+Fine-Grained Face Annotation Using Deep
+Multi-Task CNN
+Luigi Celona *
+, Simone Bianco
+nd Raimondo Schettini
+Department of Informatics, Systems and Communication, University of Milano-Bicocca,
+viale Sarca, 336 Milano, Italy; (S.B.); (R.S.)
+* Correspondence:
+Received: 3 July 2018; Accepted: 13 August 2018; Published: 14 August 2018"
+309e17e6223e13b1f76b5b0eaa123b96ef22f51b,Face recognition based on a 3D morphable model,"Face Recognition based on a 3D Morphable Model
+Volker Blanz
+University of Siegen
+H¤olderlinstr. 3
+57068 Siegen, Germany"
+3046baea53360a8c5653f09f0a31581da384202e,Deformable Face Alignment via Local Measurements and Global Constraints,"Deformable Face Alignment via Local
+Measurements and Global Constraints
+Jason M. Saragih"
+3028690d00bd95f20842d4aec84dc96de1db6e59,Leveraging Union of Subspace Structure to Improve Constrained Clustering,"Leveraging Union of Subspace Structure to Improve Constrained Clustering
+John Lipor 1 Laura Balzano 1"
+30c96cc041bafa4f480b7b1eb5c45999701fe066,Discrete Cosine Transform Locality-Sensitive Hashes for Face Retrieval,"Discrete Cosine Transform Locality-Sensitive
+Hashes for Face Retrieval
+Mehran Kafai, Member, IEEE, Kave Eshghi, and Bir Bhanu, Fellow, IEEE"
+306957285fea4ce11a14641c3497d01b46095989,Face Recognition Under Varying Lighting Based on Derivates of Log Image,"FACE RECOGNITION UNDER VARYING LIGHTING BASED ON
+DERIVATES OF LOG IMAGE
+Laiyun Qing1,2, Shiguang Shan2,  Wen Gao1,2
+ICT-ISVISION Joint R&D Laboratory for Face Recognition, CAS, Beijing 100080, China
+Graduate School, CAS, Beijing, 100039, China"
+307a810d1bf6f747b1bd697a8a642afbd649613d,An affordable contactless security system access for restricted area,"An affordable contactless security system access
+for restricted area
+Pierre Bonazza1, Johel Mitéran1, Barthélémy Heyrman1, Dominique Ginhac1,
+Vincent Thivent2, Julien Dubois1
+Laboratory Le2i
+University Bourgogne Franche-Comté, France
+Odalid compagny, France
+Contact
+Keywords – Smart Camera, Real-time Image Processing, Biometrics, Face Detection, Face Verifica-
+tion, EigenFaces, Support Vector Machine,
+We  present  in  this  paper  a  security  system  based  on
+identity verification process and a low-cost smart cam-
+era, intended to avoid unauthorized access to restricted
+rea.  The  Le2i  laboratory  has  a  longstanding  experi-
+ence in smart cameras implementation and design [1],
+for  example in the  case of  real-time classical  face de-
+tection [2] or human fall detection [3].
+The principle of the system, fully thought and designed
+in  our  laboratory,  is  as  follows:  the  allowed  user  pre-
+sents a RFID card to the reader based on Odalid system"
+302c9c105d49c1348b8f1d8cc47bead70e2acf08,Unconstrained Face Recognition Using A Set-to-Set Distance Measure,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSVT.2017.2710120, IEEE
+Transactions on Circuits and Systems for Video Technology
+IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
+Unconstrained Face Recognition Using A Set-to-Set
+Distance Measure
+Jiaojiao Zhao, Jungong Han, and Ling Shao, Senior Member IEEE"
+301b0da87027d6472b98361729faecf6e1d5e5f6,Head Pose Estimation in Face Recognition Across Pose Scenarios,"HEAD POSE ESTIMATION IN FACE RECOGNITION ACROSS
+POSE SCENARIOS
+M. Saquib Sarfraz and Olaf Hellwich
+Computer vision and Remote Sensing, Berlin university of Technology
+Sekr. FR-3-1, Franklinstr. 28/29, D-10587, Berlin, Germany.
+Keywords:
+Pose estimation, facial pose, face recognition, local energy models, shape description, local features, head
+pose classification."
+30b103d59f8460d80bb9eac0aa09aaa56c98494f,Enhancing Human Action Recognition with Region Proposals,"Enhancing Human Action Recognition with Region Proposals
+Fahimeh Rezazadegan, Sareh Shirazi, Niko Sünderhauf, Michael Milford, Ben Upcroft
+Australian Centre for Robotic Vision(ACRV), School of Electrical Engineering and Computer Science
+Queensland University of Technology(QUT)"
+5e6f546a50ed97658be9310d5e0a67891fe8a102,Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?,"Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?
+Kensho Hara, Hirokatsu Kataoka, Yutaka Satoh
+National Institute of Advanced Industrial Science and Technology (AIST)
+Tsukuba, Ibaraki, Japan
+{kensho.hara, hirokatsu.kataoka,"
+5e0eb34aeb2b58000726540336771053ecd335fc,Low-Quality Video Face Recognition with Deep Networks and Polygonal Chain Distance,"Low-Quality Video Face Recognition with Deep
+Networks and Polygonal Chain Distance
+Christian Herrmann∗†, Dieter Willersinn†, J¨urgen Beyerer†∗
+Vision and Fusion Lab, Karlsruhe Institute of Technology KIT, Karlsruhe, Germany
+Fraunhofer IOSB, Karlsruhe, Germany"
+5e28673a930131b1ee50d11f69573c17db8fff3e,Descriptor Based Methods in the Wild,"Author manuscript, published in ""Workshop on Faces in 'Real-Life' Images: Detection, Alignment, and Recognition, Marseille : France
+(2008)"""
+5ea9063b44b56d9c1942b8484572790dff82731e,Multiclass Support Vector Machines and Metric Multidimensional Scaling for Facial Expression Recognition,"MULTICLASS SUPPORT VECTOR MACHINES AND METRIC MULTIDIMENSIONAL
+SCALING FOR FACIAL EXPRESSION RECOGNITION
+Irene Kotsiay, Stefanos Zafeiriouy, Nikolaos Nikolaidisy and Ioannis Pitasy
+yAristotle University of Thessaloniki, Department of Informatics
+Thessaloniki, Greece
+email: fekotsia, dralbert, nikolaid,"
+5e6ba16cddd1797853d8898de52c1f1f44a73279,Face Identification with Second-Order Pooling,"Face Identiﬁcation with Second-Order Pooling
+Fumin Shen, Chunhua Shen and Heng Tao Shen"
+5ec94adc9e0f282597f943ea9f4502a2a34ecfc2,Leveraging the Power of Gabor Phase for Face Identification: A Block Matching Approach,"Leveraging the Power of Gabor Phase for Face
+Identiﬁcation: A Block Matching Approach
+Yang Zhong, Haibo Li
+KTH, Royal Institute of Technology"
+5b59e6b980d2447b2f3042bd811906694e4b0843,Two-stage cascade model for unconstrained face detection,"Two-stage Cascade Model for Unconstrained
+Face Detection
+Darijan Marčetić, Tomislav Hrkać, Slobodan Ribarić
+University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia
+{darijan.marcetic, tomislav.hrkac,"
+5bfc32d9457f43d2488583167af4f3175fdcdc03,Local Gray Code Pattern (LGCP): A Robust Feature Descriptor for Facial Expression Recognition,"International Journal of Science and Research (IJSR), India Online ISSN: 2319-7064
+Local Gray Code Pattern (LGCP): A Robust
+Feature Descriptor for Facial Expression
+Recognition
+Mohammad Shahidul Islam
+Atish Dipankar University of Science & Technology, School, Department of Computer Science and Engineering, Dhaka, Bangladesh."
+5ba7882700718e996d576b58528f1838e5559225,Predicting Personalized Image Emotion Perceptions in Social Networks,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TAFFC.2016.2628787, IEEE
+Transactions on Affective Computing
+IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, VOL. X, NO. X, OCTOBER 2016
+Predicting Personalized Image Emotion
+Perceptions in Social Networks
+Sicheng Zhao, Hongxun Yao, Yue Gao, Senior Member, IEEE, Guiguang Ding and Tat-Seng Chua"
+5b6f0a508c1f4097dd8dced751df46230450b01a,Finding lost children,"Finding Lost Children
+Ashley Michelle Eden
+Electrical Engineering and Computer Sciences
+University of California at Berkeley
+Technical Report No. UCB/EECS-2010-174
+http://www.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-174.html
+December 20, 2010"
+5bb684dfe64171b77df06ba68997fd1e8daffbe1,One-Sided Unsupervised Domain Mapping,
+5bae9822d703c585a61575dced83fa2f4dea1c6d,MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking,"MOTChallenge 2015:
+Towards a Benchmark for Multi-Target Tracking
+Laura Leal-Taix´e∗, Anton Milan∗, Ian Reid, Stefan Roth, and Konrad Schindler"
+5babbad3daac5c26503088782fd5b62067b94fa5,Are You Sure You Want To Do That? Classification with Verification,"Are You Sure You Want To Do That?
+Classiﬁcation with Veriﬁcation
+Harris Chan∗
+Atef Chaudhury∗
+Kevin Shen∗"
+5bb87c7462c6c1ec5d60bde169c3a785ba5ea48f,Targeting Ultimate Accuracy: Face Recognition via Deep Embedding,"Targeting Ultimate Accuracy: Face Recognition via Deep Embedding
+Jingtuo Liu     Yafeng Deng     Tao Bai     Zhengping Wei     Chang Huang
+Baidu Research – Institute of Deep Learning"
+5b9d9f5a59c48bc8dd409a1bd5abf1d642463d65,An evolving spatio-temporal approach for gender and age group classification with Spiking Neural Networks,"Evolving Systems. manuscript No.
+(will be inserted by the editor)
+An evolving spatio-temporal approach for gender and age
+group classiﬁcation with Spiking Neural Networks
+Fahad Bashir Alvi, Russel Pears, Nikola Kasabov
+Received: date / Accepted: date"
+5bf70c1afdf4c16fd88687b4cf15580fd2f26102,Residual Codean Autoencoder for Facial Attribute Analysis,"Accepted in Pattern Recognition Letters
+Pattern Recognition Letters
+journal homepage: www.elsevier.com
+Residual Codean Autoencoder for Facial Attribute Analysis
+Akshay Sethi, Maneet Singh, Richa Singh, Mayank Vatsa∗∗
+IIIT-Delhi, New Delhi, India
+Article history:
+Received 29 March 2017"
+5b721f86f4a394f05350641e639a9d6cb2046c45,Detection under Privileged Information,"A short version of this paper is accepted to ACM Asia Conference on Computer and Communications Security (ASIACCS) 2018
+Detection under Privileged Information (Full Paper)∗
+Z. Berkay Celik
+Pennsylvania State University
+Patrick McDaniel
+Pennsylvania State University
+Rauf Izmailov
+Vencore Labs
+Nicolas Papernot,
+Ryan Sheatsley, Raquel Alvarez
+Pennsylvania State University
+Ananthram Swami
+Army Research Laboratory"
+5be3cc1650c918da1c38690812f74573e66b1d32,Relative Parts: Distinctive Parts for Learning Relative Attributes,"Relative Parts: Distinctive Parts for Learning Relative Attributes
+Ramachandruni N. Sandeep
+Yashaswi Verma
+C. V. Jawahar
+Center for Visual Information Technology, IIIT Hyderabad, India - 500032"
+5b6bed112e722c0629bcce778770d1b28e42fc96,Can Your Eyes Tell Me How You Think? A Gaze Directed Estimation of the Mental Activity,"FLOREA ET AL.:CANYOUREYESTELLMEHOWYOUTHINK?
+Can Your Eyes Tell Me How You Think? A
+Gaze Directed Estimation of the Mental
+Activity
+Laura Florea
+http://alpha.imag.pub.ro/common/staff/lflorea
+Corneliu Florea
+http://alpha.imag.pub.ro/common/staff/cflorea
+Ruxandra Vrânceanu
+Constantin Vertan
+http://alpha.imag.pub.ro/common/staff/vertan
+Image Processing and Analysis
+Laboratory, LAPI
+University “Politehnica” of Bucharest
+Bucharest, Romania"
+37c8514df89337f34421dc27b86d0eb45b660a5e,Facial Landmark Tracking by Tree-Based Deformable Part Model Based Detector,"Facial Landmark Tracking by Tree-based Deformable Part Model
+Based Detector
+Michal Uˇriˇc´aˇr, Vojtˇech Franc, and V´aclav Hlav´aˇc
+Center for Machine Perception, Department of Cybernetics
+Faculty of Electrical Engineering, Czech Technical University in Prague
+66 27 Prague 6, Technick´a 2, Czech Republic
+{uricamic, xfrancv,"
+374c7a2898180723f3f3980cbcb31c8e8eb5d7af,Facial Expression Recognition in Videos using a Novel Multi-Class Support Vector Machines Variant,"FACIAL EXPRESSION RECOGNITION IN VIDEOS USING A NOVEL MULTI-CLASS
+SUPPORT VECTOR MACHINES VARIANT
+Irene Kotsiay, Nikolaos Nikolaidisy and Ioannis Pitasy
+yAristotle University of Thessaloniki
+Department of Informatics
+Box 451, 54124 Thessaloniki, Greece"
+372fb32569ced35eaf3740a29890bec2be1869fa,Mu rhythm suppression is associated with the classification of emotion in faces.,"Running head: MU RHYTHM MODULATION BY CLASSIFICATION OF EMOTION  1
+Mu rhythm suppression is associated with the classification of emotion in faces
+Matthew R. Moore1, Elizabeth A. Franz1
+Department of Psychology, University of Otago, Dunedin, New Zealand
+Corresponding authors:
+Matthew Moore & Liz Franz
+Phone:  +64 (3) 479 5269; Fax:  +64 (3) 479 8335
+Department of Psychology
+University of Otago
+PO Box 56
+Dunedin, New Zealand"
+37f2e03c7cbec9ffc35eac51578e7e8fdfee3d4e,Co-operative Pedestrians Group Tracking in Crowded Scenes Using an MST Approach,"WACV 2015 Submission #394. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
+Co-operative Pedestrians Group Tracking in Crowded Scenes using an MST
+Approach
+Anonymous WACV submission
+Paper ID 394"
+3795974e24296185d9b64454cde6f796ca235387,Finding your Lookalike: Measuring Face Similarity Rather than Face Identity,"Finding your Lookalike:
+Measuring Face Similarity Rather than Face Identity
+Amir Sadovnik, Wassim Gharbi, Thanh Vu
+Lafayette College
+Easton, PA
+Andrew Gallagher
+Google Research
+Mountain View, CA"
+37278ffce3a0fe2c2bbf6232e805dd3f5267eba3,Can we still avoid automatic face detection?,"Can we still avoid automatic face detection?
+Michael J. Wilber1,2
+Vitaly Shmatikov1,2
+Serge Belongie1,2
+Department of Computer Science, Cornell University 2 Cornell Tech"
+377a1be5113f38297716c4bb951ebef7a93f949a,Facial emotion recognition with anisotropic inhibited Gabor energy histograms,"Dear Faculty, IGERT Fellows, IGERT Associates and Students,
+You are cordially invited to attend a Seminar presented by Albert Cruz. Please
+plan to attend.
+Albert Cruz
+IGERT Fellow
+Electrical Engineering
+Date: Friday, October 11, 2013
+Location: Bourns A265
+Time: 11:00am
+Facial  emotion  recognition  with  anisotropic
+inhibited gabor energy histograms"
+370e0d9b89518a6b317a9f54f18d5398895a7046,Cross-pollination of normalisation techniques from speaker to face authentication using Gaussian mixture models,"IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. X, NO. X, XXXXXXX 20XX
+Cross-pollination of normalisation techniques
+from speaker to face authentication
+using Gaussian mixture models
+Roy Wallace, Member, IEEE, Mitchell McLaren, Member, IEEE, Christopher McCool, Member, IEEE,
+nd S´ebastien Marcel, Member, IEEE"
+37eb666b7eb225ffdafc6f318639bea7f0ba9a24,"Age, Gender and Race Estimation from Unconstrained Face Images","MSU Technical Report (2014): MSU-CSE-14-5
+Age, Gender and Race Estimation from
+Unconstrained Face Images
+Hu Han, Member, IEEE and Anil K. Jain, Fellow, IEEE"
+375435fb0da220a65ac9e82275a880e1b9f0a557,From Pixels to Response Maps: Discriminative Image Filtering for Face Alignment in the Wild,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
+From Pixels to Response Maps: Discriminative Image
+Filtering for Face Alignment in the Wild
+Akshay Asthana, Stefanos Zafeiriou, Georgios Tzimiropou-
+los, Shiyang Cheng and Maja Pantic"
+37b6d6577541ed991435eaf899a2f82fdd72c790,Vision-based Human Gender Recognition: A Survey,"Vision-based Human Gender Recognition: A Survey
+Choon Boon Ng, Yong Haur Tay, Bok Min Goi
+Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia."
+370b5757a5379b15e30d619e4d3fb9e8e13f3256,Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments,"Labeled Faces in the Wild: A Database for Studying
+Face Recognition in Unconstrained Environments
+Gary B. Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller"
+08d2f655361335bdd6c1c901642981e650dff5ec,Automatic Cast Listing in Feature-Length Films with Anisotropic Manifold Space,"This is the published version:
+Arandjelovic,	Ognjen	and	Cipolla,	R.	2006,	Automatic	cast	listing	in	feature‐length	films	with
+Anisotropic	Manifold	Space,	in	CVPR	2006	:	Proceedings	of	the	Computer	Vision	and	Pattern
+Recognition	Conference	2006,	IEEE,	Piscataway,	New	Jersey,	pp.	1513‐1520.
+http://hdl.handle.net/10536/DRO/DU:30058435
+Reproduced	with	the	kind	permission	of	the	copyright	owner.
+Copyright	:	2006,	IEEE
+Available from Deakin Research Online:"
+08fbe3187f31b828a38811cc8dc7ca17933b91e9,Statistical Computations on Grassmann and Stiefel Manifolds for Image and Video-Based Recognition,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES
+http://www.merl.com
+Statistical Computations on Grassmann and
+Stiefel Manifolds for Image and Video-Based
+Recognition
+Turaga, P.; Veeraraghavan, A.; Srivastava, A.; Chellappa, R.
+TR2011-084 April 2011"
+08ae100805d7406bf56226e9c3c218d3f9774d19,Predicting the Sixteen Personality Factors (16PF) of an individual by analyzing facial features,"Gavrilescu and Vizireanu EURASIP Journal on Image and Video Processing  (2017) 2017:59
+DOI 10.1186/s13640-017-0211-4
+EURASIP Journal on Image
+nd Video Processing
+R ES EAR CH
+Predicting the Sixteen Personality Factors
+(16PF) of an individual by analyzing facial
+features
+Mihai Gavrilescu* and Nicolae Vizireanu
+Open Access"
+08c18b2f57c8e6a3bfe462e599a6e1ce03005876,A Least-Squares Framework for Component Analysis,"A Least-Squares Framework
+for Component Analysis
+Fernando De la Torre Member, IEEE,"
+08ff81f3f00f8f68b8abd910248b25a126a4dfa4,Symmetric Subspace Learning for Image Analysis,"Papachristou, K., Tefas, A., & Pitas, I. (2014). Symmetric Subspace Learning
+5697. DOI: 10.1109/TIP.2014.2367321
+Peer reviewed version
+Link to published version (if available):
+0.1109/TIP.2014.2367321
+Link to publication record in Explore Bristol Research
+PDF-document
+This is the author accepted manuscript (AAM). The final published version (version of record) is available online
+via Institute of Electrical and Electronic Engineers at http://dx.doi.org/10.1109/TIP.2014.2367321. Please refer to
+ny applicable terms of use of the publisher.
+University of Bristol - Explore Bristol Research
+General rights
+This document is made available in accordance with publisher policies. Please cite only the published
+version using the reference above. Full terms of use are available:
+http://www.bristol.ac.uk/pure/about/ebr-terms"
+0861f86fb65aa915fbfbe918b28aabf31ffba364,An Efficient Facial Annotation with Machine Learning Approach,"International Journal of Computer Trends and Technology (IJCTT) – volume 22 Number 3–April 2015
+An Efficient Facial Annotation with Machine Learning Approach
+A.Anusha,2R.Srinivas
+Final M.Tech Student, 2Associate Professor
+,2Dept of CSE ,Aditya Institute of Technology And Management, Tekkali, Srikakulam , Andhra Pradesh"
+080c204edff49bf85b335d3d416c5e734a861151,CLAD: A Complex and Long Activities Dataset with Rich Crowdsourced Annotations,"CLAD: A Complex and Long Activities
+Dataset with Rich Crowdsourced
+Annotations
+Jawad Tayyub1, Majd Hawasly2∗, David C. Hogg1 and Anthony G. Cohn1
+Journal Title
+XX(X):1–6
+(cid:13)The Author(s) 2016
+Reprints and permission:
+sagepub.co.uk/journalsPermissions.nav
+DOI: 10.1177/ToBeAssigned
+www.sagepub.com/"
+08f4832507259ded9700de81f5fd462caf0d5be8,Geometric Approach for Human Emotion Recognition using Facial Expression,"International Journal of Computer Applications (0975 – 8887)
+Volume 118 – No.14, May 2015
+Geometric Approach for Human Emotion
+Recognition using Facial Expression
+S. S. Bavkar
+Assistant Professor
+VPCOE Baramati
+J. S. Rangole
+Assistant Professor
+VPCOE Baramati
+V. U. Deshmukh
+Assistant Professor
+VPCOE Baramati"
+08d40ee6e1c0060d3b706b6b627e03d4b123377a,Towards Weakly-Supervised Action Localization,"Human Action Localization
+with Sparse Spatial Supervision
+Philippe Weinzaepfel, Xavier Martin, and Cordelia Schmid, Fellow, IEEE"
+088aabe3da627432fdccf5077969e3f6402f0a80,Classifier-to-generator Attack: Estimation,"Under review as a conference paper at ICLR 2018
+CLASSIFIER-TO-GENERATOR ATTACK: ESTIMATION
+OF TRAINING DATA DISTRIBUTION FROM CLASSIFIER
+Anonymous authors
+Paper under double-blind review"
+08903bf161a1e8dec29250a752ce9e2a508a711c,Joint Dimensionality Reduction and Metric Learning: A Geometric Take,"Joint Dimensionality Reduction and Metric Learning: A Geometric Take
+Mehrtash Harandi 1 2 Mathieu Salzmann 3 Richard Hartley 2 1"
+08e24f9df3d55364290d626b23f3d42b4772efb6,Enhancing facial expression classification by information fusion,"ENHANCING FACIAL EXPRESSION CLASSIFICATION BY INFORMATION
+FUSION
+I. Buciu1, Z. Hammal 2, A. Caplier2, N. Nikolaidis 1, and I. Pitas 1
+AUTH/Department of Informatics/ Aristotle University of Thessaloniki
+phone: + 30(2310)99.6361, fax: + 30(2310)99.8453, email:
+GR-54124, Thessaloniki, Box 451, Greece
+Laboratoire des Images et des Signaux / Institut National Polytechnique de Grenoble
+phone: + 33(0476)574363, fax: + 33(0476)57 47 90, email:
+web: http://www.aiia.csd.auth.gr
+8031 Grenoble, France
+web: http://www.lis.inpg.fr"
+0857281a3b6a5faba1405e2c11f4e17191d3824d,Face recognition via edge-based Gabor feature representation for plastic surgery-altered images,"Chude-Olisah et al. EURASIP Journal on Advances in Signal Processing 2014, 2014:102
+http://asp.eurasipjournals.com/content/2014/1/102
+R ES EAR CH
+Face recognition via edge-based Gabor feature
+representation for plastic surgery-altered images
+Chollette C Chude-Olisah1*, Ghazali Sulong1, Uche A K Chude-Okonkwo2 and Siti Z M Hashim1
+Open Access"
+08f6745bc6c1b0fb68953ea61054bdcdde6d2fc7,Understanding Kin Relationships in a Photo,"Understanding Kin Relationships in a Photo
+Siyu Xia, Ming Shao, Student Member, IEEE, Jiebo Luo, Fellow, IEEE, and Yun Fu, Senior Member, IEEE"
+6dd052df6b0e89d394192f7f2af4a3e3b8f89875,A literature survey on Facial Expression Recognition using Global Features,"International Journal of Engineering and Advanced Technology (IJEAT)
+ISSN: 2249 – 8958, Volume-2, Issue-4, April 2013
+A literature survey on Facial Expression
+Recognition using Global Features
+Vaibhavkumar J. Mistry, Mahesh M. Goyani"
+6dd5dbb6735846b214be72983e323726ef77c7a9,A Survey on Newer Prospective Biometric Authentication Modalities,"Josai Mathematical Monographs
+vol. 7 (2014), pp. 25-40
+A Survey on Newer Prospective
+Biometric Authentication Modalities
+Narishige Abe, Takashi Shinzaki"
+6d10beb027fd7213dd4bccf2427e223662e20b7d,User Adaptive and Context-Aware Smart Home Using Pervasive and Semantic Technologies,"Publishing CorporationJournal of Electrical and Computer EngineeringVolume 2016, Article ID 4789803, 20 pageshttp://dx.doi.org/10.1155/2016/4789803"
+6dddf1440617bf7acda40d4d75c7fb4bf9517dbb,"Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks - Counting, Detection, and Tracking","JOURNAL OF LATEX CLASS FILES, VOL. XX, NO. X, MM YY
+Beyond Counting: Comparisons of Density Maps for Crowd
+Analysis Tasks - Counting, Detection, and Tracking
+Di Kang, Zheng Ma, Member, IEEE, Antoni B. Chan Senior Member, IEEE,"
+6d07e176c754ac42773690d4b4919a39df85d7ec,Face Attribute Prediction Using Off-The-Shelf Deep Learning Networks,"Face Attribute Prediction Using Off-The-Shelf Deep
+Learning Networks
+Yang Zhong
+Josephine Sullivan
+Haibo Li
+Computer Science and Communication
+KTH Royal Institute of Technology
+00 44 Stockholm, Sweden
+{yzhong, sullivan,"
+6d4b5444c45880517213a2fdcdb6f17064b3fa91,Harvesting Image Databases from The Web,"Journal of Information Engineering and Applications
+ISSN 2224-5782 (print) ISSN 2225-0506 (online)
+Vol 2, No.3, 2012
+www.iiste.org
+Harvesting Image Databases from The Web
+Snehal M. Gaikwad
+G.H.Raisoni College of Engg. & Mgmt.,Pune,India
+Snehal S. Pathare
+G.H.Raisoni College of Engg. & Mgmt.,Pune,India
+Trupti A. Jachak
+G.H.Raisoni College of Engg. & Mgmt.,Pune,India"
+6d8c9a1759e7204eacb4eeb06567ad0ef4229f93,"Face Alignment Robust to Pose, Expressions and Occlusions","Face Alignment Robust to Pose, Expressions and
+Occlusions
+Vishnu Naresh Boddeti†, Myung-Cheol Roh†, Jongju Shin, Takaharu Oguri, Takeo Kanade"
+6d618657fa5a584d805b562302fe1090957194ba,Human Facial Expression Recognition based on Principal Component Analysis and Artificial Neural Network,"Full Paper
+NNGT Int. J. of Artificial Intelligence , Vol. 1, July 2014
+Human Facial Expression Recognition based
+on Principal Component Analysis and
+Artificial Neural Network
+Laboratory of Automatic and Signals Annaba (LASA) , Department of electronics, Faculty of Engineering,
+Zermi.Narima, Ramdani.M, Saaidia.M
+Badji-Mokhtar University, P.O.Box 12, Annaba-23000, Algeria.
+E-Mail :"
+6d66c98009018ac1512047e6bdfb525c35683b16,Face Recognition Based on Fitting a 3D Morphable Model,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 25, NO. 9, SEPTEMBER 2003
+Face Recognition Based on
+Fitting a 3D Morphable Model
+Volker Blanz and Thomas Vetter, Member, IEEE"
+0172867f4c712b33168d9da79c6d3859b198ed4c,Expression and illumination invariant preprocessing technique for Face Recognition,"Technique for Face Recognition
+Computer and System Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt
+A. Abbas, M. I. Khalil, S. Abdel-Hay, H. M. Fahmy
+Expression and Illumination Invariant Preprocessing"
+0145dc4505041bf39efa70ea6d95cf392cfe7f19,Human action segmentation with hierarchical supervoxel consistency,"Human Action Segmentation with Hierarchical Supervoxel Consistency
+Jiasen Lu1, Ran Xu1 Jason J. Corso2
+Department of Computer Science and Engineering, SUNY at Buffalo. 2Department of EECS, University of Michigan.
+Detailed analysis of human action, such as classiﬁcation, detection and lo-
+alization has received increasing attention from the community; datasets
+like J-HMDB [1] have made it plausible to conduct studies analyzing the
+impact that such deeper information has on the greater action understanding
+problem. However, detailed automatic segmentation of human action has
+omparatively been unexplored. In this paper, we introduce a hierarchical
+MRF model to automatically segment human action boundaries in videos
+“in-the-wild” (see Fig. 1).
+We ﬁrst propose a human motion saliency representation which incor-
+porates two parts: foreground motion and human appearance information.
+For foreground motion estimation, we propose a new motion saliency fea-
+ture by using long-term trajectories to build a camera motion model, and
+then measure the motion saliency via the deviation from the camera model.
+For human appearance information, we use a DPM person detector trained
+on PASCAL VOC 2007 and construct a saliency map by averaging the nor-
+malized detection score of all the scale and all components.
+Then, to segment the human action, we start by applying hierarchical"
+01bef320b83ac4405b3fc5b1cff788c124109fb9,Translating Head Motion into Attention - Towards Processing of Student's Body-Language,"de Lausanne
+RLC D1 740, CH-1015
+Lausanne
+de Lausanne
+RLC D1 740, CH-1015
+Lausanne
+de Lausanne
+RLC D1 740, CH-1015
+Lausanne
+Translating Head Motion into Attention - Towards
+Processing of Student’s Body-Language
+Mirko Raca
+CHILI Laboratory
+Łukasz Kidzi´nski
+CHILI Laboratory
+Pierre Dillenbourg
+CHILI Laboratory
+École polytechnique fédérale
+École polytechnique fédérale
+École polytechnique fédérale"
+01c8d7a3460422412fba04e7ee14c4f6cdff9ad7,Rule Based System for Recognizing Emotions Using Multimodal Approach,"(IJACSA) International Journal of Advanced Computer Science and Applications,
+Vol. 4, No. 7, 2013
+Rule Based System for Recognizing Emotions Using
+Multimodal Approach
+Preeti Khanna
+Information System
+SBM, SVKM’s NMIMS
+Mumbai, India"
+0163d847307fae508d8f40ad193ee542c1e051b4,Classemes and Other Classifier-Based Features for Efficient Object Categorization,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JANUARY 2007
+Classemes and Other Classiﬁer-based
+Features for Efﬁcient Object Categorization
+- Supplementary material -
+Alessandro Bergamo, and Lorenzo Torresani, Member, IEEE
+LOW-LEVEL FEATURES
+We extract the SIFT [1] features for our descriptor
+ccording to the following pipeline. We ﬁrst convert
+each image to gray-scale, then we normalize the con-
+trast by forcing the 0.01% of lightest and darkest pixels
+to be mapped to white and black respectively, and
+linearly rescaling the values in between. All images
+exceeding 786,432 pixels of resolution are downsized
+to this maximum value while keeping the aspect ratio.
+The 128-dimensional SIFT descriptors are computed
+from the interest points returned by a DoG detec-
+tor [2]. We ﬁnally compute a Bag-Of-Word histogram
+of these descriptors, using a K-means vocabulary of
+500 words.
+CLASSEMES"
+01c4cf9c7c08f0ad3f386d88725da564f3c54679,Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV),"Interpretability Beyond Feature Attribution:
+Quantitative Testing with Concept Activation Vectors (TCAV)
+Been Kim Martin Wattenberg Justin Gilmer Carrie Cai James Wexler
+Fernanda Viegas Rory Sayres"
+017ce398e1eb9f2eed82d0b22fb1c21d3bcf9637,Face Recognition with Harmonic De-lighting,"FACE RECOGNITION WITH HARMONIC DE-LIGHTING
+Laiyun Qing1,2, Shiguang Shan2, Wen Gao1,2
+ICT-ISVISION Joint R&D Laboratory for Face Recognition, CAS, Beijing, China, 100080
+Graduate School, CAS, Beijing, China, 100080
+Emails: {lyqing, sgshan, wgao}jdl.ac.cn"
+014e3d0fa5248e6f4634dc237e2398160294edce,What does 2D geometric information really tell us about 3D face shape?,"Int J Comput Vis manuscript No.
+(will be inserted by the editor)
+What does 2D geometric information really tell us about
+D face shape?
+Anil Bas1 · William A. P. Smith1
+Received: date / Accepted: date"
+011e6146995d5d63c852bd776f782cc6f6e11b7b,Fast Training of Triplet-Based Deep Binary Embedding Networks,"Fast Training of Triplet-based Deep Binary Embedding Networks
+Bohan Zhuang, Guosheng Lin, Chunhua Shen∗, Ian Reid
+The University of Adelaide; and Australian Centre for Robotic Vision"
+0181fec8e42d82bfb03dc8b82381bb329de00631,Discriminative Subspace Clustering,"Discriminative Subspace Clustering
+Vasileios Zografos∗1, Liam Ellis†1, and Rudolf Mester‡1 2
+CVL, Dept. of Electrical Engineering, Link¨oping University, Link¨oping, Sweden
+VSI Lab, Computer Science Department, Goethe University, Frankfurt, Germany"
+0113b302a49de15a1d41ca4750191979ad756d2f,Matching Faces with Textual Cues in Soccer Videos,"424403677/06/$20.00 ©2006 IEEE
+ICME 2006"
+0601416ade6707c689b44a5bb67dab58d5c27814,Feature Selection in Face Recognition: A Sparse Representation Perspective,"Feature Selection in Face Recognition: A Sparse
+Representation Perspective
+Allan Y. Yang
+John Wright
+Yi Ma
+S. Shankar Sastry
+Electrical Engineering and Computer Sciences
+University of California at Berkeley
+Technical Report No. UCB/EECS-2007-99
+http://www.eecs.berkeley.edu/Pubs/TechRpts/2007/EECS-2007-99.html
+August 14, 2007"
+064b797aa1da2000640e437cacb97256444dee82,Coarse-to-fine Face Alignment with Multi-Scale Local Patch Regression,"Coarse-to-ﬁne Face Alignment with Multi-Scale Local Patch Regression
+Zhiao Huang
+Megvii Inc.
+Erjin Zhou
+Megvii Inc.
+Zhimin Cao
+Megvii Inc."
+06f146dfcde10915d6284981b6b84b85da75acd4,Scalable Face Image Retrieval Using Attribute-Enhanced Sparse Codewords,"Scalable Face Image Retrieval using
+Attribute-Enhanced Sparse Codewords
+Bor-Chun Chen, Yan-Ying Chen, Yin-Hsi Kuo, Winston H. Hsu"
+0697bd81844d54064d992d3229162fe8afcd82cb,User-driven mobile robot storyboarding: Learning image interest and saliency from pairwise image comparisons,"User-driven mobile robot storyboarding: Learning image interest and
+saliency from pairwise image comparisons
+Michael Burke1"
+06262d6beeccf2784e4e36a995d5ee2ff73c8d11,Recognize Actions by Disentangling Components of Dynamics,"Recognize Actions by Disentangling Components of Dynamics
+Yue Zhao1, Yuanjun Xiong1,2, and Dahua Lin1
+CUHK - SenseTime Joint Lab, The Chinese University of Hong Kong 2Amazon Rekognition"
+06d93a40365da90f30a624f15bf22a90d9cfe6bb,Learning from Candidate Labeling Sets,"Learning from Candidate Labeling Sets
+Idiap Research Institute and EPF Lausanne
+Luo Jie
+Francesco Orabona
+DSI, Universit`a degli Studi di Milano"
+06e7e99c1fdb1da60bc3ec0e2a5563d05b63fe32,WhittleSearch: Image search with relative attribute feedback,"WhittleSearch: Image Search with Relative Attribute Feedback
+Adriana Kovashka, Devi Parikh and Kristen Grauman
+(Supplementary Material)
+Comparative Qualitative Search Results
+We present three qualitative search results for human-generated feedback, in addition to those
+shown in the paper. Each example shows one search iteration, where the 20 reference images are
+randomly selected (rather than ones that match a keyword search, as the image examples in the
+main paper illustrate). For each result, the ﬁrst ﬁgure shows our method and the second ﬁgure
+shows the binary feedback result for the corresponding target image. Note that for our method,
+“more/less X” (where X is an attribute) means that the target image is more/less X than the
+reference image which is shown.
+Figures 1 and 2 show results for human-generated relative attribute and binary feedback, re-
+spectively, when both methods are used to target the same “mental image” of a shoe shown in the
+top left bubble. The top right grid of 20 images are the reference images displayed to the user, and
+those outlined and annotated with constraints are the ones chosen by the user to give feedback.
+The bottom row of images in either ﬁgure shows the top-ranked images after integrating the user’s
+feedback into the scoring function, revealing the two methods’ respective performance. We see that
+while both methods retrieve high-heeled shoes, only our method retrieves images that are as “open”
+s the target image. This is because using the proposed approach, the user was able to comment
+explicitly on the desired openness property."
+066d71fcd997033dce4ca58df924397dfe0b5fd1,Iranian Face Database and Evaluation with a New Detection Algorithm,"(cid:1)(cid:2)(cid:3)(cid:4)(cid:5)(cid:3)(cid:4)(cid:6)(cid:7)(cid:3)(cid:8)(cid:9)(cid:6)(cid:10)(cid:3)(cid:11)(cid:3)(cid:12)(cid:3)(cid:13)(cid:9)
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+(cid:3)(cid:4)(cid:5)(cid:6)(cid:7)(cid:8)(cid:1)(cid:9)(cid:10)(cid:10)(cid:8)(cid:11)(cid:6)(cid:8)(cid:12)(cid:1)(cid:13)(cid:6)(cid:7)(cid:14) (cid:3)(cid:15)(cid:16)(cid:8)(cid:17)(cid:17)(cid:8)(cid:18)(cid:1)(cid:3)(cid:8)(cid:16)(cid:18)(cid:6)(cid:1)(cid:19)(cid:4)(cid:16)(cid:11)(cid:16)(cid:6)(cid:10)(cid:6)(cid:14)(cid:1)(cid:19)(cid:20)(cid:21)(cid:1)(cid:9)(cid:22)(cid:8)(cid:17)(cid:1)(cid:23)(cid:8)(cid:11)(cid:24)(cid:8)(cid:12)(cid:25)(cid:8)(cid:20)(cid:18)
+(cid:23)(cid:12)(cid:13)(cid:11)(cid:2)(cid:3)(cid:8)(cid:11)$(cid:1)’(cid:16)(cid:6)(cid:11) ((cid:8)((cid:4)(cid:20)(cid:1)(cid:6)(cid:12)(cid:24)(cid:20)(cid:15)(cid:18))(cid:27)(cid:4)(cid:11)(cid:1)(cid:8)(cid:1)(cid:18)(cid:8)(cid:24)(cid:8)(cid:10)(cid:8)(cid:11)(cid:4)(cid:1)(cid:15)(cid:25)(cid:1)(cid:15)(cid:29)(cid:4)(cid:20)(cid:1)*(cid:14)+,,(cid:1)(cid:27)(cid:15)(cid:5)(cid:15)(cid:20)(cid:1)(cid:6)(cid:17)(cid:8)-(cid:4)(cid:11)(cid:1).(cid:4)(cid:1)(cid:27)(cid:15)(cid:5)(cid:5)(cid:4)(cid:27)(cid:24)(cid:4)(cid:18)(cid:1)(cid:25)(cid:20)(cid:15)(cid:17)(cid:1)+(cid:2)+(cid:1)(cid:18)(cid:6)(cid:25)(cid:25)(cid:4)(cid:20)(cid:4)(cid:12)(cid:24)(cid:1)(cid:16))(cid:17)(cid:8)(cid:12)(cid:1)(cid:25)(cid:8)(cid:27)(cid:4)(cid:11) (cid:6)(cid:12)(cid:1)(cid:8)-(cid:4)(cid:11)(cid:1)(cid:10)(cid:4)(cid:24).(cid:4)(cid:4)(cid:12)(cid:1)/
+(cid:8)(cid:12)(cid:18) 01(cid:21)(cid:1)2(cid:4)(cid:1)(cid:12)(cid:8)(cid:17)(cid:4)(cid:18)(cid:1)(cid:24)(cid:16)(cid:6)(cid:11)(cid:1)(cid:18)(cid:8)(cid:24)(cid:8)(cid:10)(cid:8)(cid:11)(cid:4)(cid:1)(cid:24)(cid:16)(cid:4)(cid:1)(cid:26)(cid:20)(cid:8)(cid:12)(cid:6)(cid:8)(cid:12)(cid:1)3(cid:8)(cid:27)(cid:4)(cid:1)(cid:19)(cid:8)(cid:24)(cid:8)(cid:10)(cid:8)(cid:11)(cid:4)(cid:1)4(cid:26)3(cid:19)(cid:23)5(cid:21)(cid:1)’(cid:15)(cid:1)(cid:4)(cid:29)(cid:8)(cid:5))(cid:8)(cid:24)(cid:4)(cid:1)(cid:24)(cid:16)(cid:4)(cid:1)(cid:18)(cid:8)(cid:24)(cid:8)(cid:10)(cid:8)(cid:11)(cid:4)(cid:1)(cid:24)(cid:16)(cid:4)(cid:1)(cid:4)6((cid:4)(cid:20)(cid:6)(cid:17)(cid:4)(cid:12)(cid:24)(cid:8)(cid:5)(cid:1)(cid:20)(cid:4)(cid:11))(cid:5)(cid:24)(cid:1)(cid:15)(cid:25)(cid:1)(cid:8)(cid:1)(cid:12)(cid:4).(cid:1)(cid:25)(cid:8)(cid:27)(cid:6)(cid:8)(cid:5)(cid:1)
+(cid:25)(cid:4)(cid:8)(cid:24))(cid:20)(cid:4)(cid:1)(cid:18)(cid:4)(cid:24)(cid:4)(cid:27)(cid:24)(cid:6)(cid:15)(cid:12)(cid:1)(cid:8)(cid:5)-(cid:15)(cid:20)(cid:6)(cid:24)(cid:16)(cid:17)(cid:1)(cid:6)(cid:11)(cid:1)(cid:20)(cid:4)((cid:15)(cid:20)(cid:24)(cid:4)(cid:18)(cid:21)
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+8)(cid:17)(cid:8)(cid:12)(cid:1) (cid:25)(cid:8)(cid:27)(cid:4)(cid:1) (cid:6)(cid:11)(cid:1) (cid:24)(cid:16)(cid:4)(cid:1) (cid:17)(cid:15)(cid:11)(cid:24)(cid:1) (cid:27)(cid:15)(cid:17)(cid:17)(cid:15)(cid:12)(cid:1) (cid:8)(cid:12)(cid:18)(cid:1) )(cid:11)(cid:4)(cid:25))(cid:5)(cid:1) (cid:7)(cid:4)(cid:30)(cid:1) (cid:24)(cid:15)(cid:1) (cid:8)(cid:1)
+((cid:4)(cid:20)(cid:11)(cid:15)(cid:12)9(cid:11)(cid:1) (cid:6)(cid:18)(cid:4)(cid:12)(cid:24)(cid:6)(cid:24)(cid:30)(cid:21)(cid:1) (cid:9)(cid:11)(cid:1) (cid:16))(cid:17)(cid:8)(cid:12)(cid:11)(cid:14)(cid:1) .(cid:4)(cid:1) (cid:8)(cid:20)(cid:4)(cid:1) (cid:8)(cid:10)(cid:5)(cid:4)(cid:1) (cid:24)(cid:15)(cid:1) (cid:27)(cid:8)(cid:24)(cid:4)-(cid:15)(cid:20)(cid:6)(cid:22)(cid:4)(cid:1) (cid:8)(cid:1)
+((cid:4)(cid:20)(cid:11)(cid:15)(cid:12):(cid:11)(cid:1)(cid:8)-(cid:4)(cid:1)-(cid:20)(cid:15))((cid:1)(cid:25)(cid:20)(cid:15)(cid:17)(cid:1)(cid:8)(cid:1)((cid:4)(cid:20)(cid:11)(cid:15)(cid:12):(cid:11)(cid:1)(cid:25)(cid:8)(cid:27)(cid:4)(cid:1)(cid:6)(cid:17)(cid:8)-(cid:4)(cid:1)(cid:8)(cid:12)(cid:18)(cid:1)(cid:8)(cid:20)(cid:4)(cid:1)(cid:15)(cid:25)(cid:24)(cid:4)(cid:12)(cid:1)
+(cid:8)(cid:10)(cid:5)(cid:4)(cid:1)(cid:24)(cid:15)(cid:1)(cid:10)(cid:4)(cid:1);)(cid:6)(cid:24)(cid:4)(cid:1)((cid:20)(cid:4)(cid:27)(cid:6)(cid:11)(cid:4)(cid:1)(cid:6)(cid:12)(cid:1)(cid:24)(cid:16)(cid:6)(cid:11)(cid:1)(cid:4)(cid:11)(cid:24)(cid:6)(cid:17)(cid:8)(cid:24)(cid:6)(cid:15)(cid:12)(cid:1)<(cid:2)=(cid:21)(cid:1)(cid:26)(cid:12)(cid:1)(cid:20)(cid:4)(cid:27)(cid:4)(cid:12)(cid:24)(cid:1)(cid:30)(cid:4)(cid:8)(cid:20)(cid:11)(cid:14)(cid:1)
+(cid:25)(cid:8)(cid:27)(cid:4)(cid:1) (cid:20)(cid:4)(cid:27)(cid:15)-(cid:12)(cid:6)(cid:24)(cid:6)(cid:15)(cid:12)(cid:1) (cid:8)(cid:12)(cid:18)(cid:1) (cid:20)(cid:4)(cid:5)(cid:8)(cid:24)(cid:4)(cid:18)(cid:1) .(cid:15)(cid:20)(cid:7)(cid:11)(cid:1) (cid:16)(cid:8)(cid:29)(cid:4)(cid:1) (cid:20)(cid:4)(cid:27)(cid:4)(cid:6)(cid:29)(cid:4)(cid:18)(cid:1) (cid:11))(cid:10)(cid:11)(cid:24)(cid:8)(cid:12)(cid:24)(cid:6)(cid:8)(cid:5)(cid:1)
+(cid:8)(cid:24)(cid:24)(cid:4)(cid:12)(cid:24)(cid:6)(cid:15)(cid:12)(cid:1) (cid:25)(cid:20)(cid:15)(cid:17)(cid:1) (cid:20)(cid:4)(cid:11)(cid:4)(cid:8)(cid:20)(cid:27)(cid:16)(cid:4)(cid:20)(cid:11)(cid:1) (cid:6)(cid:12)(cid:1) (cid:10)(cid:6)(cid:15)(cid:17)(cid:4)(cid:24)(cid:20)(cid:6)(cid:27)(cid:11)(cid:14)(cid:1) ((cid:8)(cid:24)(cid:24)(cid:4)(cid:20)(cid:12)(cid:1) (cid:20)(cid:4)(cid:27)(cid:15)-(cid:12)(cid:6)(cid:24)(cid:6)(cid:15)(cid:12)(cid:14)(cid:1)
+(cid:8)(cid:12)(cid:18)(cid:1) (cid:27)(cid:15)(cid:17)()(cid:24)(cid:4)(cid:20) (cid:29)(cid:6)(cid:11)(cid:6)(cid:15)(cid:12)(cid:1) (cid:27)(cid:15)(cid:17)(cid:17))(cid:12)(cid:6)(cid:24)(cid:6)(cid:4)(cid:11)(cid:1) </(cid:14)(cid:1) *(cid:14)(cid:1) > (cid:8)(cid:12)(cid:18) 1=(cid:21)(cid:1) ’(cid:16)(cid:4)(cid:11)(cid:4)(cid:1)
+(cid:27)(cid:15)(cid:17)(cid:17)(cid:15)(cid:12)(cid:1)(cid:6)(cid:12)(cid:24)(cid:4)(cid:20)(cid:4)(cid:11)(cid:24)(cid:11)(cid:1)(cid:8)(cid:17)(cid:15)(cid:12)-(cid:1)(cid:20)(cid:4)(cid:11)(cid:4)(cid:8)(cid:20)(cid:27)(cid:16)(cid:4)(cid:20)(cid:11)(cid:1)(cid:17)(cid:15)(cid:24)(cid:6)(cid:29)(cid:8)(cid:24)(cid:4)(cid:18)(cid:1))(cid:11)(cid:1)(cid:24)(cid:15)(cid:1)(cid:27)(cid:15)(cid:5)(cid:5)(cid:4)(cid:27)(cid:24)(cid:1)(cid:8)(cid:1)
+(cid:18)(cid:8)(cid:24)(cid:8)(cid:10)(cid:8)(cid:11)(cid:4)(cid:1) (cid:15)(cid:25)(cid:1) (cid:25)(cid:8)(cid:27)(cid:6)(cid:8)(cid:5)(cid:1) (cid:6)(cid:17)(cid:8)-(cid:4)(cid:11)(cid:1) (cid:25)(cid:20)(cid:15)(cid:17)(cid:1) ((cid:4)(cid:15)((cid:5)(cid:4)(cid:1) (cid:6)(cid:12)(cid:1) (cid:18)(cid:6)(cid:25)(cid:25)(cid:4)(cid:20)(cid:4)(cid:12)(cid:24)(cid:1) (cid:8)-(cid:4)(cid:11)(cid:21) ’(cid:16)(cid:4)(cid:1)
+(cid:18)(cid:8)(cid:24)(cid:8)(cid:10)(cid:8)(cid:11)(cid:4)(cid:1)(cid:6)(cid:11)(cid:1)(cid:6)(cid:12)(cid:24)(cid:4)(cid:12)(cid:18)(cid:4)(cid:18)(cid:1)(cid:25)(cid:15)(cid:20)(cid:1)(cid:18)(cid:6)(cid:11)(cid:24)(cid:20)(cid:6)(cid:10))(cid:24)(cid:6)(cid:15)(cid:12)(cid:1)(cid:24)(cid:15)(cid:1)(cid:20)(cid:4)(cid:11)(cid:4)(cid:8)(cid:20)(cid:27)(cid:16)(cid:4)(cid:20)(cid:11)(cid:21)
+’(cid:16)(cid:4)(cid:20)(cid:4)(cid:1) (cid:8)(cid:20)(cid:4)(cid:1) (cid:17)(cid:8)(cid:12)(cid:30)(cid:1) ()(cid:10)(cid:5)(cid:6)(cid:27)(cid:8)(cid:5)(cid:5)(cid:30)(cid:1) (cid:8)(cid:29)(cid:8)(cid:6)(cid:5)(cid:8)(cid:10)(cid:5)(cid:4)(cid:1) (cid:18)(cid:8)(cid:24)(cid:8)(cid:10)(cid:8)(cid:11)(cid:4)(cid:11)(cid:1) (cid:25)(cid:15)(cid:20)(cid:1) (cid:25)(cid:8)(cid:27)(cid:4)(cid:1)"
+06560d5721ecc487a4d70905a485e22c9542a522,Deep Facial Attribute Detection in the Wild: From General to Specific,"SUN, YU: DEEP FACIAL ATTRIBUTE DETECTION IN THE WILD
+Deep Facial Attribute Detection in the Wild:
+From General to Speciﬁc
+Yuechuan Sun
+Jun Yu
+Department of Automation
+University of Science and Technology
+of China
+Hefei, China"
+06fe63b34fcc8ff68b72b5835c4245d3f9b8a016,Learning semantic representations of objects and their parts,"Mach Learn
+DOI 10.1007/s10994-013-5336-9
+Learning semantic representations of objects
+nd their parts
+Grégoire Mesnil · Antoine Bordes · Jason Weston ·
+Gal Chechik · Yoshua Bengio
+Received: 24 May 2012 / Accepted: 26 February 2013
+© The Author(s) 2013"
+06aab105d55c88bd2baa058dc51fa54580746424,Image Set-Based Collaborative Representation for Face Recognition,"Image Set based Collaborative Representation for
+Face Recognition
+Pengfei Zhu, Student Member, IEEE, Wangmeng Zuo, Member, IEEE, Lei Zhang, Member, IEEE, Simon C.K. Shiu,
+Member, IEEE, David Zhang, Fellow, IEEE"
+06262d14323f9e499b7c6e2a3dec76ad9877ba04,Real-Time Pose Estimation Piggybacked on Object Detection,"Real-Time Pose Estimation Piggybacked on Object Detection
+Roman Jur´anek, Adam Herout, Mark´eta Dubsk´a, Pavel Zemˇc´ık
+Brno University of Technology
+Brno, Czech Republic"
+062c41dad67bb68fefd9ff0c5c4d296e796004dc,Temporal Generative Adversarial Nets with Singular Value Clipping,"Temporal Generative Adversarial Nets with Singular Value Clipping
+Masaki Saito∗
+Eiichi Matsumoto∗
+Preferred Networks inc., Japan
+{msaito, matsumoto,
+Shunta Saito"
+06400a24526dd9d131dfc1459fce5e5189b7baec,Event Recognition in Photo Collections with a Stopwatch HMM,"Event Recognition in Photo Collections with a Stopwatch HMM
+Lukas Bossard1
+Matthieu Guillaumin1
+Luc Van Gool1,2
+Computer Vision Lab
+ETH Z¨urich, Switzerland
+ESAT, PSI-VISICS
+K.U. Leuven, Belgium"
+0694b05cbc3ef5d1c5069a4bfb932a5a7b4d5ff0,Exploiting Local Class Information in Extreme Learning Machine,"Iosifidis, A., Tefas, A., & Pitas, I. (2014). Exploiting Local Class Information
+in Extreme Learning Machine. Paper presented at International Joint
+Conference on Computational Intelligence (IJCCI), Rome, Italy.
+Peer reviewed version
+Link to publication record in Explore Bristol Research
+PDF-document
+University of Bristol - Explore Bristol Research
+General rights
+This document is made available in accordance with publisher policies. Please cite only the published
+version using the reference above. Full terms of use are available:
+http://www.bristol.ac.uk/pure/about/ebr-terms"
+060820f110a72cbf02c14a6d1085bd6e1d994f6a,Fine-grained classification of pedestrians in video: Benchmark and state of the art,"Fine-Grained Classiﬁcation of Pedestrians in Video: Benchmark and State of the Art
+David Hall and Pietro Perona
+California Institute of Technology.
+The dataset was labelled with bounding boxes, tracks, pose and ﬁne-
+grained labels. To achieve this, crowdsourcing, using workers from Ama-
+zon’s Mechanical Turk (MTURK) was used. A summary of the dataset’s
+statistics can be found in Table 1.
+Number of Frames Sent to MTURK
+Number of Frames with at least 1 Pedestrian
+Number of Bounding Box Labels
+Number of Pose Labels
+Number of Tracks
+8,708
+0,994
+2,457
+7,454
+,222
+Table 1: Dataset Statistics
+A state-of-the-art algorithm for ﬁne-grained classiﬁcation was tested us-
+ing the dataset. The results are reported as a useful performance baseline."
+063a3be18cc27ba825bdfb821772f9f59038c207,The development of spontaneous facial responses to others’ emotions in infancy: An EMG study,"This is a repository copy of The development of spontaneous facial responses to others’
+emotions in infancy. An EMG study.
+White Rose Research Online URL for this paper:
+http://eprints.whiterose.ac.uk/125231/
+Version: Published Version
+Article:
+Kaiser, Jakob, Crespo-Llado, Maria Magdalena, Turati, Chiara et al. (1 more author)
+(2017) The development of spontaneous facial responses to others’ emotions in infancy.
+An EMG study. Scientific Reports. ISSN 2045-2322
+https://doi.org/10.1038/s41598-017-17556-y
+Reuse
+This article is distributed under the terms of the Creative Commons Attribution (CC BY) licence. This licence
+llows you to distribute, remix, tweak, and build upon the work, even commercially, as long as you credit the
+uthors for the original work. More information and the full terms of the licence here:
+https://creativecommons.org/licenses/
+Takedown
+If you consider content in White Rose Research Online to be in breach of UK law, please notify us by
+emailing including the URL of the record and the reason for the withdrawal request.
+https://eprints.whiterose.ac.uk/"
+06ad99f19cf9cb4a40741a789e4acbf4433c19ae,SenTion: A framework for Sensing Facial Expressions,"SenTion: A framework for Sensing Facial
+Expressions
+Rahul Islam∗, Karan Ahuja∗, Sandip Karmakar∗, Ferdous Barbhuiya∗ ∗IIIT Guwahati
+{rahul.islam, karan.ahuja, sandip,"
+6c27eccf8c4b22510395baf9f0d0acc3ee547862,Using CMU PIE Human Face Database to a Convolutional Neural Network - Neocognitron,"Using CMU PIE Human Face Database to a
+Convolutional Neural Network - Neocognitron
+José Hiroki Saito1, Tiago Vieira de Carvalho1, Marcelo Hirakuri1, André Saunite1,
+Alessandro Noriaki Ide2 and Sandra Abib1
+- Federal University of São Carlos - Computer Science Department - GAPIS
+Rodovia Washington Luis, Km 235, São Carlos – SP - Brazil
+- University of Genoa - Department of Informatics, Systems and Telematics - Neurolab
+Via Opera Pia, 13 – I-16145 – Genoa - Italy"
+6cefb70f4668ee6c0bf0c18ea36fd49dd60e8365,Privacy-Preserving Deep Inference for Rich User Data on The Cloud,"Privacy-Preserving Deep Inference for Rich User
+Data on The Cloud
+Seyed Ali Osia ♯, Ali Shahin Shamsabadi ♯, Ali Taheri ♯, Kleomenis Katevas ⋆,
+Hamid R. Rabiee ♯, Nicholas D. Lane †, Hamed Haddadi ⋆
+♯ Sharif University of Technology
+⋆ Queen Mary University of London
+Nokia Bell Labs & University of Oxford"
+6c304f3b9c3a711a0cca5c62ce221fb098dccff0,Attentive Semantic Video Generation Using Captions,"Attentive Semantic Video Generation using Captions
+Tanya Marwah∗
+IIT Hyderabad
+Gaurav Mittal∗
+Vineeth N. Balasubramanian
+IIT Hyderabad"
+6cb7648465ba7757ecc9c222ac1ab6402933d983,Visual Forecasting by Imitating Dynamics in Natural Sequences,"Visual Forecasting by Imitating Dynamics in Natural Sequences
+Kuo-Hao Zeng†‡ William B. Shen† De-An Huang† Min Sun‡ Juan Carlos Niebles†
+{khzeng, bshen88, dahuang,
+Stanford University ‡National Tsing Hua University"
+6c2b392b32b2fd0fe364b20c496fcf869eac0a98,Fully automatic face recognition framework based on local and global features,"DOI 10.1007/s00138-012-0423-7
+ORIGINAL PAPER
+Fully automatic face recognition framework based
+on local and global features
+Cong Geng · Xudong Jiang
+Received: 30 May 2011 / Revised: 21 February 2012 / Accepted: 29 February 2012 / Published online: 22 March 2012
+© Springer-Verlag 2012"
+6cddc7e24c0581c50adef92d01bb3c73d8b80b41,Face Verification Using the LARK Representation,"Face Veriﬁcation Using the LARK
+Representation
+Hae Jong Seo, Student Member, IEEE, Peyman Milanfar, Fellow, IEEE,"
+6cfc337069868568148f65732c52cbcef963f79d,Audio-Visual Speaker Localization via Weighted Clustering Israel -,"Audio-Visual Speaker Localization via Weighted
+Clustering
+Israel-Dejene Gebru, Xavier Alameda-Pineda, Radu Horaud, Florence Forbes
+To cite this version:
+Israel-Dejene Gebru, Xavier Alameda-Pineda, Radu Horaud, Florence Forbes. Audio-Visual Speaker
+Localization via Weighted Clustering. IEEE Workshop on Machine Learning for Signal Processing,
+Sep 2014, Reims, France. pp.1-6, 2014, <10.1109/MLSP.2014.6958874>. <hal-01053732>
+HAL Id: hal-01053732
+https://hal.archives-ouvertes.fr/hal-01053732
+Submitted on 11 Aug 2014
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entific research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destinée au dépôt et à la diffusion de documents
+scientifiques de niveau recherche, publiés ou non,
+émanant des établissements d’enseignement et de"
+6cd96f2b63c6b6f33f15c0ea366e6003f512a951,A New Approach in Solving Illumination and Facial Expression Problems for Face Recognition,"A New Approach in Solving Illumination and Facial Expression Problems
+for Face Recognition
+Yee Wan Wong, Kah Phooi Seng, Li-Minn Ang
+The University of Nottingham Malaysia Campus
+Tel : 03-89248358, Fax : 03-89248017
+E-mail :
+Jalan Broga
+3500 Semenyih, Selangor"
+6c8c7065d1041146a3604cbe15c6207f486021ba,Attention Modeling for Face Recognition via Deep Learning,"Attention Modeling for Face Recognition via Deep Learning
+Sheng-hua Zhong
+Department of Computing, Hung Hom, Kowloon
+Hong Kong, 999077 CHINA
+Yan Liu
+Department of Computing, Hung Hom, Kowloon
+Hong Kong, 99907 CHINA
+Yao Zhang
+Department of Computing, Hung Hom, Kowloon
+Hong Kong, 99907 CHINA
+Fu-lai Chung
+Department of Computing, Hung Hom, Kowloon
+Hong Kong, 99907 CHINA"
+390f3d7cdf1ce127ecca65afa2e24c563e9db93b,Learning Deep Representation for Face Alignment with Auxiliary Attributes,"Learning Deep Representation for Face
+Alignment with Auxiliary Attributes
+Zhanpeng Zhang, Ping Luo, Chen Change Loy, Member, IEEE and Xiaoou Tang, Fellow, IEEE"
+39ed31ced75e6151dde41944a47b4bdf324f922b,Pose-Guided Photorealistic Face Rotation,"Pose-Guided Photorealistic Face Rotation
+Yibo Hu1,2, Xiang Wu1, Bing Yu3, Ran He1,2 ∗, Zhenan Sun1,2
+CRIPAC & NLPR & CEBSIT, CASIA 2University of Chinese Academy of Sciences
+Noah’s Ark Laboratory, Huawei Technologies Co., Ltd.
+{yibo.hu, {rhe,"
+3918b425bb9259ddff9eca33e5d47bde46bd40aa,Learning Language from Ambiguous Perceptual Context,"Copyright
+David Lieh-Chiang Chen"
+3998c5aa6be58cce8cb65a64cb168864093a9a3e,Understanding head and hand activities and coordination in naturalistic driving videos,Intelligent Vehicles Symposium 2014
+39dc2ce4cce737e78010642048b6ed1b71e8ac2f,Recognition of six basic facial expressions by feature-points tracking using RBF neural network and fuzzy inference system,"Recognition of Six Basic Facial Expressions by Feature-Points Tracking using
+RBF Neural Network and Fuzzy Inference System
+Hadi Seyedarabi*, Ali Aghagolzadeh **, Sohrab Khanmohammadi **
+*Islamic Azad University of AHAR
+**Elect. Eng. Faculty, Tabriz University, Tabriz, Iran"
+396a19e29853f31736ca171a3f40c506ef418a9f,Real World Real-time Automatic Recognition of Facial Expressions,"Real World Real-time Automatic Recognition of Facial Expressions
+Ying-li Tian Lisa Brown Arun Hampapur Sharat Pankanti Andrew Senior and Ruud Bolle
+Exploratory Computer Vision Group, IBM T. J. Watson Research Center
+PO Box 704, Yorktown Heights, NY 10598"
+39c8b34c1b678235b60b648d0b11d241a34c8e32,Learning to Deblur Images with Exemplars,"Learning to Deblur Images with Exemplars
+Jinshan Pan∗, Wenqi Ren∗, Zhe Hu∗, and Ming-Hsuan Yang"
+3986161c20c08fb4b9b791b57198b012519ea58b,An Efficient Method for Face Recognition based on Fusion of Global and Local Feature Extraction,"International Journal of Soft Computing and Engineering (IJSCE)
+ISSN: 2231-2307, Volume-4 Issue-4, September 2014
+An Efficient Method for Face Recognition based on
+Fusion of Global and Local Feature Extraction
+E. Gomathi, K. Baskaran"
+392c3cabe516c0108b478152902a9eee94f4c81e,Tiny images,"Computer Science and Artificial Intelligence Laboratory
+Technical Report
+MIT-CSAIL-TR-2007-024
+April 23, 2007
+Tiny images
+Antonio Torralba, Rob Fergus, and William T. Freeman
+m a s s a c h u s e t t s   i n s t i t u t e   o f   t e c h n o l o g y,   c a m b r i d g e ,   m a   0 213 9   u s a   —   w w w. c s a i l . m i t . e d u"
+3933e323653ff27e68c3458d245b47e3e37f52fd,Evaluation of a 3 D-aided Pose Invariant 2 D Face Recognition System,"Evaluation of a 3D-aided Pose Invariant 2D Face Recognition System
+Xiang Xu, Ha A. Le, Pengfei Dou, Yuhang Wu, Ioannis A. Kakadiaris
+{xxu18, hale4, pdou, ywu35,
+Computational Biomedicine Lab
+800 Calhoun Rd. Houston, TX, USA"
+3958db5769c927cfc2a9e4d1ee33ecfba86fe054,Describable Visual Attributes for Face Verification and Image Search,"Describable Visual Attributes for
+Face Veriﬁcation and Image Search
+Neeraj Kumar, Student Member, IEEE, Alexander C. Berg, Member, IEEE,
+Peter N. Belhumeur, and Shree K. Nayar, Member, IEEE"
+99ced8f36d66dce20d121f3a29f52d8b27a1da6c,Organizing Multimedia Data in Video Surveillance Systems Based on Face Verification with Convolutional Neural Networks,"Organizing Multimedia Data in Video
+Surveillance Systems Based on Face Veriﬁcation
+with Convolutional Neural Networks
+Anastasiia D. Sokolova, Angelina S. Kharchevnikova, Andrey V. Savchenko
+National Research University Higher School of Economics, Nizhny Novgorod, Russian
+Federation"
+994f7c469219ccce59c89badf93c0661aae34264,Model Based Face Recognition Across Facial Expressions,"Model Based Face Recognition Across Facial
+Expressions
+Zahid Riaz, Christoph Mayer, Matthias Wimmer, and Bernd Radig, Senior Member, IEEE
+screens,  embedded  into  mobiles  and  installed  into  everyday
+living  and  working  environments  they  become  valuable  tools
+for human system interaction. A particular important aspect of
+this  interaction  is  detection  and  recognition  of  faces  and
+interpretation  of  facial  expressions.  These  capabilities  are
+deeply  rooted  in  the  human  visual  system  and  a  crucial
+uilding  block  for  social  interaction.  Consequently,  these
+apabilities  are  an  important  step  towards  the  acceptance  of
+many technical systems.
+trees  as  a  classifier
+lies  not  only"
+9949ac42f39aeb7534b3478a21a31bc37fe2ffe3,Parametric Stereo for Multi-pose Face Recognition and 3D-Face Modeling,"Parametric Stereo for Multi-Pose Face Recognition and
+D-Face Modeling
+Rik Fransens, Christoph Strecha, Luc Van Gool
+PSI ESAT-KUL
+Leuven, Belgium"
+9958942a0b7832e0774708a832d8b7d1a5d287ae,The Sparse Matrix Transform for Covariance Estimation and Analysis of High Dimensional Signals,"The Sparse Matrix Transform for Covariance
+Estimation and Analysis of High Dimensional
+Signals
+Guangzhi Cao*, Member, IEEE, Leonardo R. Bachega, and Charles A. Bouman, Fellow, IEEE"
+99726ad232cef837f37914b63de70d8c5101f4e2,Facial Expression Recognition Using PCA & Distance Classifier,"International Journal of Scientific & Engineering Research, Volume 5, Issue 5, May-2014                                                                                                      570
+ISSN 2229-5518
+Facial Expression Recognition Using PCA & Distance Classifier
+AlpeshKumar Dauda*
+Dept. of Electronics & Telecomm. Engg.
+Ph.D Scholar,VSSUT
+BURLA, ODISHA, INDIA
+Nilamani Bhoi
+Reader in Dept. of Electronics & Telecomm. Engg.
+VEER SURENDRA SAI UNIVERSITY OF
+TECHNOLOGY
+BURLA, ODISHA, INDIA"
+9993f1a7cfb5b0078f339b9a6bfa341da76a3168,"A Simple, Fast and Highly-Accurate Algorithm to Recover 3D Shape from 2D Landmarks on a Single Image","JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
+A Simple, Fast and Highly-Accurate Algorithm to
+Recover 3D Shape from 2D Landmarks on a Single
+Image
+Ruiqi Zhao, Yan Wang, Aleix M. Martinez"
+992ebd81eb448d1eef846bfc416fc929beb7d28b,Exemplar-Based Face Parsing Supplementary Material,"Exemplar-Based Face Parsing
+Supplementary Material
+Brandon M. Smith Li Zhang
+Jonathan Brandt Zhe Lin Jianchao Yang
+University of Wisconsin–Madison
+Adobe Research
+http://www.cs.wisc.edu/~lizhang/projects/face-parsing/
+. Additional Selected Results
+Figures 1 and 2 supplement Figure 4 in our paper. In all cases, the input images come from our Helen [1] test set. We note
+that our algorithm generally produces accurate results, as shown in Figures 1. However, our algorithm is not perfect and makes
+mistakes on especially challenging input images, as shown in Figure 2.
+In our view, the mouth is the most challenging region of the face to segment: the shape and appearance of the lips vary
+widely from subject to subject, mouths deform signiﬁcantly, and the overall appearance of the mouth region changes depending
+on whether the inside of the mouth is visible or not. Unusual mouth expressions, like those shown in Figure 2, are not repre-
+sented well in the exemplar images, which results in poor label transfer from the top exemplars to the test image. Despite these
+hallenges, our algorithm generally performs well on the mouth, with large segmentation errors occurring infrequently.
+. Comparisons with Liu et al. [2]
+The scene parsing approach by Liu et al. [2] shares sevaral similarities with our work. Like our approach, they propose a
+nonparametric system that transfers labels from exemplars in a database to annotate a test image. This begs the question, Why
+not simply apply the approach from Liu et al. to face images?"
+99c20eb5433ed27e70881d026d1dbe378a12b342,Semi-Supervised and Unsupervised Data Extraction Targeting Speakers: From Speaker Roles to Fame?,"ISCA Archive
+http://www.isca-speech.org/archive
+First Workshop on Speech, Language
+nd Audio in Multimedia
+Marseille, France
+August 22-23, 2013
+Proceedings of the First Workshop on Speech, Language and Audio in Multimedia (SLAM), Marseille, France, August 22-23, 2013."
+9990e0b05f34b586ffccdc89de2f8b0e5d427067,Auto - Optimized Multimodal Expression Recognition Framework Using 3 D Kinect Data for ASD Therapeutic Aid,"International Journal of Modeling and Optimization, Vol. 3, No. 2, April 2013
+Auto-Optimized Multimodal Expression Recognition
+Framework Using 3D Kinect Data for ASD Therapeutic
+Amira E. Youssef, Sherin F. Aly, Ahmed S. Ibrahim, and A. Lynn Abbott
+regarding
+emotion
+recognize"
+99d7678039ad96ee29ab520ff114bb8021222a91,Political image analysis with deep neural networks,"Political image analysis with deep neural
+networks
+L. Jason Anastasopoulos∗
+Shiry Ginosar§.
+Dhruvil Badani†
+Jake Ryland Williams¶
+Crystal Lee‡
+November 28, 2017"
+52012b4ecb78f6b4b9ea496be98bcfe0944353cd,Using Support Vector Machine and Local Binary Pattern for Facial Expression Recognition,"JOURNAL OF COMPUTATION IN BIOSCIENCES AND ENGINEERING
+Journal homepage: http://scienceq.org/Journals/JCLS.php
+Research Article
+Using  Support  Vector  Machine  and  Local  Binary  Pattern  for  Facial  Expression
+Recognition
+Open Access
+Ayeni Olaniyi Abiodun 1, Alese Boniface Kayode1, Dada Olabisi Matemilayo2
+1. Department of Computer Science, Federal University Technology Akure, PMB 704, Akure, Nigeria.
+. Department of computer science, Kwara state polytechnic Ilorin, Kwara-State, Nigeria.
+. *Corresponding author:  Ayeni Olaniyi Abiodun  Mail Id:
+Received:    September 22, 2015, Accepted: December 14, 2015, Published: December 14, 2015."
+529e2ce6fb362bfce02d6d9a9e5de635bde81191,Normalization of Face Illumination Based on Large-and Small-Scale Features,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.
+> TIP-05732-2009<
+Normalization of Face Illumination Based
+on Large- and Small- Scale Features
+Xiaohua Xie, Wei-Shi Zheng, Member, IEEE, Jianhuang Lai*, Member, IEEE
+Pong C. Yuen, Member, IEEE, Ching Y. Suen, IEEE Fellow"
+52887969107956d59e1218abb84a1f834a314578,Travel Recommendation by Mining People Attributes and Travel Group Types From Community-Contributed Photos,"Travel Recommendation by Mining People
+Attributes and Travel Group Types From
+Community-Contributed Photos
+Yan-Ying Chen, An-Jung Cheng, and Winston H. Hsu, Senior Member, IEEE"
+52258ec5ec73ce30ca8bc215539c017d279517cf,Recognizing Faces with Expressions: Within-class Space and Between-class Space,"Recognizing Faces with Expressions: Within-class Space and Between-class Space
+Department of Computer Science and Engineering, Zhejang University, Hangzhou 310027,P.R.China
+Email:
+Yu  Bing      Chen  Ping      Jin  Lianfu"
+529baf1a79cca813f8c9966ceaa9b3e42748c058,Triangle wise Mapping Technique to Transform one Face Image into Another Face Image,"Triangle Wise Mapping Technique to Transform one Face Image into Another Face Image
+{tag}                                                                           {/tag}
+International Journal of Computer Applications
+© 2014 by IJCA Journal
+Volume 87 - Number 6
+Year of Publication: 2014
+Authors:
+Rustam Ali Ahmed
+Bhogeswar Borah
+10.5120/15209-3714
+{bibtex}pxc3893714.bib{/bibtex}"
+5239001571bc64de3e61be0be8985860f08d7e7e,Deep Appearance Models: A Deep Boltzmann Machine Approach for Face Modeling,"SUBMITTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, JUNE 2016
+Deep Appearance Models: A Deep Boltzmann
+Machine Approach for Face Modeling
+Chi Nhan Duong, Student, IEEE, Khoa Luu, Member, IEEE,
+Kha Gia Quach, Student, IEEE, Tien D. Bui, Senior Member, IEEE"
+554b9478fd285f2317214396e0ccd81309963efd,Spatio-Temporal Action Localization For Human Action Recognition in Large Dataset,"Spatio-Temporal Action Localization For Human Action
+Recognition in Large Dataset
+Sameh MEGRHI1, Marwa JMAL 2, Azeddine BEGHDADI1 and Wided Mseddi1,2
+L2TI, Institut Galil´ee, Universit´e Paris 13, France;
+SERCOM, Ecole Polytechnique de Tunisie"
+55c68c1237166679d2cb65f266f496d1ecd4bec6,Learning to score the figure skating sports videos,"Learning to Score Figure Skating Sport Videos
+Chengming Xu, Yanwei Fu, Zitian Chen,Bing Zhang, Yu-Gang Jiang, Xiangyang Xue"
+5502dfe47ac26e60e0fb25fc0f810cae6f5173c0,Affordance Prediction via Learned Object Attributes,"Affordance Prediction via Learned Object Attributes
+Tucker Hermans
+James M. Rehg
+Aaron Bobick"
+55a158f4e7c38fe281d06ae45eb456e05516af50,Simile Classifiers for Face Classification,"The 22nd International Conference on Computer Graphics and Vision
+GraphiCon’2012"
+5550a6df1b118a80c00a2459bae216a7e8e3966c,A perusal on Facial Emotion Recognition System ( FERS ),"ISSN: 0974-2115
+www.jchps.com                                                                       Journal of Chemical and Pharmaceutical Sciences
+A perusal on Facial Emotion Recognition System (FERS)
+School of Information Technology and Engineering, VIT University, Vellore, 632014, India
+Krithika L.B
+*Corresponding author: E-Mail:"
+55079a93b7d1eb789193d7fcdcf614e6829fad0f,Efficient and Robust Inverse Lighting of a Single Face Image Using Compressive Sensing,"Efﬁcient and Robust Inverse Lighting of a Single Face Image using Compressive
+Sensing
+Miguel Heredia Conde†, Davoud Shahlaei#, Volker Blanz# and Otmar Loffeld†
+Center for Sensor Systems† (ZESS) and Institute for Vision and Graphics#, University of Siegen
+57076 Siegen, Germany"
+551fa37e8d6d03b89d195a5c00c74cc52ff1c67a,GeThR-Net: A Generalized Temporally Hybrid Recurrent Neural Network for Multimodal Information Fusion,"GeThR-Net: A Generalized Temporally Hybrid
+Recurrent Neural Network for Multimodal
+Information Fusion
+Ankit Gandhi1 ∗, Arjun Sharma1 ∗ , Arijit Biswas2, and Om Deshmukh1
+Xerox Research Centre India; 2 Amazon Development Center India
+(*-equal contribution)"
+55c40cbcf49a0225e72d911d762c27bb1c2d14aa,Indian Face Age Database : A Database for Face Recognition with Age Variation,"Indian Face Age Database: A Database for Face Recognition with Age Variation
+{tag}                                                                  {/tag}
+International Journal of Computer Applications
+Foundation of Computer Science (FCS), NY, USA
+Volume 126
+Number 5
+Year of Publication: 2015
+Authors:
+Reecha Sharma, M.S. Patterh
+10.5120/ijca2015906055
+{bibtex}2015906055.bib{/bibtex}"
+973e3d9bc0879210c9fad145a902afca07370b86,From Emotion Recognition to Website Customizations,"(IJACSA) International Journal of Advanced Computer Science and Applications,
+Vol. 7, No. 7, 2016
+From Emotion Recognition to Website
+Customizations
+O.B.  Efremides
+School  of  Web  Media
+Bahrain  Polytechnic
+Isa  Town,  Kingdom  of  Bahrain"
+97b8249914e6b4f8757d22da51e8347995a40637,"Large-Scale Vehicle Detection, Indexing, and Search in Urban Surveillance Videos","Large-Scale Vehicle Detection, Indexing,
+nd Search in Urban Surveillance Videos
+Rogerio Schmidt Feris, Associate Member, IEEE, Behjat Siddiquie, James Petterson,
+Yun Zhai, Associate Member, IEEE, Ankur Datta, Lisa M. Brown, Senior Member, IEEE, and
+Sharath Pankanti, Fellow, IEEE"
+972ef9ddd9059079bdec17abc8b33039ed25c99c,A Novel on understanding How IRIS Recognition works,"International Journal of Innovations in Engineering and Technology (IJIET)
+A Novel on understanding How IRIS
+Recognition works
+Vijay Shinde
+Dept. of Comp. Science
+M.P.M. College, Bhopal, India
+Prof. Prakash Tanwar
+Asst. Professor CSE
+M.P.M. College, Bhopal, India"
+97032b13f1371c8a813802ade7558e816d25c73f,Total Recall Final Report,"Total Recall Final Report
+Peter Collingbourne, Nakul Durve, Khilan Gudka, Steve Lovegrove, Jiefei Ma, Sadegh Shahrbaf
+Supervisor: Professor Duncan Gillies
+January 11, 2006"
+97137d5154a9f22a5d9ecc32e8e2b95d07a5a571,Facial expression recognition based on local region specific features and support vector machines,"The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-016-3418-y
+Facial Expression Recognition based on Local Region
+Specific Features and Support Vector Machines
+Deepak Ghimire1, Sunghwan Jeong1, Joonwhoan Lee2, ♣, Sang Hyun
+Park1
+Korea Electronics Technology Institute, Jeonju-si, Jeollabuk-do 561-844, Rep. of Korea; E-
+Mails: (deepak, shjeong,
+Division of Computer Engineering, Jeonbuk National University, Jeonju-si, Jeollabuk-do 561-
+756, Rep. of Korea; E-Mail:
+♣  Corresponding Author; E-Mail:
+Tel.: +82-63-270-2406; Fax: +82-63-270-2394."
+97f9c3bdb4668f3e140ded2da33fe704fc81f3ea,An Experimental Comparison of Appearance and Geometric Model Based Recognition,"AnExperimentalComparisonofAppearance
+ndGeometricModelBasedRecognition
+J.Mundy,A.Liu,N.Pillow,A.Zisserman,S.Abdallah,S.Utcke,
+S.NayarandC.Rothwell
+GeneralElectricCorporateResearchandDevelopment,Schenectady,NY,USA
+RoboticsResearchGroup,UniversityofOxford,Oxford,UK
+Dept.ofComputerScience,ColumbiaUniversity,NY,USA
+INRIA,SophiaAntipolis,France"
+97cf04eaf1fc0ac4de0f5ad4a510d57ce12544f5,"Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond","manuscript No.
+(will be inserted by the editor)
+Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge,
+Deep Architectures, and Beyond
+Dimitrios Kollias (cid:63) · Panagiotis Tzirakis † · Mihalis A. Nicolaou ∗ · Athanasios
+Papaioannou(cid:107) · Guoying Zhao1 · Bj¨orn Schuller2 · Irene Kotsia3 · Stefanos
+Zafeiriou4"
+97d1d561362a8b6beb0fdbee28f3862fb48f1380,Age Synthesis and Estimation via Faces: A Survey,"Age Synthesis and Estimation via Faces:
+A Survey
+Yun Fu, Member, IEEE, Guodong Guo, Senior Member, IEEE, and
+Thomas S. Huang, Fellow, IEEE"
+97865d31b5e771cf4162bc9eae7de6991ceb8bbf,Face and Gender Classification in Crowd Video,"Face and Gender Classiﬁcation in Crowd Video
+Priyanka Verma
+IIIT-D-MTech-CS-GEN-13-100
+July 16, 2015
+Indraprastha Institute of Information Technology
+New Delhi
+Thesis Advisors
+Dr. Richa Singh
+Dr. Mayank Vatsa
+Submitted in partial fulﬁllment of the requirements
+for the Degree of M.Tech. in Computer Science
+(cid:13) Verma, 2015
+Keywords : Face Recognition, Gender Classiﬁcation, Crowd database"
+9755554b13103df634f9b1ef50a147dd02eab02f,How Transferable Are CNN-Based Features for Age and Gender Classification?,"How Transferable are CNN-based Features for
+Age and Gender Classification?
+Gökhan Özbulak1, Yusuf Aytar2 and Hazım Kemal Ekenel1"
+63cf5fc2ee05eb9c6613043f585dba48c5561192,Prototype Selection for Classification in Standard and Generalized Dissimilarity Spaces Prototype Selection for Classification in Standard and Generalized Dissimilarity Spaces,"Prototype Selection for
+Classiﬁcation in Standard
+nd Generalized
+Dissimilarity Spaces"
+63c109946ffd401ee1195ed28f2fb87c2159e63d,Robust Facial Feature Localization Using Improved Active Shape Model and Gabor Filter,"MVA2011 IAPR Conference on Machine Vision Applications, June 13-15, 2011, Nara, JAPAN
+Robust Facial Feature Localization using Improved Active Shape
+Model and Gabor Filter
+Hui-Yu Huang
+Engineering, National Formosa University,
+Taiwan
+E-mail:"
+631483c15641c3652377f66c8380ff684f3e365c,Sync-DRAW: Automatic GIF Generation using Deep Recurrent Attentive Architectures,"Sync-DRAW: Automatic Video Generation using Deep Recurrent
+A(cid:130)entive Architectures
+Gaurav Mi(cid:138)al∗
+Tanya Marwah∗
+IIT Hyderabad
+Vineeth N Balasubramanian
+IIT Hyderabad"
+632fa986bed53862d83918c2b71ab953fd70d6cc,What Face and Body Shapes Can Tell About Height,"GÜNEL ET AL.: WHAT FACE AND BODY SHAPES CAN TELL ABOUT HEIGHT
+What Face and Body Shapes Can Tell
+About Height
+Semih Günel
+Helge Rhodin
+Pascal Fua
+CVLab
+EPFL,
+Lausanne, Switzerland"
+63340c00896d76f4b728dbef85674d7ea8d5ab26,Discriminant Subspace Analysis: A Fukunaga-Koontz Approach,"Discriminant Subspace Analysis:
+A Fukunaga-Koontz Approach
+Sheng Zhang, Member, IEEE, and Terence Sim, Member, IEEE"
+633101e794d7b80f55f466fd2941ea24595e10e6,Face Attribute Prediction with classification CNN,"In submission to IEEE conference
+Face Attribute Prediction with classiﬁcation CNN
+FACE ATTRIBUTE PREDICTION WITH
+CLASSIFICATION CNN
+Yang Zhong
+Josephine Sullivan
+Haibo Li
+Computer Science and Communication
+KTH Royal Institute of Technology
+00 44 Stockholm, Sweden
+{yzhong, sullivan,"
+634541661d976c4b82d590ef6d1f3457d2857b19,Advanced Techniques for Face Recognition under Challenging Environments,"AAllmmaa  MMaatteerr  SSttuuddiioorruumm  ––  UUnniivveerrssiittàà  ddii  BBoollooggnnaa
+in cotutela con Università di Sassari
+DOTTORATO DI RICERCA IN
+INGEGNERIA ELETTRONICA, INFORMATICA E DELLE
+TELECOMUNICAZIONI
+Ciclo XXVI
+Settore Concorsuale di afferenza: 09/H1
+Settore Scientifico disciplinare: ING-INF/05
+ADVANCED TECHNIQUES FOR FACE RECOGNITION
+UNDER CHALLENGING ENVIRONMENTS
+TITOLO TESI
+YUNLIAN SUN
+Presentata da:
+Coordinatore Dottorato
+ALESSANDRO VANELLI-CORALLI
+Relatore
+DAVIDE MALTONI
+Relatore
+MASSIMO TISTARELLI
+Esame finale anno 2014"
+6332a99e1680db72ae1145d65fa0cccb37256828,MASTER IN COMPUTER VISION AND ARTIFICIAL INTELLIGENCE REPORT OF THE RESEARCH PROJECT OPTION: COMPUTER VISION Pose and Face Recovery via Spatio-temporal GrabCut Human Segmentation,"MASTER IN COMPUTER VISION AND ARTIFICIAL INTELLIGENCE
+REPORT OF THE RESEARCH PROJECT
+OPTION: COMPUTER VISION
+Pose and Face Recovery via
+Spatio-temporal GrabCut Human
+Segmentation
+Author: Antonio Hernández Vela
+Date: 13/07/2010
+Advisor: Sergio Escalera Guerrero"
+63488398f397b55552f484409b86d812dacde99a,Learning Universal Multi-view Age Estimator by Video Contexts,"Learning Universal Multi-view Age Estimator by Video Contexts
+Zheng Song1, Bingbing Ni3, Dong Guo4, Terence Sim2, Shuicheng Yan1
+Department of Electrical and Computer Engineering, 2 School of Computing, National University of Singapore;
+{zheng.s,
+Advanced Digital Sciences Center, Singapore; 4 Facebook"
+63c022198cf9f084fe4a94aa6b240687f21d8b41,Consensus Message Passing for Layered Graphical Models,
+0f65c91d0ed218eaa7137a0f6ad2f2d731cf8dab,Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition,"Multi-Directional Multi-Level Dual-Cross
+Patterns for Robust Face Recognition
+Changxing Ding, Jonghyun Choi, Dacheng Tao, Senior Member, IEEE, and Larry S. Davis, Fellow, IEEE"
+0f112e49240f67a2bd5aaf46f74a924129f03912,Age-Invariant Face Recognition,"Age-Invariant Face Recognition
+Unsang Park, Member, IEEE,
+Yiying Tong, Member, IEEE, and
+Anil K. Jain, Fellow, IEEE"
+0f4cfcaca8d61b1f895aa8c508d34ad89456948e,Local appearance based face recognition using discrete cosine transform,"LOCAL APPEARANCE BASED FACE RECOGNITION USING
+DISCRETE COSINE TRANSFORM  (WedPmPO4)
+Author(s) :"
+0fdcfb4197136ced766d538b9f505729a15f0daf,Multiple pattern classification by sparse subspace decomposition,"Multiple Pattern Classiﬁcation by Sparse Subspace Decomposition
+Institute of Media and Information Technology, Chiba University
+Tomoya Sakai
+-33 Yayoi, Inage, Chiba, Japan"
+0fad544edfc2cd2a127436a2126bab7ad31ec333,Decorrelating Semantic Visual Attributes by Resisting the Urge to Share,"Decorrelating Semantic Visual Attributes by Resisting the Urge to Share
+Dinesh Jayaraman
+UT Austin
+Fei Sha
+Kristen Grauman
+UT Austin"
+0fd1715da386d454b3d6571cf6d06477479f54fc,A Survey of Autonomous Human Affect Detection Methods for Social Robots Engaged in Natural HRI,"J Intell Robot Syst (2016) 82:101–133
+DOI 10.1007/s10846-015-0259-2
+A Survey of Autonomous Human Affect Detection Methods
+for Social Robots Engaged in Natural HRI
+Derek McColl · Alexander Hong ·
+Naoaki Hatakeyama · Goldie Nejat ·
+Beno Benhabib
+Received: 10 December 2014 / Accepted: 11 August 2015 / Published online: 23 August 2015
+© Springer Science+Business Media Dordrecht 2015"
+0f92e9121e9c0addc35eedbbd25d0a1faf3ab529,MORPH-II: A Proposed Subsetting Scheme,"MORPH-II: A Proposed Subsetting Scheme
+Participants: K. Kempfert, J. Fabish, K. Park, and R. Towner
+Mentors: Y. Wang, C. Chen, and T. Kling
+NSF-REU Site at UNC Wilmington, Summer 2017"
+0f0366070b46972fcb2976775b45681e62a94a26,Reliable Posterior Probability Estimation for Streaming Face Recognition,"Reliable Posterior Probability Estimation for Streaming Face Recognition
+Abhijit Bendale
+University of Colorado at Colorado Springs
+Terrance Boult
+University of Colorado at Colorado Springs"
+0ff23392e1cb62a600d10bb462d7a1f171f579d0,Toward Sparse Coding on Cosine Distance,"Toward	Sparse	Coding	on	Cosine
+Distance
+Jonghyun	Choi,	Hyunjong	Cho,	Jungsuk	Kwak#,
+Larry	S.	Davis
+UMIACS	|	University	of	Maryland,	College	Park
+#Stanford	University"
+0f395a49ff6cbc7e796656040dbf446a40e300aa,The Change of Expression Configuration Affects Identity-Dependent Expression Aftereffect but Not Identity-Independent Expression Aftereffect,"ORIGINAL RESEARCH
+published: 22 December 2015
+doi: 10.3389/fpsyg.2015.01937
+The Change of Expression
+Conﬁguration Affects
+Identity-Dependent Expression
+Aftereffect but Not
+Identity-Independent Expression
+Aftereffect
+Miao Song 1, 2*, Keizo Shinomori 2, Qian Qian 3, Jun Yin 1 and Weiming Zeng 1
+College of Information Engineering, Shanghai Maritime University, Shanghai, China, 2 School of Information, Kochi University
+of Technology, Kochi, Japan, 3 Yunnan Key Laboratory of Computer Technology Applications, Kunming University of Science
+nd Technology, Kunming, China
+The present study examined the influence of expression conﬁguration on cross-identity
+expression aftereffect. The expression conﬁguration refers to the spatial arrangement
+of facial features in a face for conveying an emotion, e.g., an open-mouth smile vs.
+closed-mouth smile. In the ﬁrst of two experiments, the expression aftereffect is
+measured using a cross-identity/cross-expression conﬁguration factorial design. The
+facial
+identities of test faces were the same or different from the adaptor, while"
+0fd1bffb171699a968c700f206665b2f8837d953,Weakly Supervised Object Localization with Multi-Fold Multiple Instance Learning,"Weakly Supervised Object Localization with
+Multi-fold Multiple Instance Learning
+Ramazan Gokberk Cinbis, Jakob Verbeek, and Cordelia Schmid, Fellow, IEEE"
+0a6d344112b5af7d1abbd712f83c0d70105211d0,Constrained Local Neural Fields for Robust Facial Landmark Detection in the Wild,"Constrained Local Neural Fields for robust facial landmark detection in the wild
+Tadas Baltruˇsaitis
+Peter Robinson
+University of Cambridge Computer Laboratory
+USC Institute for Creative Technologies
+5 JJ Thomson Avenue
+Louis-Philippe Morency
+2015 Waterfront Drive"
+0a3863a0915256082aee613ba6dab6ede962cdcd,Early and Reliable Event Detection Using Proximity Space Representation,"Early and Reliable Event Detection Using Proximity Space Representation
+Maxime Sangnier
+LTCI, CNRS, T´el´ecom ParisTech, Universit´e Paris-Saclay, 75013, Paris, France
+J´erˆome Gauthier
+LADIS, CEA, LIST, 91191, Gif-sur-Yvette, France
+Alain Rakotomamonjy
+Normandie Universit´e, UR, LITIS EA 4108, Avenue de l’universit´e, 76801, Saint-Etienne-du-Rouvray, France"
+0a60d9d62620e4f9bb3596ab7bb37afef0a90a4f,Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates,"Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates. GCPR 2016
+(cid:13) Copyright by Springer. The final publication will be available at link.springer.com
+A. Freytag, E. Rodner, M. Simon, A. Loos, H. K¨uhl and J. Denzler
+Chimpanzee Faces in the Wild:
+Log-Euclidean CNNs for Predicting Identities
+nd Attributes of Primates
+Alexander Freytag1,2, Erik Rodner1,2, Marcel Simon1, Alexander Loos3,
+Hjalmar S. K¨uhl4,5, and Joachim Denzler1,2,5
+Computer Vision Group, Friedrich Schiller University Jena, Germany
+Michael Stifel Center Jena, Germany
+Fraunhofer Institute for Digital Media Technology, Germany
+Max Planck Institute for Evolutionary Anthropology, Germany
+5German Centre for Integrative Biodiversity Research (iDiv), Germany"
+0aa9872daf2876db8d8e5d6197c1ce0f8efee4b7,Timing is everything : a spatio-temporal approach to the analysis of facial actions,"Imperial College of Science, Technology and Medicine
+Department of Computing
+Timing is everything
+A spatio-temporal approach to the analysis of facial
+ctions
+Michel Fran¸cois Valstar
+Submitted in part fulﬁlment of the requirements for the degree of
+Doctor of Philosophy in Computing of Imperial College, February 2008"
+0a87d781fe2ae2e700237ddd00314dbc10b1429c,Multi-scale HOG Prescreening Algorithm for Detection of Buried Explosive Hazards in FL-IR and FL-GPR Data,"Distribution Statement A:  Approved for public release; distribution unlimited.
+Multi-scale HOG Prescreening Algorithm for Detection of Buried
+Explosive Hazards in FL-IR and FL-GPR Data
+*University of Missouri, Electrical and Computer Engineering Department, Columbia, MO
+K. Stone*, J. M. Keller*, D. Shaw*"
+0af48a45e723f99b712a8ce97d7826002fe4d5a5,Toward Wide-Angle Microvision Sensors,"Toward Wide-Angle Microvision Sensors
+Sanjeev J. Koppal, Member, IEEE, Ioannis Gkioulekas, Student Member, IEEE,
+Travis Young, Member, IEEE, Hyunsung Park, Student Member, IEEE,
+Kenneth B. Crozier, Member, IEEE, Geoffrey L. Barrows, Member, IEEE, and
+Todd Zickler, Member, IEEE"
+0aa8a0203e5f406feb1815f9b3dd49907f5fd05b,Mixture Subclass Discriminant Analysis,"Mixture subclass discriminant analysis
+Nikolaos Gkalelis, Vasileios Mezaris, Ioannis Kompatsiaris"
+0a7309147d777c2f20f780a696efe743520aa2db,Stories for Images-in-Sequence by using Visual and Narrative Components,"Stories for Images-in-Sequence by using Visual
+nd Narrative Components (cid:63)
+Marko Smilevski1,2, Ilija Lalkovski2, and Gjorgji Madjarov1,3
+Ss. Cyril and Methodius University, Skopje, Macedonia
+Pendulibrium, Skopje, Macedonia
+Elevate Global, Skopje, Macedonia"
+0a1138276c52c734b67b30de0bf3f76b0351f097,Discriminant Incoherent Component Analysis,"This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.
+The final version of record is available at
+http://dx.doi.org/10.1109/TIP.2016.2539502
+Discriminant Incoherent Component Analysis
+Christos Georgakis, Student Member, IEEE, Yannis Panagakis, Member, IEEE, and Maja Pantic, Fellow, IEEE"
+0a6a25ee84fc0bf7284f41eaa6fefaa58b5b329a,Neural Networks Regularization Through Representation Learning,"THÈSEPour obtenir le diplôme de doctorat Spécialité Informatique Préparée au sein de « l'INSA Rouen Normandie » Présentée et soutenue parSoufiane BELHARBIThèse dirigée par Sébastien ADAM, laboratoire LITIS Neural Networks Regularization Through Representation LearningThèse soutenue publiquement le 06 Juillet 2018 devant le jury composé deSébastien ADAMProfesseur à l'Université de Rouen NormandieDirecteur de thèseClément CHATELAINMaître de conférence à l'INSA  Rouen NormandieEncadrant de thèseRomain HÉRAULTMaître de conférence à l'INSA  Rouen NormandieEncadrant de thèseElisa FROMONTProfesseur à l'Université de Rennes 1Rapporteur de thèseThierry ARTIÈRESProfesseur à l'École Centrale MarseilleRapporteur de thèseJohn LEEProfesseur à l'Université Catholique de LouvainExaminateur de thèseDavid PICARDMaître de conférences à l'École Nationale Supérieure de l'Électronique et de ses ApplicationsExaminateur de thèseFrédéric JURIEProfesseur à l' Université de Caen NormandieInvité"
+0ae9cc6a06cfd03d95eee4eca9ed77b818b59cb7,"Multi-task, multi-label and multi-domain learning with residual convolutional networks for emotion recognition","Noname manuscript No.
+(will be inserted by the editor)
+Multi-task, multi-label and multi-domain learning with
+residual convolutional networks for emotion recognition
+Gerard Pons · David Masip
+Received: date / Accepted: date"
+0acf23485ded5cb9cd249d1e4972119239227ddb,Dual coordinate solvers for large-scale structural SVMs,"Dual coordinate solvers for large-scale structural SVMs
+Deva Ramanan
+UC Irvine
+This manuscript describes a method for training linear SVMs (including binary SVMs, SVM regression,
+nd structural SVMs) from large, out-of-core training datasets. Current strategies for large-scale learning fall
+into one of two camps; batch algorithms which solve the learning problem given a ﬁnite datasets, and online
+lgorithms which can process out-of-core datasets. The former typically requires datasets small enough to ﬁt
+in memory. The latter is often phrased as a stochastic optimization problem [4, 15]; such algorithms enjoy
+strong theoretical properties but often require manual tuned annealing schedules, and may converge slowly
+for problems with large output spaces (e.g., structural SVMs). We discuss an algorithm for an “intermediate”
+regime in which the data is too large to ﬁt in memory, but the active constraints (support vectors) are small
+enough to remain in memory.
+In this case, one can design rather ef‌f‌icient learning algorithms that are
+s stable as batch algorithms, but capable of processing out-of-core datasets. We have developed such a
+MATLAB-based solver and used it to train a series of recognition systems [19, 7, 21, 12] for articulated pose
+estimation, facial analysis, 3D object recognition, and action classiﬁcation, all with publicly-available code.
+This writeup describes the solver in detail.
+Approach: Our approach is closely based on data-subsampling algorithms for collecting hard exam-
+ples [9, 10, 6], combined with the dual coordinate quadratic programming (QP) solver described in liblinear
+[8]. The latter appears to be current fastest method for learning linear SVMs. We make two extensions (1)"
+6412d8bbcc01f595a2982d6141e4b93e7e982d0f,"Deep Convolutional Neural Network Using Triplets of Faces, Deep Ensemble, and Score-Level Fusion for Face Recognition","Deep Convolutional Neural Network using Triplets of Faces, Deep Ensemble, and
+Score-level Fusion for Face Recognition
+Bong-Nam Kang, Student Member, IEEE1, Yonghyun Kim, Student Member, IEEE2, and
+Daijin Kim, Member, IEEE2
+Department of Creative IT Engineering, POSTECH, Korea
+Department of Computer Science and Engineering, POSTECH, Korea
+{bnkang, gkyh0805,"
+641f0989b87bf7db67a64900dcc9568767b7b50f,Reconstructing faces from their signatures using RBF regression,"Reconstructing Faces from their Signatures using RBF
+Regression
+Alexis Mignon, Fr´ed´eric Jurie
+To cite this version:
+Alexis Mignon, Fr´ed´eric Jurie. Reconstructing Faces from their Signatures using RBF Regres-
+sion. British Machine Vision Conference 2013, Sep 2013, Bristol, United Kingdom. pp.103.1–
+03.12, 2013, <10.5244/C.27.103>. <hal-00943426>
+HAL Id: hal-00943426
+https://hal.archives-ouvertes.fr/hal-00943426
+Submitted on 13 Feb 2014
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entiﬁc research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destin´ee au d´epˆot et `a la diffusion de documents
+scientiﬁques de niveau recherche, publi´es ou non,
+´emanant des ´etablissements d’enseignement et de"
+64153df77fe137b7c6f820a58f0bdb4b3b1a879b,Shape Invariant Recognition of Segmented Human Faces using Eigenfaces,"Shape Invariant Recognition of Segmented Human
+Faces using Eigenfaces
+Zahid Riaz, Michael Beetz, Bernd Radig
+Department of Informatics
+Technical University of Munich, Germany"
+649eb674fc963ce25e4e8ce53ac7ee20500fb0e3,Toward correlating and solving abstract tasks using convolutional neural networks,
+645de797f936cb19c1b8dba3b862543645510544,Deep Temporal Linear Encoding Networks,"Deep Temporal Linear Encoding Networks
+Ali Diba1,(cid:63), Vivek Sharma1,(cid:63), and Luc Van Gool1,2
+ESAT-PSI, KU Leuven, 2CVL, ETH Z¨urich"
+90d735cffd84e8f2ae4d0c9493590f3a7d99daf1,Recognition of Faces using Efficient Multiscale Local Binary Pattern and Kernel Discriminant Analysis in Varying Environment,"Original Research Paper
+American Journal of Engineering and Applied Sciences
+Recognition of Faces using Efficient Multiscale Local Binary
+Pattern and Kernel Discriminant Analysis in Varying
+Environment
+Sujata G. Bhele and
+V.H. Mankar
+Department of Electronics Engg, Priyadarshini College of Engg, Nagpur, India
+Department of Electronics Engg, Government Polytechnic, Nagpur, India
+Article history
+Received: 20-06-2017
+Revised: 18-07-2017
+Accepted: 21-08-2017
+Corresponding Author:
+Sujata G. Bhele
+Department of Electronics
+Engg, Priyadarshini College of
+Engg, Nagpur, India
+Email:"
+90fb58eeb32f15f795030c112f5a9b1655ba3624,Face and Iris Recognition in a Video Sequence Using Dbpnn and Adaptive Hamming Distance,"INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND ROBOTICS
+www.ijrcar.com
+Vol.4 Issue 6, Pg.: 12-27
+June 2016
+INTERNATIONAL JOURNAL OF
+RESEARCH IN COMPUTER
+APPLICATIONS AND ROBOTICS
+ISSN 2320-7345
+FACE AND IRIS RECOGNITION IN A
+VIDEO SEQUENCE USING DBPNN AND
+ADAPTIVE HAMMING DISTANCE
+S. Revathy, 2Mr. L. Ramasethu
+PG Scholar, Hindusthan College of Engineering and Technology, Coimbatore, India.
+Assistant Professor, Hindusthan College of Engineering and Technology, Coimbatore, India.
+Email id:"
+90cb074a19c5e7d92a1c0d328a1ade1295f4f311,Fully Automatic Upper Facial Action Recognition,"MIT. Media Laboratory Affective Computing Technical Report #571
+Appears in IEEE International Workshop on Analysis and Modeling of Faces and Gestures , Oct 2003
+Fully Automatic Upper Facial Action Recognition
+Ashish Kapoor Yuan Qi Rosalind W. Picard
+MIT Media Laboratory
+Cambridge, MA 02139"
+907475a4febf3f1d4089a3e775ea018fbec895fe,Statistical modeling for facial expression analysis and synthesis,"STATISTICAL MODELING FOR FACIAL EXPRESSION ANALYSIS AND SYNTHESIS
+Bouchra Abboud, Franck Davoine, Mˆo Dang
+Heudiasyc Laboratory, CNRS, University of Technology of Compi`egne.
+BP 20529, 60205 COMPIEGNE Cedex, FRANCE.
+E-mail:"
+9028fbbd1727215010a5e09bc5758492211dec19,Solving the Uncalibrated Photometric Stereo Problem Using Total Variation,"Solving the Uncalibrated Photometric Stereo
+Problem using Total Variation
+Yvain Qu´eau1, Fran¸cois Lauze2, and Jean-Denis Durou1
+IRIT, UMR CNRS 5505, Toulouse, France
+Dept. of Computer Science, Univ. of Copenhagen, Denmark"
+bff77a3b80f40cefe79550bf9e220fb82a74c084,Facial Expression Recognition Based on Local Binary Patterns and Local Fisher Discriminant Analysis,"Facial Expression Recognition Based on Local Binary Patterns and
+Local Fisher Discriminant Analysis
+SHIQING ZHANG 1, XIAOMING ZHAO 2, BICHENG LEI 1
+School of Physics and Electronic Engineering
+Taizhou University
+Taizhou 318000
+CHINA
+2Department of Computer Science
+Taizhou University
+Taizhou 318000
+CHINA"
+bf1e0279a13903e1d43f8562aaf41444afca4fdc,Different Viewpoints of Recognizing Fleeting Facial Expressions with DWT,"International Research Journal of Engineering and Technology (IRJET)       e-ISSN: 2395-0056
+Volume: 04 Issue: 10 | Oct -2017                     www.irjet.net                                                                 p-ISSN: 2395-0072
+Different Viewpoints of Recognizing Fleeting Facial Expressions with
+VAIBHAV SHUBHAM1, MR. SANJEEV SHRIVASTAVA2, DR. MOHIT GANGWAR3
+information
+to  get  desired
+information
+Introduction
+---------------------------------------------------------------------***---------------------------------------------------------------------"
+bf5940d57f97ed20c50278a81e901ae4656f0f2c,Query-Free Clothing Retrieval via Implicit Relevance Feedback,"Query-free Clothing Retrieval via Implicit
+Relevance Feedback
+Zhuoxiang Chen, Zhe Xu, Ya Zhang, Member, IEEE, and Xiao Gu"
+bfb98423941e51e3cd067cb085ebfa3087f3bfbe,Sparseness helps: Sparsity Augmented Collaborative Representation for Classification,"Sparseness helps: Sparsity Augmented
+Collaborative Representation for Classiﬁcation
+Naveed Akhtar, Faisal Shafait, and Ajmal Mian"
+d3b73e06d19da6b457924269bb208878160059da,Implementation of an Automated Smart Home Control for Detecting Human Emotions via Facial Detection,"Proceedings of the 5th International Conference on Computing and Informatics, ICOCI 2015
+1-13 August, 2015 Istanbul, Turkey. Universiti Utara Malaysia (http://www.uum.edu.my )
+Paper No.
+IMPLEMENTATION OF AN AUTOMATED SMART HOME
+CONTROL FOR DETECTING HUMAN EMOTIONS VIA FACIAL
+DETECTION
+Lim Teck Boon1, Mohd Heikal Husin2, Zarul Fitri Zaaba3 and Mohd Azam
+Osman4
+Universiti Sains Malaysia, Malaysia,
+Universiti Sains Malaysia, Malaysia,
+Universiti Sains Malaysia, Malaysia,
+Universiti Sains Malaysia, Malaysia,"
+d3d71a110f26872c69cf25df70043f7615edcf92,Learning Compact Feature Descriptor and Adaptive Matching Framework for Face Recognition,"Learning Compact Feature Descriptor and Adaptive
+Matching Framework for Face Recognition
+Zhifeng Li, Senior Member, IEEE, Dihong Gong, Xuelong Li, Fellow, IEEE, and Dacheng Tao, Fellow, IEEE
+improvements"
+d3b18ba0d9b247bfa2fb95543d172ef888dfff95,Learning and Using the Arrow of Time,"Learning and Using the Arrow of Time
+Donglai Wei1, Joseph Lim2, Andrew Zisserman3 and William T. Freeman4,5
+Harvard University 2University of Southern California
+University of Oxford 4Massachusetts Institute of Technology 5Google Research
+Figure 1: Seeing these ordered frames from videos, can you tell whether each video is playing forward or backward? (answer
+elow1). Depending on the video, solving the task may require (a) low-level understanding (e.g. physics), (b) high-level
+reasoning (e.g. semantics), or (c) familiarity with very subtle effects or with (d) camera conventions. In this work, we learn
+nd exploit several types of knowledge to predict the arrow of time automatically with neural network models trained on
+large-scale video datasets."
+d309e414f0d6e56e7ba45736d28ee58ae2bad478,Efficient Two-Stream Motion and Appearance 3 D CNNs for Video Classification,"Efﬁcient Two-Stream Motion and Appearance 3D CNNs for
+Video Classiﬁcation
+Ali Diba
+ESAT-KU Leuven
+Ali Pazandeh
+Sharif UTech
+Luc Van Gool
+ESAT-KU Leuven, ETH Zurich"
+d3f5a1848b0028d8ab51d0b0673732cad2e3c8c9,STAIR Actions: A Video Dataset of Everyday Home Actions,
+d3c004125c71942846a9b32ae565c5216c068d1e,Recognizing Age-Separated Face Images: Humans and Machines,"RESEARCH ARTICLE
+Recognizing Age-Separated Face Images:
+Humans and Machines
+Daksha Yadav1, Richa Singh2, Mayank Vatsa2*, Afzel Noore1
+. West Virginia University, Morgantown, West Virginia, United States of America, 2. IIIT Delhi, New Delhi,
+Delhi, India"
+d350a9390f0818703f886138da27bf8967fe8f51,Lighting design for portraits with a virtual light stage,"LIGHTING DESIGN FOR PORTRAITS WITH A VIRTUAL LIGHT STAGE
+Davoud Shahlaei, Marcel Piotraschke, Volker Blanz
+Institute for Vision and Graphics, University of Siegen, Germany"
+d33fcdaf2c0bd0100ec94b2c437dccdacec66476,Neurons With Paraboloid Decision Boundaries for Improved Neural Network Classification Performance.,"Neurons with Paraboloid Decision Boundaries for
+Improved Neural Network Classiﬁcation
+Performance
+Nikolaos Tsapanos, Anastasios Tefas, Member, IEEE, Nikolaos Nikolaidis, Member, IEEE, and
+Ioannis Pitas, Fellow, IEEE"
+d46b790d22cb59df87f9486da28386b0f99339d3,Learning Face Deblurring Fast and Wide,"Learning Face Deblurring Fast and Wide
+Meiguang Jin
+University of Bern
+Switzerland
+Michael Hirsch†
+Amazon Research
+Germany
+Paolo Favaro
+University of Bern
+Switzerland"
+d41c11ebcb06c82b7055e2964914b9af417abfb2,CDI-Type I: Unsupervised and Weakly-Supervised Discovery of Facial Events,"CDI-Type I: Unsupervised and Weakly-Supervised
+Introduction
+Discovery of Facial Events
+The face is one of the most powerful channels of nonverbal communication. Facial expression has been a
+focus of emotion research for over a hundred years [12]. It is central to several leading theories of emotion
+[18, 31, 54] and has been the focus of at times heated debate about issues in emotion science [19, 24, 50].
+Facial expression ﬁgures prominently in research on almost every aspect of emotion, including psychophys-
+iology [40], neural correlates [20], development [11], perception [4], addiction [26], social processes [30],
+depression [49] and other emotion disorders [55], to name a few. In general, facial expression provides cues
+bout emotional response, regulates interpersonal behavior, and communicates aspects of psychopathology.
+Because of its importance to behavioral science and the emerging ﬁelds of computational behavior
+science, perceptual computing, and human-robot interaction, signiﬁcant efforts have been applied toward
+developing algorithms that automatically detect facial expression. With few exceptions, previous work on
+facial expression relies on supervised approaches to learning (i.e. event categories are deﬁned in advance
+in labeled training data). While supervised learning has important advantages, two critical limitations may
+e noted. One, because labeling facial expression is highly labor intensive, progress in automated facial
+expression recognition and analysis is slowed. For the most detailed and comprehensive labeling or coding
+systems, such as Facial Action Coding System (FACS), three to four months is typically required to train
+coder (’coding’ refers to the labeling of video using behavioral descriptors). Once trained, each minute
+of video may require 1 hour or more to code [9]. No wonder relatively few databases are yet available,"
+d444368421f456baf8c3cb089244e017f8d32c41,CNN for IMU assisted odometry estimation using velodyne LiDAR,"CNN for IMU Assisted Odometry Estimation using Velodyne LiDAR
+Martin Velas, Michal Spanel, Michal Hradis, and Adam Herout"
+d4885ca24189b4414031ca048a8b7eb2c9ac646c,"Efficient Facial Representations for Age, Gender and Identity Recognition in Organizing Photo Albums using Multi-output CNN","Ef‌f‌icient Facial Representations for Age, Gender
+nd Identity Recognition in Organizing Photo
+Albums using Multi-output CNN
+Andrey V. Savchenko
+Samsung-PDMI Joint AI Center, St. Petersburg Department of Steklov Institute of
+Mathematics
+National Research University Higher School of Economics
+Nizhny Novgorod, Russia"
+d4001826cc6171c821281e2771af3a36dd01ffc0,Modélisation de contextes pour l'annotation sémantique de vidéos. (Context based modeling for video semantic annotation),"Modélisation de contextes pour l’annotation sémantique
+de vidéos
+Nicolas Ballas
+To cite this version:
+Nicolas Ballas. Modélisation de contextes pour l’annotation sémantique de vidéos. Autre [cs.OH].
+Ecole Nationale Supérieure des Mines de Paris, 2013. Français. <NNT : 2013ENMP0051>. <pastel-
+00958135>
+HAL Id: pastel-00958135
+https://pastel.archives-ouvertes.fr/pastel-00958135
+Submitted on 11 Mar 2014
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entific research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destinée au dépôt et à la diffusion de documents
+scientifiques de niveau recherche, publiés ou non,
+émanant des établissements d’enseignement et de"
+d458c49a5e34263c95b3393386b5d76ba770e497,A Comparative Analysis of Gender Classification Techniques,"Middle-East Journal of Scientific Research 20 (1): 01-13, 2014
+ISSN 1990-9233
+© IDOSI Publications, 2014
+DOI: 10.5829/idosi.mejsr.2014.20.01.11434
+A Comparative Analysis of Gender Classification Techniques
+Sajid Ali Khan, Maqsood Ahmad, Muhammad Nazir and Naveed Riaz
+Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad, Pakistan"
+d4e669d5d35fa0ca9f8d9a193c82d4153f5ffc4e,A Lightened CNN for Deep Face Representation,"A Lightened CNN for Deep Face Representation
+Xiang Wu
+School of Computer and Communication Engineering
+University of Science and Technology Beijing, Beijing, China
+Ran He, Zhenan Sun
+National Laboratory of Pattern Recognition
+Institute of Automation Chinese Academy of Sciences, Beijing, China
+{rhe,"
+d4b88be6ce77164f5eea1ed2b16b985c0670463a,A Survey of Different 3D Face Reconstruction Methods,"TECHNICAL REPORT JAN.15.2016
+A Survey of Different 3D Face Reconstruction
+Methods
+Amin Jourabloo
+Department of Computer Science and Engineering"
+d44ca9e7690b88e813021e67b855d871cdb5022f,"Selecting, Optimizing and Fusing 'Salient' Gabor Features for Facial Expression Recognition","QUT Digital Repository:
+http://eprints.qut.edu.au/
+Zhang, Ligang and Tjondronegoro, Dian W. (2009) Selecting, optimizing and
+fusing ‘salient’ Gabor features for facial expression recognition. In: Neural
+Information Processing (Lecture Notes in Computer Science), 1-5 December
+009, Hotel Windsor Suites Bangkok, Bangkok.
+©  Copyright 2009 Springer-Verlag GmbH Berlin Heidelberg"
+bafb8812817db7445fe0e1362410a372578ec1fc,Image-Quality-Based Adaptive Face Recognition,"Image-Quality-Based Adaptive Face Recognition
+Harin Sellahewa and Sabah A. Jassim"
+ba99c37a9220e08e1186f21cab11956d3f4fccc2,A Fast Factorization-Based Approach to Robust PCA,"A Fast Factorization-based Approach to Robust PCA
+Department of Computer Science, Southern Illinois University,Carbondale, IL 62901 USA
+Chong Peng, Zhao Kang, and Qiang Cheng
+Email:"
+ba816806adad2030e1939450226c8647105e101c,MindLAB at the THUMOS Challenge,"MindLAB at the THUMOS Challenge
+Fabi´an P´aez
+Jorge A. Vanegas
+Fabio A. Gonz´alez
+MindLAB Research Group
+MindLAB Research Group
+MindLAB Research Group
+Bogot´a, Colombia
+Bogot´a, Colombia
+Bogot´a, Colombia"
+badcd992266c6813063c153c41b87babc0ba36a3,Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks,"Recent Advances in Object Detection in the Age
+of Deep Convolutional Neural Networks
+Shivang Agarwal(∗
+,1), Jean Ogier du Terrail(∗
+,1,2), Fr´ed´eric Jurie(1)
+(∗) equal contribution
+(1)Normandie Univ, UNICAEN, ENSICAEN, CNRS
+(2)Safran Electronics and Defense
+September 11, 2018"
+ba8a99d35aee2c4e5e8a40abfdd37813bfdd0906,Uporaba emotivno pogojenega računalništva v priporočilnih sistemih,"ELEKTROTEHNI ˇSKI VESTNIK 78(1-2): 12–17, 2011
+EXISTING SEPARATE ENGLISH EDITION
+Uporaba emotivno pogojenega raˇcunalniˇstva v
+priporoˇcilnih sistemih
+Marko Tkalˇciˇc, Andrej Koˇsir, Jurij Tasiˇc
+Univerza v Ljubljani, Fakulteta za elektrotehniko, Trˇzaˇska 25, 1000 Ljubljana, Slovenija
+Univerza v Ljubljani, Fakulteta za raˇcunalniˇstvo in informatiko, Trˇzaˇska 25, 1000 Ljubljana, Slovenija
+E-poˇsta:
+Povzetek. V ˇclanku predstavljamo rezultate treh raziskav, vezanih na izboljˇsanje delovanja multimedijskih
+priporoˇcilnih sistemov s pomoˇcjo metod emotivno pogojenega raˇcunalniˇstva (ang. affective computing).
+Vsebinski priporoˇcilni sistem smo izboljˇsali s pomoˇcjo metapodatkov, ki opisujejo emotivne odzive uporabnikov.
+Pri skupinskem priporoˇcilnem sistemu smo dosegli znaˇcilno izboljˇsanje v obmoˇcju hladnega zagona z uvedbo
+nove mere podobnosti, ki temelji na osebnostnem modelu velikih pet (ang. ﬁve factor model). Razvili smo tudi
+sistem za neinvazivno oznaˇcevanje vsebin z emotivnimi parametri, ki pa ˇse ni zrel za uporabo v priporoˇcilnih
+sistemih.
+Kljuˇcne besede: priporoˇcilni sistemi, emotivno pogojeno raˇcunalniˇstvo, strojno uˇcenje, uporabniˇski proﬁl,
+emocije
+Uporaba emotivnega raˇcunalniˇstva v priporoˇcilnih
+sistemih
+In this paper we present the results of three investigations of"
+badd371a49d2c4126df95120902a34f4bee01b00,Parallel Separable 3D Convolution for Video and Volumetric Data Understanding,"GONDA, WEI, PARAG, PFISTER: PARALLEL SEPARABLE 3D CONVOLUTION
+Parallel Separable 3D Convolution for Video
+nd Volumetric Data Understanding
+Harvard John A. Paulson School of
+Engineering and Applied Sciences
+Camabridge MA, USA
+Felix Gonda
+Donglai Wei
+Touﬁq Parag
+Hanspeter Pﬁster"
+a0f94e9400938cbd05c4b60b06d9ed58c3458303,Value-Directed Human Behavior Analysis from Video Using Partially Observable Markov Decision Processes,"Value-Directed Human Behavior Analysis
+from Video Using Partially Observable
+Markov Decision Processes
+Jesse Hoey and James J. Little, Member, IEEE"
+a022eff5470c3446aca683eae9c18319fd2406d5,Deep learning for semantic description of visual human traits. (Apprentissage profond pour la description sémantique des traits visuels humains),"017-ENST-0071
+EDITE - ED 130
+Doctorat ParisTech
+T H È S E
+pour obtenir le grade de docteur délivré par
+TÉLÉCOM ParisTech
+Spécialité « SIGNAL et IMAGES »
+présentée et soutenue publiquement par
+Grigory ANTIPOV
+le 15 décembre 2017
+Apprentissage Profond pour la Description Sémantique des Traits
+Visuels Humains
+Directeur de thèse : Jean-Luc DUGELAY
+Co-encadrement de la thèse : Moez BACCOUCHE
+Mme Bernadette DORIZZI, PRU, Télécom SudParis
+Mme Jenny BENOIS-PINEAU, PRU, Université de Bordeaux
+M. Christian WOLF, MC/HDR, INSA de Lyon
+M. Patrick PEREZ, Chercheur/HDR, Technicolor Rennes
+M. Moez BACCOUCHE, Chercheur/Docteur, Orange Labs Rennes
+M. Jean-Luc DUGELAY, PRU, Eurecom Sophia Antipolis"
+a0c37f07710184597befaa7e6cf2f0893ff440e9,Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning,
+a0fd85b3400c7b3e11122f44dc5870ae2de9009a,Learning Deep Representation for Face Alignment with Auxiliary Attributes,"Learning Deep Representation for Face
+Alignment with Auxiliary Attributes
+Zhanpeng Zhang, Ping Luo, Chen Change Loy, Member, IEEE and Xiaoou Tang, Fellow, IEEE"
+a0dfb8aae58bd757b801e2dcb717a094013bc178,Reconocimiento de expresiones faciales con base en la dinámica de puntos de referencia faciales,"Reconocimiento de expresiones faciales con base
+en la din´amica de puntos de referencia faciales
+E. Morales-Vargas, C.A. Reyes-Garcia, Hayde Peregrina-Barreto
+Instituto Nacional de Astrof´ısica ´Optica y Electr´onica,
+Divisi´on de Ciencias Computacionales, Tonantzintla, Puebla,
+M´exico
+Resumen. Las expresiones faciales permiten a las personas comunicar
+emociones, y es pr´acticamente lo primero que observamos al interactuar
+on alguien. En el ´area de computaci´on, el reconocimiento de expresiones
+faciales es importante debido a que su an´alisis tiene aplicaci´on directa en
+´areas como psicolog´ıa, medicina, educaci´on, entre otras. En este articulo
+se presenta el proceso de dise˜no de un sistema para el reconocimiento de
+expresiones faciales utilizando la din´amica de puntos de referencia ubi-
+ados en el rostro, su implementaci´on, experimentos realizados y algunos
+de los resultados obtenidos hasta el momento.
+Palabras clave: Expresiones faciales, clasiﬁcaci´on, m´aquinas de soporte
+vectorial,modelos activos de apariencia.
+Facial Expressions Recognition Based on Facial
+Landmarks Dynamics"
+a0aa32bb7f406693217fba6dcd4aeb6c4d5a479b,Cascaded Regressor based 3D Face Reconstruction from a Single Arbitrary View Image,"Cascaded Regressor based 3D Face Reconstruction
+from a Single Arbitrary View Image
+Feng Liu, Dan Zeng, Jing Li, Qijun Zhao
+College of Computer Science, Sichuan University, Chengdu, China"
+a03cfd5c0059825c87d51f5dbf12f8a76fe9ff60,Simultaneous Learning and Alignment: Multi-Instance and Multi-Pose Learning,"Simultaneous Learning and Alignment:
+Multi-Instance and Multi-Pose Learning?
+Boris Babenko1 Piotr Doll´ar1,2
+Zhuowen Tu3
+Serge Belongie1,2
+Comp. Science & Eng.
+Univ. of CA, San Diego
+Electrical Engineering
+California Inst. of Tech.
+Lab of Neuro Imaging
+Univ. of CA, Los Angeles"
+a090d61bfb2c3f380c01c0774ea17929998e0c96,On the dimensionality of video bricks under varying illumination,"On the Dimensionality of Video Bricks under Varying Illumination
+Beijing Lab of Intelligent Information Technology, School of Computer Science,
+Youdong Zhao, Xi Song, Yunde Jia
+Beijing Institute of Technology, Beijing 100081, PR China
+{zyd458, songxi,"
+a000149e83b09d17e18ed9184155be140ae1266e,Action Recognition in Realistic Sports Videos,"Chapter 9
+Action Recognition in Realistic
+Sports Videos
+Khurram Soomro and Amir R. Zamir"
+a01f9461bc8cf8fe40c26d223ab1abea5d8e2812,Facial Age Estimation Through the Fusion of Texture and Local Appearance Descriptors,"Facial Age Estimation Through the Fusion of Texture
+nd local appearance Descriptors
+Ivan Huerta1, Carles Fern´andez2, and Andrea Prati1
+DPDCE, University IUAV, Santa Croce 1957, 30135 Venice, Italy
+Herta Security, Pau Claris 165 4-B, 08037 Barcelona, Spain"
+a702fc36f0644a958c08de169b763b9927c175eb,Facial expression recognition using Hough forest,"FACIAL EXPRESSION RECOGNITION USING HOUGH FOREST
+Chi-Ting Hsu1, Shih-Chung Hsu1, and Chung-Lin Huang1,2
+.  Department of Electrical Engineering, National Tsing-Hua University, Hsin-Chu, Taiwan
+Email:
+.  Department of Applied Informatics and Multimedia, Asia University, Taichung, Taiwan"
+a7267bc781a4e3e79213bb9c4925dd551ea1f5c4,Proceedings of eNTERFACE 2015 Workshop on Intelligent Interfaces,"Proceedings of eNTERFACE’15
+The 11th Summer Workshop
+on Multimodal Interfaces
+August 10th - September 4th, 2015
+Numediart Institute, University of Mons
+Mons, Belgium"
+a784a0d1cea26f18626682ab108ce2c9221d1e53,Anchored Regression Networks Applied to Age Estimation and Super Resolution,"Anchored Regression Networks applied to Age Estimation and Super Resolution
+Eirikur Agustsson
+D-ITET, ETH Zurich
+Switzerland
+Radu Timofte
+D-ITET, ETH Zurich
+Merantix GmbH
+Luc Van Gool
+D-ITET, ETH Zurich
+ESAT, KU Leuven"
+a77e9f0bd205a7733431a6d1028f09f57f9f73b0,Multimodal feature fusion for CNN-based gait recognition: an empirical comparison,"Multimodal feature fusion for CNN-based gait recognition: an
+empirical comparison
+F.M. Castroa,, M.J. Mar´ın-Jim´enezb, N. Guila, N. P´erez de la Blancac
+Department of Computer Architecture, University of Malaga, Spain, 29071
+Department of Computing and Numerical Analysis, University of Cordoba, Spain, 14071
+Department of Computer Science and Artiﬁcial Intelligence, University of Granada, Spain, 18071"
+a7d23c699a5ae4ad9b8a5cbb8c38e5c3b5f5fb51,A Summary of literature review : Face Recognition,"Postgraduate Annual Research Seminar 2007 (3-4 July 2007)
+A Summary of literature review : Face Recognition
+Kittikhun Meethongjan & Dzulkifli Mohamad
+Faculty of Computer Science & Information System,
+University Technology of Malaysia, 81310 Skudai, Johor, Malaysia."
+a7664247a37a89c74d0e1a1606a99119cffc41d4,Modal Consistency based Pre-Trained Multi-Model Reuse,Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
+a7a6eb53bee5e2224f2ecd56a14e3a5a717e55b9,Face Recognition Using Multi-viewpoint Patterns for Robot Vision,"1th International Symposium of Robotics Research (ISRR2003), pp.192-201, 2003
+Face Recognition Using Multi-viewpoint Patterns for
+Robot Vision
+Kazuhiro Fukui and Osamu Yamaguchi
+Corporate Research and Development Center, TOSHIBA Corporation
+, KomukaiToshiba-cho, Saiwai-ku, Kawasaki 212-8582 Japan"
+a758b744a6d6962f1ddce6f0d04292a0b5cf8e07,"Study on Human Face Recognition under Invariant Pose, Illumination and Expression using LBP, LoG and SVM","ISSN XXXX XXXX © 2017 IJESC
+Research Article                                                                                                                              Volume 7 Issue No.4
+Study on Human Face Recognition under Invariant Pose, Illumination
+nd Expression using LBP, LoG and SVM
+Amrutha
+Depart ment of Co mputer Science & Engineering
+Mangalore Institute of Technology & Engineering , Moodabidri, Mangalore, India
+INTRODUCTION
+RELATED WORK
+Abstrac t:
+Face  recognition  system  uses  human  face  for  the  identification  of  the   user.  Face  recognition  is  a  difficu lt  task  there  is  no  unique
+method  that  provide  accurate  an  accurate  and  effic ient  solution  in  all  the  situations  like  the  face  image  with  differen t  pose ,
+illu mination  and  exp ression.  Local  Binary  Pattern  (LBP)  and  Laplac ian  of  Gaussian  (Lo G)  operators.  Support  Vector  Machine
+lassifier  is  used  to  recognize  the  human  face.  The  Lo G  algorith m  is  used  to preprocess the  image  to  detect  the  edges of  the  face
+image to get the image information. The  LBP operator divides the face  image into several blocks to generate the features informat ion
+on  pixe l  level  by  creating  LBP  labels  for  all  the  blocks  of  image  is  obtained  by  concatenating  all  the  individual  local  histo grams.
+Support Vector Machine classifier  (SVM )  is used to classify t he image. The a lgorith m performances is verified under the constraints
+like illu mination, e xp ression and pose variation
+Ke ywor ds:  Face  Recognition,  Local  Binary  Pattern,  Laplac ian  of  Gaussian,  histogram,  illu mination,  pose  angle,  exp ression
+variations, SVM ."
+a75ee7f4c4130ef36d21582d5758f953dba03a01,Human face attributes prediction with Deep Learning,"DD2427 Final Project Report
+Mohamed Abdulaziz Ali Haseeb
+DD2427 Final Project Report
+Human face attributes prediction with Deep
+Learning
+Mohamed Abdulaziz Ali Haseeb"
+a775da3e6e6ea64bffab7f9baf665528644c7ed3,Human Face Pose Estimation based on Feature Extraction Points,"International Journal of Computer Applications (0975 – 8887)
+Volume 142 – No.9, May 2016
+Human Face Pose Estimation based on Feature
+Extraction Points
+Guneet Bhullar
+Research scholar,
+Department of ECE
+SBSSTC, Moga Road,
+Ferozepur, Punjab, India"
+a703d51c200724517f099ee10885286ddbd8b587,Fuzzy neural networks(FNN)-based approach for personalized facial expression recognition with novel feature selection method,"Fuzzy Neural Networks(FNN)-based Approach for
+Personalized Facial Expression Recognition with
+Novel Feature Selection Method
+Dae-Jin Kim and Zeungnam Bien
+Div. of EE, Dept. of EECS, KAIST
+73-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea
+Kwang-Hyun Park
+Human-friendly Welfare Robotic System Engineering Research Center, KAIST
+73-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea"
+b871d1b8495025ff8a6255514ed39f7765415935,Application of Completed Local Binary Pattern for Facial Expression Recognition on Gabor Filtered Facial Images,"Application of Completed Local Binary Pattern for Facial Expression
+Recognition on Gabor Filtered Facial Images
+Tanveer Ahsan, 2Rifat Shahriar, *3Uipil Chong
+Dept. of Electrical and Computer Engineering, University of Ulsan, Ulsan, Republic of Korea"
+b8dba0504d6b4b557d51a6cf4de5507141db60cf,Comparing Performances of Big Data Stream Processing Platforms with RAM3S,"Comparing Performances of Big Data Stream
+Processing Platforms with RAM3S"
+b89862f38fff416d2fcda389f5c59daba56241db,A Web Survey for Facial Expressions Evaluation,"A Web Survey for Facial Expressions Evaluation
+Matteo Sorci
+Gianluca Antonini
+Jean-Philippe Thiran
+Ecole Polytechnique Federale de Lausanne
+Signal Processing Institute
+Ecublens, 1015 Lausanne, Switzerland
+Ecole Polytechnique Federale de Lausanne, Operation Research Group
+Michel Bierlaire
+Ecublens, 1015 Lausanne, Switzerland
+June 9, 2008"
+b8f3f6d8f188f65ca8ea2725b248397c7d1e662d,Selfie Detection by Synergy-Constraint Based Convolutional Neural Network,"Selﬁe Detection by Synergy-Constriant Based
+Convolutional Neural Network
+Yashas Annadani, Vijaykrishna Naganoor, Akshay Kumar Jagadish and Krishnan Chemmangat
+Electrical and Electronics Engineering, NITK-Surathkal, India."
+b85580ff2d8d8be0a2c40863f04269df4cd766d9,HCMUS team at the Multimodal Person Discovery in Broadcast TV Task of MediaEval 2016,"HCMUS team at the Multimodal Person Discovery in
+Broadcast TV Task of MediaEval 2016
+Vinh-Tiep Nguyen, Manh-Tien H. Nguyen, Quoc-Huu Che, Van-Tu Ninh,
+Tu-Khiem Le, Thanh-An Nguyen, Minh-Triet Tran
+Faculty of Information Technology
+University of Science, Vietnam National University-Ho Chi Minh city
+{nhmtien, cqhuu, nvtu,"
+b81cae2927598253da37954fb36a2549c5405cdb,Experiments on Visual Information Extraction with the Faces of Wikipedia,"Experiments on Visual Information Extraction with the Faces of Wikipedia
+Md. Kamrul Hasan and Christopher Pal
+D´epartement de g´enie informatique et g´enie logiciel, Polytechnique Montr´eal
+500, Chemin de Polytechnique, Universit´e de Montr´eal, Montr`eal, Qu´ebec, Canada"
+b8a829b30381106b806066d40dd372045d49178d,A Probabilistic Framework for Joint Pedestrian Head and Body Orientation Estimation,"A Probabilistic Framework for Joint Pedestrian Head
+nd Body Orientation Estimation
+Fabian Flohr, Madalin Dumitru-Guzu, Julian F. P. Kooij, and Dariu M. Gavrila"
+b1d89015f9b16515735d4140c84b0bacbbef19ac,Too Far to See? Not Really!—Pedestrian Detection With Scale-Aware Localization Policy,"Too Far to See? Not Really!
+— Pedestrian Detection with Scale-aware
+Localization Policy
+Xiaowei Zhang, Li Cheng, Bo Li, and Hai-Miao Hu"
+b14b672e09b5b2d984295dfafb05604492bfaec5,Apprentissage de Modèles pour la Classification et la Recherche d ’ Images Learning Image Classification and Retrieval Models,LearningImageClassiﬁcationandRetrievalModelsThomasMensink
+b1a3b19700b8738b4510eecf78a35ff38406df22,Automatic Analysis of Facial Actions: A Survey,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TAFFC.2017.2731763, IEEE
+Transactions on Affective Computing
+JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014
+Automatic Analysis of Facial Actions: A Survey
+Brais Martinez, Member, IEEE, Michel F. Valstar, Senior Member, IEEE, Bihan Jiang,
+nd Maja Pantic, Fellow, IEEE"
+b166ce267ddb705e6ed855c6b679ec699d62e9cb,Sample group and misplaced atom dictionary learning for face recognition,"Turk J Elec Eng & Comp Sci
+(2017) 25: 4421 { 4430
+⃝ T (cid:127)UB_ITAK
+doi:10.3906/elk-1702-49
+Sample group and misplaced atom dictionary learning for face recognition
+Meng WANG1;2, Zhengping HU1;(cid:3)
+, Zhe Sun1, Mei ZHU2, Mei SUN2
+Department of Information Science & Engineering, Faculty of Electronics & Communication, Yanshan University,
+Department of Physics & Electronics Engineering, Faculty of Electronics & Communication, Taishan University,
+Qinhuangdao, P.R. China
+Tai’an, P.R. China
+Received: 04.02.2017
+(cid:15)
+Accepted/Published Online: 01.06.2017
+(cid:15)
+Final Version: 05.10.2017"
+b15a06d701f0a7f508e3355a09d0016de3d92a6d,Facial contrast is a cue for perceiving health from the face.,"Running head:  FACIAL CONTRAST LOOKS HEALTHY
+Facial contrast is a cue for perceiving health from the face
+Richard Russell1, Aurélie Porcheron2,3, Jennifer R. Sweda1, Alex L. Jones1, Emmanuelle
+Mauger2, Frederique Morizot2
+Gettysburg College, Gettysburg, PA, USA
+CHANEL Recherche et Technologie, Chanel PB
+Université Grenoble Alpes
+Author Note
+Richard Russell, Jennifer R. Sweda, and Alex L. Jones, Department of Psychology,
+Gettysburg College.  Aurélie Porcheron, Emmanuelle Mauger, and Frederique Morizot,
+CHANEL Recherche et Technologie, Chanel PB.  Aurélie Porcheron, Laboratoire de
+Psychologie et NeuroCognition, Université Grenoble Alpes.
+Corresponding author:  Richard Russell, Department of Psychology, Box 407, Gettysburg
+College, Gettysburg, PA 17325, USA.  Email:
+This is a prepublication copy.  This article may not exactly replicate the authoritative document
+published in the APA journal. It is not the copy of record.  The authoritative document can be
+found through this DOI: http://psycnet.apa.org/doi/10.1037/xhp0000219"
+b1444b3bf15eec84f6d9a2ade7989bb980ea7bd1,Local Directional Relation Pattern for Unconstrained and Robust Face Retrieval,"LOCAL DIRECTIONAL RELATION PATTERN
+Local Directional Relation Pattern for
+Unconstrained and Robust Face Retrieval
+Shiv Ram Dubey, Member, IEEE"
+b1451721864e836069fa299a64595d1655793757,Criteria Sliders: Learning Continuous Database Criteria via Interactive Ranking,"Criteria Sliders: Learning Continuous
+Database Criteria via Interactive Ranking
+James Tompkin,1∗ Kwang In Kim,2∗ Hanspeter Pﬁster,3 and Christian Theobalt4
+Brown University 2University of Bath
+Harvard University 4Max Planck Institute for Informatics"
+b19e83eda4a602abc5a8ef57467c5f47f493848d,Heat Kernel Based Local Binary Pattern for Face Representation,"JOURNAL OF LATEX CLASS FILES
+Heat Kernel Based Local Binary Pattern for
+Face Representation
+Xi Li†, Weiming Hu†, Zhongfei Zhang‡, Hanzi Wang§"
+dde5125baefa1141f1ed50479a3fd67c528a965f,Synthesizing Normalized Faces from Facial Identity Features,"Synthesizing Normalized Faces from Facial Identity Features
+Forrester Cole1 David Belanger1,2 Dilip Krishnan1 Aaron Sarna1 Inbar Mosseri1 William T. Freeman1,3
+Google, Inc. 2University of Massachusetts Amherst 3MIT CSAIL
+{fcole, dbelanger, dilipkay, sarna, inbarm,"
+dd8084b2878ca95d8f14bae73e1072922f0cc5da,"Model Distillation with Knowledge Transfer in Face Classification, Alignment and Verification","Model Distillation with Knowledge Transfer from
+Face Classiﬁcation to Alignment and Veriﬁcation
+Chong Wang∗, Xipeng Lan and Yangang Zhang
+Beijing Orion Star Technology Co., Ltd. Beijing, China
+{chongwang.nlpr, xipeng.lan,"
+ddf55fc9cf57dabf4eccbf9daab52108df5b69aa,Methodology and Performance Analysis of 3-D Facial Expression Recognition Using Statistical Shape Representation,"International Journal of Grid and Distributed Computing
+Vol. 4, No. 3, September, 2011
+Methodology and Performance Analysis of 3-D Facial Expression
+Recognition Using Statistical Shape Representation
+Wei Quan, Bogdan J. Matuszewski, Lik-Kwan Shark
+ADSIP Research Centre, University of Central Lancashire
+{WQuan, BMatuszewski1,
+Charlie Frowd
+School of Psychology, University of Central Lancashire"
+ddea3c352f5041fb34433b635399711a90fde0e8,Facial Expression Classification using Visual Cues and Language,"Facial Expression Classiﬁcation using Visual Cues and Language
+Abhishek Kar
+Advisor: Dr. Amitabha Mukerjee
+Department of Computer Science and Engineering, IIT Kanpur"
+ddbd24a73ba3d74028596f393bb07a6b87a469c0,Multi-region Two-Stream R-CNN for Action Detection,"Multi-region two-stream R-CNN
+for action detection
+Xiaojiang Peng, Cordelia Schmid
+Inria(cid:63)"
+ddf099f0e0631da4a6396a17829160301796151c,Learning Face Image Quality from Human Assessments,"IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
+Learning Face Image Quality from
+Human Assessments
+Lacey Best-Rowden, Member, IEEE, and Anil K. Jain, Life Fellow, IEEE"
+dd0a334b767e0065c730873a95312a89ef7d1c03,Eigenexpressions: Emotion Recognition Using Multiple Eigenspaces,"Eigenexpressions: Emotion Recognition using Multiple
+Eigenspaces
+Luis Marco-Gim´enez1, Miguel Arevalillo-Herr´aez1, and Cristina Cuhna-P´erez2
+University of Valencia. Computing Department,
+Burjassot. Valencia 46100, Spain,
+Universidad Cat´olica San Vicente M´artir de Valencia (UCV),
+Burjassot. Valencia. Spain"
+dd8d53e67668067fd290eb500d7dfab5b6f730dd,A Parameter-Free Framework for General Supervised Subspace Learning,"A Parameter-Free Framework for General
+Supervised Subspace Learning
+Shuicheng Yan, Member, IEEE, Jianzhuang Liu, Senior Member, IEEE, Xiaoou Tang, Senior Member, IEEE,
+nd Thomas S. Huang, Life Fellow, IEEE"
+ddbb6e0913ac127004be73e2d4097513a8f02d37,Face Detection Using Quantized Skin Color Regions Merging and Wavelet Packet Analysis,"IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 1, NO. 3, SEPTEMBER 1999
+Face Detection Using Quantized Skin Color
+Regions Merging and Wavelet Packet Analysis
+Christophe Garcia and Georgios Tziritas, Member, IEEE"
+dc550f361ae82ec6e1a0cf67edf6a0138163382e,Emotion Based Music Player,"ISSN XXXX XXXX © 2018 IJESC
+Research Article                                                                                                                           Volume 8 Issue No.3
+Vijay Chakole1, Aniket Choudhary2, Kalyani Trivedi3, Kshitija Bhoyar4, Ruchita Bodele5, Sayali Karmore6
+Emotion Based Music Player
+Professor1, UG Student2, 3, 4, 5, 6
+Department of Electronics Engineering
+K.D.K. College of Engineering Nagpur, India"
+dcb44fc19c1949b1eda9abe998935d567498467d,Ordinal Zero-Shot Learning,"Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
+labelunseen labelFigure1:Supervisionintensityfordifferentlabels.Greenrepre-sentsseenlabelsandredrepresentsunseenlabels.Thegroundtruthlabelofthisinstanceis“Good”,soithasthestrongestsupervisionintensity.Although“Common”isanunseenlabel,itstillhascertainsupervisioninformationbecauseitiscloselyrelatedto“Good”.classiﬁer;[ZhangandSaligrama,2016]learnsajointlatentspaceusingstructuredlearning.Thedifﬁcultyinobtainingthesideinformationorusingothertechniquestoprocessthesideinformationarethemostseriousissuesformanyexistingzero-shotlearningmethods.Fortheattribute-basedmethods,humanexpertsareneededtolabelattributesandthisisverytime-consumingandnoteasytoobtainthediscriminativecategory-levelattributes.Somemethodsdiscoverattributesinteractively[ParikhandGrau-man,2011][Bransonetal.,2010],butthisalsorequiresla-borioushumanparticipation.Althoughmanyalgorithmscandiscoverattribute-relatedconceptsontheWeb[Rohrbachetal.,2010][Bergetal.,2010],theycanalsobebiasedorlackinformationthatiscriticaltoaparticulartask[ParikhandGrauman,2011].Forthetextcorpora-basedmethods,theyﬁrstrequirealargelanguagecorpora,suchasWikipedia,andthenneedtolearnwordrepresentation[Socheretal.,2013]orusestandardNaturalLanguageProcessing(NLP)techniquestoproduceclassdescriptions[Elhoseinyetal.,2013].Itishardtoguaranteethecorrectnessofsuchclassdescriptionsforzero-shotlearning.Conclusively,althoughsideinforma-tionishelpfulforzero-shotlearning,ithasmanydisadvan-tages.Generatingthesesideinformationisverytediousandsometimeswecannotknowwhichsideinformationistrulywanted.IfwedependonhumanlabororNLPtechniques,noisysideinformationwillbecomealmostinevitableandin-fluencetheﬁnalperformance.Toavoidtheseproblems,itisimportanttosolvezero-shotlearninginwhateverpossiblecasesthathavesomepropertieswecanutilizetoavoidusingsideinformation."
+dc7df544d7c186723d754e2e7b7217d38a12fcf7,Facial expression recognition using salient facial patches,"Facial expression recognition using salient facial patches
+Hazar Mliki
+MIRACL-ENET’COM
+University of Sfax
+Tunisia (3018), Sfax
+Mohamed Hammami
+MIRACL-FSS
+University of Sfax
+Tunisia (3018), Sfax"
+dc77287bb1fcf64358767dc5b5a8a79ed9abaa53,Fashion Conversation Data on Instagram,"Fashion Conversation Data on Instagram
+Yu-I Ha∗
+Sejeong Kwon∗
+Meeyoung Cha∗
+Jungseock Joo†
+Graduate School of Culture Technology, KAIST, South Korea
+Department of Communication Studies, UCLA, USA"
+dc2e805d0038f9d1b3d1bc79192f1d90f6091ecb,Face Recognition and Facial Attribute Analysis from Unconstrained Visual Data,
+dc974c31201b6da32f48ef81ae5a9042512705fe,Am I Done? Predicting Action Progress in Videos,"Am I done? Predicting Action Progress in Video
+Federico Becattini1, Tiberio Uricchio1, Lorenzo Seidenari1,
+Alberto Del Bimbo1, and Lamberto Ballan2
+Media Integration and Communication Center, Univ. of Florence, Italy
+Department of Mathematics “Tullio Levi-Civita”, Univ. of Padova, Italy"
+b613b30a7cbe76700855479a8d25164fa7b6b9f1,Identifying User-Specific Facial Affects from Spontaneous Expressions with Minimal Annotation,"Identifying User-Specific Facial Affects from
+Spontaneous Expressions with Minimal Annotation
+Michael Xuelin Huang, Grace Ngai, Kien A. Hua, Fellow, IEEE, Stephen C.F. Chan, Member, IEEE
+nd Hong Va Leong, Member, IEEE Computer Society"
+b6f682648418422e992e3ef78a6965773550d36b,"CBMM Memo No . 061 February 8 , 2017 Full interpretation of minimal images","February 8, 2017"
+a9791544baa14520379d47afd02e2e7353df87e5,The Need for Careful Data Collection for Pattern Recognition in Digital Pathology,"Technical Note
+The Need for Careful Data Collection for Pattern Recognition in
+Digital Pathology
+Raphaël Marée1
+Department of Electrical Engineering and Computer Science, Montefiore Institute, University of Liège, 4000 Liège, Belgium
+Received: 08 December 2016
+Accepted: 15 March 2017
+Published: 10 April 2017"
+a9eb6e436cfcbded5a9f4b82f6b914c7f390adbd,A Model for Facial Emotion Inference Based on Planar Dynamic Emotional Surfaces,"(IJARAI) International Journal of Advanced Research in Artificial Intelligence,
+Vol. 5, No.6, 2016
+A Model for Facial Emotion Inference Based on
+Planar Dynamic Emotional Surfaces
+Ruivo,  J.  P.  P.
+Escola  Polit´ecnica
+Negreiros,  T.
+Escola  Polit´ecnica
+Barretto,  M.  R.  P.
+Escola  Polit´ecnica
+Tinen,  B.
+Escola  Polit´ecnica
+Universidade de S˜ao Paulo
+Universidade de S˜ao Paulo
+Universidade de S˜ao Paulo
+Universidade de S˜ao Paulo
+S˜ao Paulo, Brazil
+S˜ao Paulo, Brazil
+S˜ao Paulo, Brazil
+S˜ao Paulo, Brazil"
+a955033ca6716bf9957b362b77092592461664b4,Video Based Face Recognition Using Artificial Neural Network,"ISSN(Online): 2320-9801
+ISSN (Print):  2320-9798
+International Journal of Innovative Research in Computer
+nd Communication Engineering
+(An ISO 3297: 2007 Certified Organization)
+Video Based Face Recognition Using Artificial
+Vol. 3, Issue 6, June 2015
+Neural Network
+Santhy Mol T, Neethu Susan Jacob
+Pursuing M.Tech, Dept. of CSE, Caarmel Engineering College, MG University, Kerala, India
+Assistant Professor, Dept of CSE, Caarmel Engineering College, MG University, Kerala, India"
+a956ff50ca958a3619b476d16525c6c3d17ca264,A novel bidirectional neural network for face recognition,"A Novel Bidirectional Neural Network for Face Recognition
+JalilMazloum, Ali Jalali and Javad Amiryan
+Electrical and Computer Engineering Department
+ShahidBeheshti University
+Tehran, Iran"
+a98316980b126f90514f33214dde51813693fe0d,Collaborations on YouTube: From Unsupervised Detection to the Impact on Video and Channel Popularity,"Collaborations on YouTube: From Unsupervised Detection to the
+Impact on Video and Channel Popularity
+Christian Koch, Moritz Lode, Denny Stohr, Amr Rizk, Ralf Steinmetz
+Multimedia Communications Lab (KOM), Technische Universität Darmstadt, Germany
+E-Mail: {Christian.Koch | Denny.Stohr | Amr.Rizk |"
+a93781e6db8c03668f277676d901905ef44ae49f,Recent Data Sets on Object Manipulation: A Survey.,"Recent Datasets on Object Manipulation: A Survey
+Yongqiang Huang, Matteo Bianchi, Minas Liarokapis and Yu Sun"
+a9adb6dcccab2d45828e11a6f152530ba8066de6,Aydınlanma Alt-uzaylarına dayalı Gürbüz Yüz Tanıma Illumination Subspaces based Robust Face Recognition,"Aydınlanma Alt-uzaylarına dayalı Gürbüz Yüz Tanıma
+Illumination Subspaces based Robust Face Recognition
+D. Kern, H.K. Ekenel, R. Stiefelhagen
+Interactive Systems Labs, Universität Karlsruhe (TH)
+76131 Karlsruhe, Almanya
+web: http://isl.ira.uka.de/face_recognition
+Özetçe
+yönlerine
+ydınlanma
+kaynaklanan
+sonra,  yüz  uzayı
+Bu çalışmada aydınlanma alt-uzaylarına dayalı bir yüz tanıma
+sistemi  sunulmuştur.  Bu  sistemde,
+ilk  olarak,  baskın
+ydınlanma yönleri, bir topaklandırma algoritması kullanılarak
+öğrenilmiştir.  Topaklandırma  algoritması  sonucu  önden,  sağ
+ve  sol  yanlardan  olmak  üzere  üç  baskın  aydınlanma  yönü
+gözlemlenmiştir.  Baskın
+karar
+-yüzün  görünümündeki"
+a95dc0c4a9d882a903ce8c70e80399f38d2dcc89,Review and Implementation of High-Dimensional Local Binary Patterns and Its Application to Face Recognition,"TR-IIS-14-003
+Review and Implementation of
+High-Dimensional Local Binary
+Patterns and Its Application to
+Face Recognition
+Bor-Chun Chen, Chu-Song Chen, Winston Hsu
+July. 24,    2014    ||    Technical Report No. TR-IIS-14-003
+http://www.iis.sinica.edu.tw/page/library/TechReport/tr2014/tr14.html"
+a9286519e12675302b1d7d2fe0ca3cc4dc7d17f6,Learning to Succeed while Teaching to Fail: Privacy in Closed Machine Learning Systems,"Learning to Succeed while Teaching to Fail:
+Privacy in Closed Machine Learning Systems
+Jure Sokoli´c, Qiang Qiu, Miguel R. D. Rodrigues, and Guillermo Sapiro"
+a949b8700ca6ba96ee40f75dfee1410c5bbdb3db,Instance-Weighted Transfer Learning of Active Appearance Models,"Instance-weighted Transfer Learning of Active Appearance Models
+Daniel Haase, Erik Rodner, and Joachim Denzler
+Computer Vision Group, Friedrich Schiller University of Jena, Germany
+Ernst-Abbe-Platz 2-4, 07743 Jena, Germany"
+a92b5234b8b73e06709dd48ec5f0ec357c1aabed,Disjoint Multi-task Learning Between Heterogeneous Human-Centric Tasks,
+d50c6d22449cc9170ab868b42f8c72f8d31f9b6c,Dynamic Multi-Task Learning with Convolutional Neural Network,Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
+d522c162bd03e935b1417f2e564d1357e98826d2,Weakly supervised object extraction with iterative contour prior for remote sensing images,"He et al. EURASIP Journal on Advances in Signal Processing 2013, 2013:19
+http://asp.eurasipjournals.com/content/2013/1/19
+RESEARCH
+Open Access
+Weakly supervised object extraction with
+iterative contour prior for remote sensing
+images
+Chu He1,2*, Yu Zhang1, Bo Shi1, Xin Su3, Xin Xu1 and Mingsheng Liao2"
+d59f18fcb07648381aa5232842eabba1db52383e,Robust Facial Expression Recognition Using Spatially Localized Geometric Model,"International Conference on Systemics, Cybernetics and Informatics, February 12–15, 2004
+ROBUST FACIAL EXPRESSION RECOGNITION USING SPATIALLY
+LOCALIZED GEOMETRIC MODEL
+Department of Electrical Engineering
+Dept. of Computer Sc. and Engg.
+Ashutosh Saxena
+IIT Kanpur
+Kanpur 208016, India
+Kanpur 208016, India
+Ankit Anand
+IIT Kanpur
+Prof. Amitabha Mukerjee
+Dept. of Computer Sc. and Engg.
+IIT Kanpur
+Kanpur 208016, India
+While  approaches  based  on  3D  deformable  facial  model  have
+chieved expression recognition rates of as high as 98% [2], they
+re  computationally  inefficient  and  require  considerable  apriori
+training  based  on  3D  information,  which  is  often  unavailable.
+Recognition  from  2D  images  remains  a  difficult  yet  important"
+d588dd4f305cdea37add2e9bb3d769df98efe880,Audio - Visual Authentication System over the Internet Protocol,"Audio-Visual Authentication System over the
+Internet Protocol
+Yee Wan Wong, Kah Phooi Seng, and Li-Minn Ang
+bandoned.
+illumination  based
+is  developed  with  the  objective  to"
+d5444f9475253bbcfef85c351ea9dab56793b9ea,BoxCars: Improving Fine-Grained Recognition of Vehicles using 3-D Bounding Boxes in Traffic Surveillance,"IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
+BoxCars: Improving Fine-Grained Recognition
+of Vehicles using 3D Bounding Boxes
+in Trafﬁc Surveillance
+Jakub Sochor, Jakub ˇSpaˇnhel, Adam Herout
+in contrast"
+d5ab6aa15dad26a6ace5ab83ce62b7467a18a88e,Optimized Structure for Facial Action Unit Relationship Using Bayesian Network,"World Journal of Computer Application and Technology 2(7): 133-138, 2014
+DOI: 10.13189/wjcat.2014.020701
+http://www.hrpub.org
+Optimized Structure for Facial Action Unit Relationship
+Using Bayesian Network
+Yee Koon Loh*, Shahrel A. Suandi
+Intelligent Biometric Group, School of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, Pulau
+*Corresponding Author:
+Pinang, Malaysia
+Copyright © 2014 Horizon Research Publishing All rights reserved."
+d56fe69cbfd08525f20679ffc50707b738b88031,Training of multiple classifier systems utilizing partially labeled sequential data sets,"Training of multiple classiﬁer systems utilizing
+partially labelled sequences
+Martin Schels, Patrick Schillinger, and Friedhelm Schwenker
+Ulm University - Department of Neural Information Processing
+89069 Ulm - Germany"
+d5de42d37ee84c86b8f9a054f90ddb4566990ec0,Asynchronous Temporal Fields for Action Recognition,"Asynchronous Temporal Fields for Action Recognition
+Gunnar A. Sigurdsson1∗ Santosh Divvala2,3 Ali Farhadi2,3 Abhinav Gupta1,3
+Carnegie Mellon University 2University of Washington 3Allen Institute for Artiﬁcial Intelligence
+github.com/gsig/temporal-fields/"
+d50a40f2d24363809a9ac57cf7fbb630644af0e5,End-to-end Trained CNN Encode-Decoder Networks for Image Steganography,"END-TO-END TRAINED CNN ENCODER-DECODER NETWORKS FOR IMAGE
+STEGANOGRAPHY
+Atique ur Rehman, Raﬁa Rahim, Shahroz Nadeem, Sibt ul Hussain
+National University of Computer & Emerging Sciences (NUCES-FAST), Islamabad, Pakistan.
+Reveal.ai (Recognition, Vision & Learning) Lab"
+d5b5c63c5611d7b911bc1f7e161a0863a34d44ea,Extracting Scene-Dependent Discriminant Features for Enhancing Face Recognition under Severe Conditions,"Extracting Scene-dependent Discriminant
+Features for Enhancing Face Recognition
+under Severe Conditions
+Rui Ishiyama and Nobuyuki Yasukawa
+Information and Media Processing Research Laboratories, NEC Corporation
+753, Shimonumabe, Nakahara-Ku, Kawasaki 211-8666 Japan"
+d59404354f84ad98fa809fd1295608bf3d658bdc,Face Synthesis from Visual Attributes via Sketch using Conditional VAEs and GANs,"International Journal of Computer Vision manuscript No.
+(will be inserted by the editor)
+Face Synthesis from Visual Attributes via Sketch using
+Conditional VAEs and GANs
+Xing Di · Vishal M. Patel
+Received: date / Accepted: date"
+d231a81b38fde73bdbf13cfec57d6652f8546c3c,SUPERRESOLUTION TECHNIQUES FOR FACE RECOGNITION FROM VIDEO by Osman,"SUPERRESOLUTION TECHNIQUES
+FOR FACE RECOGNITION FROM VIDEO
+Osman Gökhan Sezer
+B.S., E.E., Boğaziçi University, 2003
+Submitted to the Graduate School of Engineering
+and Natural Sciences in partially fulfillment of
+the requirement for the degree of
+Master of Science
+Graduate Program in Electronics Engineering and Computer Science
+Sabancı University
+Spring 2005"
+d22785eae6b7503cb16402514fd5bd9571511654,Evaluating Facial Expressions with Different Occlusion around Image Sequence,"Evaluating Facial Expressions with Different
+Occlusion around Image Sequence
+Ankita Vyas, Ramchand Hablani
+Department of Computer Science
+Sanghvi Institute of Management & Science
+Indore (MP), India
+local
+INTRODUCTION"
+d2eb1079552fb736e3ba5e494543e67620832c52,DeSTNet: Densely Fused Spatial Transformer Networks,"ANNUNZIATA, SAGONAS, CALÌ: DENSELY FUSED SPATIAL TRANSFORMER NETWORKS1
+DeSTNet: Densely Fused Spatial
+Transformer Networks1
+Roberto Annunziata
+Christos Sagonas
+Jacques Calì
+Onﬁdo Research
+Finsbury Avenue
+London, UK"
+d24dafe10ec43ac8fb98715b0e0bd8e479985260,"Effects of Social Anxiety on Emotional Mimicry and Contagion: Feeling Negative, but Smiling Politely","J Nonverbal Behav (2018) 42:81–99
+https://doi.org/10.1007/s10919-017-0266-z
+O R I G I N A L P A P E R
+Effects of Social Anxiety on Emotional Mimicry
+nd Contagion: Feeling Negative, but Smiling Politely
+Corine Dijk1
+Charlotte van Eeuwijk4
+• Gerben A. van Kleef2
+• Agneta H. Fischer2
+• Nexhmedin Morina3
+Published online: 25 September 2017
+Ó The Author(s) 2017. This article is an open access publication"
+d278e020be85a1ccd90aa366b70c43884dd3f798,Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks,"Learning From Less Data: Diversiﬁed Subset Selection and
+Active Learning in Image Classiﬁcation Tasks
+Vishal Kaushal
+IIT Bombay
+Mumbai, Maharashtra, India
+Khoshrav Doctor
+AITOE Labs
+Mumbai, Maharashtra, India
+Suyash Shetty
+AITOE Labs
+Mumbai, Maharashtra, India
+Rishabh Iyer
+AITOE Labs
+Seattle, Washington, USA
+Anurag Sahoo
+AITOE Labs
+Seattle, Washington, USA
+Narsimha Raju
+IIT Bombay
+Mumbai, Maharashtra, India"
+aadf4b077880ae5eee5dd298ab9e79a1b0114555,Using Hankel matrices for dynamics-based facial emotion recognition and pain detection,"Dynamics-based Facial Emotion Recognition and Pain Detection
+Using Hankel Matrices for
+Liliana Lo Presti and Marco La Cascia
+DICGIM - University of Palermo
+V.le delle Scienze, Ed. 6, 90128 Palermo (Italy)"
+aae742779e8b754da7973949992d258d6ca26216,Robust facial expression classification using shape and appearance features,"Robust Facial Expression Classification Using Shape
+nd Appearance Features
+S L Happy and Aurobinda Routray
+Department of Electrical Engineering,
+Indian Institute of Technology Kharagpur, India"
+aa52910c8f95e91e9fc96a1aefd406ffa66d797d,Face Recognition System Based on 2dfld and Pca,"FACE RECOGNITION SYSTEM BASED
+ON 2DFLD AND PCA
+Dr. Sachin D. Ruikar
+E&TC Department
+Sinhgad Academy of Engineering
+Pune, India
+Mr. Hulle Rohit Rajiv
+ME E&TC [Digital System]
+Sinhgad Academy of Engineering
+Pune, India"
+aafb8dc8fda3b13a64ec3f1ca7911df01707c453,Excitation Backprop for RNNs,"Excitation Backprop for RNNs
+Sarah Adel Bargal∗1, Andrea Zunino∗ 2, Donghyun Kim1, Jianming Zhang3,
+Vittorio Murino2,4, Stan Sclaroff1
+Department of Computer Science, Boston University 2Pattern Analysis & Computer Vision (PAVIS),
+Istituto Italiano di Tecnologia 3Adobe Research 4Computer Science Department, Universit`a di Verona
+Figure 1: Our proposed framework spatiotemporally highlights/grounds the evidence that an RNN model used in producing a class label
+or caption for a given input video. In this example, by using our proposed back-propagation method, the evidence for the activity class
+CliffDiving is highlighted in a video that contains CliffDiving and HorseRiding. Our model employs a single backward pass to produce
+saliency maps that highlight the evidence that a given RNN used in generating its outputs."
+aadfcaf601630bdc2af11c00eb34220da59b7559,Multi-view Hybrid Embedding: A Divide-and-Conquer Approach,"Multi-view Hybrid Embedding:
+A Divide-and-Conquer Approach
+Jiamiao Xu∗, Shujian Yu∗, Xinge You†, Senior Member, IEEE, Mengjun Leng,
+Xiao-Yuan Jing, and C. L. Philip Chen, Fellow, IEEE"
+aaa4c625f5f9b65c7f3df5c7bfe8a6595d0195a5,Biometrics in ambient intelligence,"Biometrics in Ambient Intelligence
+Massimo Tistarelli§ and Ben Schouten§§"
+aae0e417bbfba701a1183d3d92cc7ad550ee59c3,A Statistical Method for 2-D Facial Landmarking,"A Statistical Method for 2-D Facial Landmarking
+Hamdi Dibeklio˘glu, Student Member, IEEE, Albert Ali Salah, Member, IEEE, and Theo Gevers, Member, IEEE"
+aa577652ce4dad3ca3dde44f881972ae6e1acce7,Deep Attribute Networks,"Deep Attribute Networks
+Junyoung Chung
+Department of EE, KAIST
+Daejeon, South Korea
+Donghoon Lee
+Department of EE, KAIST
+Daejeon, South Korea
+Youngjoo Seo
+Department of EE, KAIST
+Daejeon, South Korea
+Chang D. Yoo
+Department of EE, KAIST
+Daejeon, South Korea"
+aa94f214bb3e14842e4056fdef834a51aecef39c,Reconhecimento de padrões faciais: Um estudo,"Reconhecimento de padrões faciais: Um estudo
+Alex Lima Silva, Marcos Evandro Cintra
+Universidade Federal
+Rural do Semi-Árido
+Departamento de Ciências Naturais
+Mossoró, RN - 59625-900
+Email:
+Resumo—O reconhecimento facial tem sido utilizado em di-
+versas áreas para identiﬁcação e autenticação de usuários. Um
+dos principais mercados está relacionado a segurança, porém há
+uma grande variedade de aplicações relacionadas ao uso pessoal,
+onveniência, aumento de produtividade, etc. O rosto humano
+possui um conjunto de padrões complexos e mutáveis. Para
+reconhecer esses padrões, são necessárias técnicas avançadas de
+reconhecimento de padrões capazes, não apenas de reconhecer,
+mas de se adaptar às mudanças constantes das faces das pessoas.
+Este documento apresenta um método de reconhecimento facial
+proposto a partir da análise comparativa de trabalhos encontra-
+dos na literatura.
+iométrica é o uso da biometria para reconhecimento, identi-"
+aac101dd321e6d2199d8c0b48c543b541c181b66,Using Context to Enhance the Understanding of Face Images,"USING CONTEXT TO ENHANCE THE
+UNDERSTANDING OF FACE IMAGES
+A Dissertation Presented
+VIDIT JAIN
+Submitted to the Graduate School of the
+University of Massachusetts Amherst in partial fulﬁllment
+of the requirements for the degree of
+DOCTOR OF PHILOSOPHY
+September 2010
+Department of Computer Science"
+af6e351d58dba0962d6eb1baf4c9a776eb73533f,How to Train Your Deep Neural Network with Dictionary Learning,"How to Train Your Deep Neural Network with
+Dictionary Learning
+Vanika Singhal*, Shikha Singh+ and Angshul Majumdar#
+*IIIT Delhi
+Okhla Phase 3
+Delhi, 110020, India
++IIIT Delhi
+Okhla Phase 3
+#IIIT Delhi
+Okhla Phase 3
+Delhi, 110020, India
+Delhi, 110020, India"
+af62621816fbbe7582a7d237ebae1a4d68fcf97d,Active Shape Model Based Recognition Of Facial Expression,"International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622
+International Conference on Humming Bird ( 01st March 2014)
+RESEARCH ARTICLE
+OPEN ACCESS
+Active Shape Model Based Recognition Of Facial Expression
+AncyRija V  , Gayathri. S2
+AncyRijaV,Author is currently pursuing M.E (Software Engineering) in Vins Christian College of
+Engineering,
+e-mail:
+Gayathri.S, M.E., Asst.Prof.,Department of Information Technology , Vins Christian college of Engineering."
+afa57e50570a6599508ee2d50a7b8ca6be04834a,Motion in action : optical flow estimation and action localization in videos. (Le mouvement en action : estimation du flot optique et localisation d'actions dans les vidéos),"Motion in action : optical flow estimation and action
+localization in videos
+Philippe Weinzaepfel
+To cite this version:
+Philippe Weinzaepfel. Motion in action : optical flow estimation and action localization in videos.
+Computer Vision and Pattern Recognition [cs.CV]. Université Grenoble Alpes, 2016. English. <NNT :
+016GREAM013>. <tel-01407258>
+HAL Id: tel-01407258
+https://tel.archives-ouvertes.fr/tel-01407258
+Submitted on 1 Dec 2016
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entific research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destinée au dépôt et à la diffusion de documents
+scientifiques de niveau recherche, publiés ou non,
+émanant des établissements d’enseignement et de"
+afc7092987f0d05f5685e9332d83c4b27612f964,Person-independent facial expression detection using Constrained Local Models,"Person-Independent Facial Expression Detection using Constrained
+Local Models
+Sien. W. Chew, Patrick Lucey, Simon Lucey, Jason Saragih, Jeffrey F. Cohn and Sridha Sridharan"
+b730908bc1f80b711c031f3ea459e4de09a3d324,Active Orientation Models for Face Alignment In-the-Wild,"Active Orientation Models for Face
+Alignment In-the-Wild
+Georgios Tzimiropoulos, Joan Alabort-i-Medina, Student Member, IEEE,
+Stefanos P. Zafeiriou, Member, IEEE, and Maja Pantic, Fellow, IEEE"
+b7cf7bb574b2369f4d7ebc3866b461634147041a,From NLDA to LDA/GSVD: a modified NLDA algorithm,"Neural Comput & Applic (2012) 21:1575–1583
+DOI 10.1007/s00521-011-0728-x
+O R I G I N A L A R T I C L E
+From NLDA to LDA/GSVD: a modiﬁed NLDA algorithm
+Jun Yin • Zhong Jin
+Received: 2 August 2010 / Accepted: 3 August 2011 / Published online: 19 August 2011
+Ó Springer-Verlag London Limited 2011"
+b7894c1f805ffd90ab4ab06002c70de68d6982ab,A comprehensive age estimation on face images using hybrid filter based feature extraction,"Biomedical Research 2017; Special Issue: S610-S618
+ISSN 0970-938X
+www.biomedres.info
+A comprehensive age estimation on face images using hybrid filter based
+feature extraction.
+Karthikeyan D1*, Balakrishnan G2
+Department of ECE, Srinivasan Engineering College, Perambalur, India
+Department of Computer Science and Engineering, Indra Ganesan College of Engineering, Trichy, India"
+b7eead8586ffe069edd190956bd338d82c69f880,A Video Database for Facial Behavior Understanding,"A VIDEO DATABASE FOR FACIAL
+BEHAVIOR UNDERSTANDING
+D. Freire-Obreg´on and M. Castrill´on-Santana.
+SIANI, Universidad de Las Palmas de Gran Canaria, Spain"
+b7774c096dc18bb0be2acef07ff5887a22c2a848,Distance metric learning for image and webpage comparison. (Apprentissage de distance pour la comparaison d'images et de pages Web),"Distance metric learning for image and webpage
+omparison
+Marc Teva Law
+To cite this version:
+Marc Teva Law. Distance metric learning for image and webpage comparison. Image Processing. Uni-
+versité Pierre et Marie Curie - Paris VI, 2015. English. <NNT : 2015PA066019>. <tel-01135698v2>
+HAL Id: tel-01135698
+https://tel.archives-ouvertes.fr/tel-01135698v2
+Submitted on 18 Mar 2015
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entific research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destinée au dépôt et à la diffusion de documents
+scientifiques de niveau recherche, publiés ou non,
+émanant des établissements d’enseignement et de
+recherche français ou étrangers, des laboratoires"
+b7f05d0771da64192f73bdb2535925b0e238d233,Robust Active Shape Model using AdaBoosted Histogram Classifiers,"MVA2005  IAPR  Conference on Machine VIsion Applications, May 16-18, 2005 Tsukuba Science City, Japan
+Robust Active Shape Model using AdaBoosted Histogram Classifiers
+Yuanzhong Li
+W ataru Ito
+Imaging Software Technology Center
+Imaging Software Technology Center
+FUJI PHOTO FILM  CO., LTD.
+fujifilm.co.jp
+FUJI PHOTO FILM  CO., LTD.
+fujifilm.co.jp"
+b755505bdd5af078e06427d34b6ac2530ba69b12,NFRAD: Near-Infrared Face Recognition at a Distance,"To appear in the International Joint Conf. Biometrics, Washington D.C., October, 2011
+NFRAD: Near-Infrared Face Recognition at a Distance
+Hyunju Maenga, Hyun-Cheol Choia, Unsang Parkb, Seong-Whan Leea and Anil K. Jaina,b
+Dept. of Brain and Cognitive Eng. Korea Univ., Seoul, Korea
+Dept. of Comp. Sci. & Eng. Michigan State Univ., E. Lansing, MI, USA 48824
+{hjmaeng, ,"
+b7b461f82c911f2596b310e2b18dd0da1d5d4491,K-mappings and Regression trees,"014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP)
+978-1-4799-2893-4/14/$31.00 ©2014 IEEE
+K-MAPPINGS AND REGRESSION TREES
+SAMSI and Duke University
+. INTRODUCTION
+rgminM1,...,MK
+P1,...PK
+Arthur Szlam†
+.1. Partitioning Y
+K(cid:2)
+(cid:2)
+(cid:3)
+(cid:4)"
+b73fdae232270404f96754329a1a18768974d3f6,Local Relation Map : A Novel Illumination Invariant Face Recognition Approach Regular Paper,
+b76af8fcf9a3ebc421b075b689defb6dc4282670,Face Mask Extraction in Video Sequence,"Face Mask Extraction in Video Sequence
+Yujiang Wang 1 · Bingnan Luo 1 · Jie Shen 1 · Maja Pantic 1"
+b7f7a4df251ff26aca83d66d6b479f1dc6cd1085,Handling missing weak classifiers in boosted cascade: application to multiview and occluded face detection,"Bouges et al. EURASIP Journal on Image and Video Processing 2013, 2013:55
+http://jivp.eurasipjournals.com/content/2013/1/55
+RESEARCH
+Open Access
+Handling missing weak classifiers in boosted
+ascade: application to multiview and
+occluded face detection
+Pierre Bouges1*, Thierry Chateau1*, Christophe Blanc1 and Gaëlle Loosli2"
+db227f72bb13a5acca549fab0dc76bce1fb3b948,Characteristic Based Image Search Using Re-Ranking Method,"International Refereed Journal of Engineering and Science (IRJES)
+ISSN (Online) 2319-183X, (Print) 2319-1821
+Volume 4, Issue 6 (June 2015), PP.169-169-174
+Characteristic Based Image Search using Re-Ranking method
+Chitti Babu, 2Yasmeen Jaweed, 3G.Vijay Kumar
+,2,3Computer Science Engineering Dept, Sree Dattha Institute of Engineering & Science"
+dbaf89ca98dda2c99157c46abd136ace5bdc33b3,Nonlinear Cross-View Sample Enrichment for Action Recognition,"Nonlinear Cross-View Sample Enrichment for
+Action Recognition
+Ling Wang, Hichem Sahbi
+Institut Mines-T´el´ecom; T´el´ecom ParisTech; CNRS LTCI"
+dbe255d3d2a5d960daaaba71cb0da292e0af36a7,Evolutionary Cost-Sensitive Extreme Learning Machine,"Evolutionary Cost-sensitive Extreme Learning
+Machine
+Lei Zhang, Member, IEEE, and David Zhang, Fellow, IEEE"
+dbb0a527612c828d43bcb9a9c41f1bf7110b1dc8,Machine Learning Techniques for Face Analysis,"Chapter 7
+Machine Learning Techniques
+for Face Analysis
+Roberto Valenti, Nicu Sebe, Theo Gevers, and Ira Cohen"
+dbb7f37fb9b41d1aa862aaf2d2e721a470fd2c57,Face image analysis with convolutional neural networks,"Face Image Analysis With
+Convolutional Neural Networks
+Dissertation
+Zur Erlangung des Doktorgrades
+der Fakult¨at f¨ur Angewandte Wissenschaften
+n der Albert-Ludwigs-Universit¨at Freiburg im Breisgau
+Stefan Duffner"
+dbd5e9691cab2c515b50dda3d0832bea6eef79f2,Image - based Face Recognition : Issues and Methods 1,"Image-basedFaceRecognition:IssuesandMethods
+WenYiZhao
+RamaChellappa
+Sarno(cid:11)Corporation
+CenterforAutomationResearch
+
+UniversityofMaryland
+Princeton,NJ
+CollegePark,MD
+db67edbaeb78e1dd734784cfaaa720ba86ceb6d2,SPECFACE — A dataset of human faces wearing spectacles,"SPECFACE - A Dataset of Human Faces Wearing Spectacles
+Anirban Dasgupta, Shubhobrata Bhattacharya and Aurobinda Routray
+Indian Institute of Technology Kharagpur
+India"
+a83fc450c124b7e640adc762e95e3bb6b423b310,Deep Face Feature for Face Alignment and Reconstruction,"Deep Face Feature for Face Alignment
+Boyi Jiang, Juyong Zhang, Bailin Deng, Yudong Guo and Ligang Liu"
+a85e9e11db5665c89b057a124547377d3e1c27ef,Dynamics of Driver's Gaze: Explorations in Behavior Modeling and Maneuver Prediction,"Dynamics of Driver’s Gaze: Explorations in
+Behavior Modeling & Maneuver Prediction
+Sujitha Martin, Member, IEEE, Sourabh Vora, Kevan Yuen, and Mohan M. Trivedi, Fellow, IEEE"
+a8117a4733cce9148c35fb6888962f665ae65b1e,A Good Practice Towards Top Performance of Face Recognition: Transferred Deep Feature Fusion,"IEEE TRANSACTIONS ON XXXX, VOL. XX, NO. XX, XX 201X
+A Good Practice Towards Top Performance of Face
+Recognition: Transferred Deep Feature Fusion
+Lin Xiong1∗†, Jayashree Karlekar1∗, Jian Zhao2∗†, Jiashi Feng2, Member, IEEE, Sugiri Pranata1, and
+Shengmei Shen1"
+a87ab836771164adb95d6744027e62e05f47fd96,Understanding human-human interactions: a survey,"Understanding human-human interactions: a survey
+Alexandros Stergiou
+Department of Information and Computing Sciences, Utrecht University,Buys Ballotgebouw, Princetonplein 5, Utrecht, 3584CC, Netherlands
+Department of Information and Computing Sciences, Utrecht University,Buys Ballotgebouw, Princetonplein 5, Utrecht, 3584CC, Netherlands
+Ronald Poppe1"
+a8035ca71af8cc68b3e0ac9190a89fed50c92332,IIIT-CFW: A Benchmark Database of Cartoon Faces in the Wild,"IIIT-CFW: A Benchmark Database of
+Cartoon Faces in the Wild
+Ashutosh Mishra1, Shyam Nandan Rai1, Anand Mishra2, C. V. Jawahar1
+IIIT Chittoor, Sri City, India
+CVIT, KCIS, IIIT Hyderabad, India"
+a88640045d13fc0207ac816b0bb532e42bcccf36,Simultaneously Learning Neighborship and Projection Matrix for Supervised Dimensionality Reduction,"ARXIV VERSION
+Simultaneously Learning Neighborship and
+Projection Matrix for Supervised
+Dimensionality Reduction
+Yanwei Pang, Senior Member, IEEE, Bo Zhou, and Feiping Nie, Senior Member, IEEE"
+a8a30a8c50d9c4bb8e6d2dd84bc5b8b7f2c84dd8,This is a repository copy of Modelling of Orthogonal Craniofacial Profiles,"This is a repository copy of Modelling of Orthogonal Craniofacial Profiles.
+White Rose Research Online URL for this paper:
+http://eprints.whiterose.ac.uk/131767/
+Version: Published Version
+Article:
+Dai, Hang, Pears, Nicholas Edwin orcid.org/0000-0001-9513-5634 and Duncan, Christian
+(2017) Modelling of Orthogonal Craniofacial Profiles. Journal of Imaging. ISSN 2313-433X
+https://doi.org/10.3390/jimaging3040055
+Reuse
+This article is distributed under the terms of the Creative Commons Attribution (CC BY) licence. This licence
+llows you to distribute, remix, tweak, and build upon the work, even commercially, as long as you credit the
+uthors for the original work. More information and the full terms of the licence here:
+https://creativecommons.org/licenses/
+Takedown
+If you consider content in White Rose Research Online to be in breach of UK law, please notify us by
+emailing including the URL of the record and the reason for the withdrawal request.
+https://eprints.whiterose.ac.uk/"
+a8638a07465fe388ae5da0e8a68e62a4ee322d68,How to predict the global instantaneous feeling induced by a facial picture?,"How to predict the global instantaneous feeling induced
+y a facial picture?
+Arnaud Lienhard, Patricia Ladret, Alice Caplier
+To cite this version:
+Arnaud Lienhard, Patricia Ladret, Alice Caplier. How to predict the global instantaneous
+feeling induced by a facial picture?. Signal Processing: Image Communication, Elsevier, 2015,
+pp.1-30. .
+HAL Id: hal-01198718
+https://hal.archives-ouvertes.fr/hal-01198718
+Submitted on 14 Sep 2015
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entiﬁc research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destin´ee au d´epˆot et `a la diffusion de documents
+scientiﬁques de niveau recherche, publi´es ou non,
+´emanant des ´etablissements d’enseignement et de"
+a8e75978a5335fd3deb04572bb6ca43dbfad4738,Sparse Graphical Representation based Discriminant Analysis for Heterogeneous Face Recognition,"Sparse Graphical Representation based Discriminant
+Analysis for Heterogeneous Face Recognition
+Chunlei Peng, Xinbo Gao, Senior Member, IEEE, Nannan Wang, Member, IEEE, and Jie Li"
+ded968b97bd59465d5ccda4f1e441f24bac7ede5,Large scale 3 D Morphable Models,"Noname manuscript No.
+(will be inserted by the editor)
+Large scale 3D Morphable Models
+James Booth · Anastasios Roussos · Allan Ponniah · David Dunaway · Stefanos
+Zafeiriou
+Received: date / Accepted: date"
+de0eb358b890d92e8f67592c6e23f0e3b2ba3f66,Inference-Based Similarity Search in Randomized Montgomery Domains for Privacy-Preserving Biometric Identification,"ACCEPTED BY IEEE TRANS. PATTERN ANAL. AND MACH. INTELL.
+Inference-Based Similarity Search in
+Randomized Montgomery Domains for
+Privacy-Preserving Biometric Identiﬁcation
+Yi Wang, Jianwu Wan, Jun Guo, Yiu-Ming Cheung, and Pong C Yuen"
+dee406a7aaa0f4c9d64b7550e633d81bc66ff451,Content-Adaptive Sketch Portrait Generation by Decompositional Representation Learning,"Content-Adaptive Sketch Portrait Generation by
+Decompositional Representation Learning
+Dongyu Zhang, Liang Lin, Tianshui Chen, Xian Wu, Wenwei Tan, and Ebroul Izquierdo"
+dedabf9afe2ae4a1ace1279150e5f1d495e565da,Robust Face Recognition With Structurally Incoherent Low-Rank Matrix Decomposition,"Robust Face Recognition With Structurally
+Incoherent Low-Rank Matrix Decomposition
+Chia-Po Wei, Chih-Fan Chen, and Yu-Chiang Frank Wang"
+de398bd8b7b57a3362c0c677ba8bf9f1d8ade583,Hierarchical Bayesian Theme Models for Multipose Facial Expression Recognition,"Hierarchical Bayesian Theme Models for
+Multi-pose Facial Expression Recognition
+Qirong Mao, Member, IEEE, Qiyu Rao, Yongbin Yu, and Ming Dong*, Member, IEEE"
+defa8774d3c6ad46d4db4959d8510b44751361d8,FEBEI - Face Expression Based Emoticon Identification CS - B657 Computer Vision,"FEBEI - Face Expression Based Emoticon Identiﬁcation
+CS - B657 Computer Vision
+Nethra Chandrasekaran Sashikar - necsashi
+Prashanth Kumar Murali - prmurali
+Robert J Henderson - rojahend"
+b08203fca1af7b95fda8aa3d29dcacd182375385,Object and Text-guided Semantics for CNN-based Activity Recognition,"OBJECT AND TEXT-GUIDED SEMANTICS FOR CNN-BASED ACTIVITY RECOGNITION
+(cid:63)Sungmin Eum †§, (cid:63)Christopher Reale †, Heesung Kwon†, Claire Bonial †, Clare Voss†
+U.S. Army Research Laboratory, Adelphi, MD, USA
+§Booz Allen Hamilton Inc., McLean, VA, USA"
+b09b693708f412823053508578df289b8403100a,Two-Stream SR-CNNs for Action Recognition in Videos,"WANG et al.: TWO-STREAM SR-CNNS FOR ACTION RECOGNITION IN VIDEOS
+Two-Stream SR-CNNs for Action
+Recognition in Videos
+Yifan Wang1
+Jie Song1
+Limin Wang2
+Luc Van Gool2
+Otmar Hilliges1
+Advanced Interactive Technologies Lab
+ETH Zurich
+Zurich, Switzerland
+Computer Vision Lab
+ETH Zurich
+Zurich, Switzerland"
+b07582d1a59a9c6f029d0d8328414c7bef64dca0,Employing Fusion of Learned and Handcrafted Features for Unconstrained Ear Recognition,"Employing Fusion of Learned and Handcrafted
+Features for Unconstrained Ear Recognition
+Maur´ıcio Pamplona Segundo∗†
+Earnest E. Hansley∗
+Sudeep Sarkar∗‡
+October 24, 2017"
+b0c1615ebcad516b5a26d45be58068673e2ff217,How Image Degradations Affect Deep CNN-Based Face Recognition?,"How Image Degradations Affect Deep CNN-based Face
+Recognition?
+S¸amil Karahan1 Merve Kılınc¸ Yıldırım1 Kadir Kırtac¸1 Ferhat S¸ ¨ukr¨u Rende1
+G¨ultekin B¨ut¨un1Hazım Kemal Ekenel2"
+b0de0892d2092c8c70aa22500fed31aa7eb4dd3f,A Robust and Efficient Video Representation for Action Recognition,"(will be inserted by the editor)
+A robust and efﬁcient video representation for action recognition
+Heng Wang · Dan Oneata · Jakob Verbeek · Cordelia Schmid
+Received: date / Accepted: date"
+a66d89357ada66d98d242c124e1e8d96ac9b37a0,Failure Detection for Facial Landmark Detectors,"Failure Detection for Facial Landmark Detectors
+Andreas Steger, Radu Timofte, and Luc Van Gool
+Computer Vision Lab, D-ITET, ETH Zurich, Switzerland
+{radu.timofte,"
+a608c5f8fd42af6e9bd332ab516c8c2af7063c61,Age Estimation via Grouping and Decision Fusion,"Age Estimation via Grouping and Decision Fusion
+Kuan-Hsien Liu, Member, IEEE, Shuicheng Yan, Senior Member, IEEE,
+nd C.-C. Jay Kuo, Fellow, IEEE"
+a6eb6ad9142130406fb4ffd4d60e8348c2442c29,"Video Description: A Survey of Methods, Datasets and Evaluation Metrics","Video Description: A Survey of Methods,
+Datasets and Evaluation Metrics
+Nayyer Aafaq, Syed Zulqarnain Gilani, Wei Liu, and Ajmal Mian"
+a6590c49e44aa4975b2b0152ee21ac8af3097d80,3D Interpreter Networks for Viewer-Centered Wireframe Modeling,"https://doi.org/10.1007/s11263-018-1074-6
+D Interpreter Networks for Viewer-Centered Wireframe Modeling
+Jiajun Wu1 · Tianfan Xue2 · Joseph J. Lim3 · Yuandong Tian4 ·
+Joshua B. Tenenbaum1 · Antonio Torralba1 · William T. Freeman1,5
+Received: date / Accepted: date"
+a694180a683f7f4361042c61648aa97d222602db,Face recognition using scattering wavelet under Illicit Drug Abuse variations,"Face Recognition using Scattering Wavelet under Illicit Drug Abuse Variations
+Prateekshit Pandey, Richa Singh, Mayank Vatsa
+fprateekshit12078, rsingh,
+IIIT-Delhi India"
+a6ce2f0795839d9c2543d64a08e043695887e0eb,Driver Gaze Region Estimation Without Using Eye Movement,"Driver Gaze Region Estimation
+Without Using Eye Movement
+Lex Fridman, Philipp Langhans, Joonbum Lee, and Bryan Reimer
+Massachusetts Institute of Technology (MIT)"
+a6ebe013b639f0f79def4c219f585b8a012be04f,Facial Expression Recognition Based on Hybrid Approach,"Facial Expression Recognition Based on Hybrid
+Approach
+Md. Abdul Mannan, Antony Lam, Yoshinori Kobayashi, and Yoshinori Kuno
+Graduate School of Science and Engineering, Saitama University,
+55 Shimo-Okubo, Sakura-ku, Saitama-shi, Saitama 338-8570, Japan
+E-mail"
+b97f694c2a111b5b1724eefd63c8d64c8e19f6c9,Group Affect Prediction Using Multimodal Distributions,"Group Affect Prediction Using Multimodal Distributions
+Saqib Nizam Shamsi
+Aspiring Minds
+Bhanu Pratap Singh
+Univeristy of Massachusetts, Amherst
+Manya Wadhwa
+Johns Hopkins University"
+b9d0774b0321a5cfc75471b62c8c5ef6c15527f5,Fishy Faces: Crafting Adversarial Images to Poison Face Authentication,"Fishy Faces: Crafting Adversarial Images to Poison Face Authentication
+Giuseppe Garofalo
+Vera Rimmer
+Tim Van hamme
+imec-DistriNet, KU Leuven
+imec-DistriNet, KU Leuven
+imec-DistriNet, KU Leuven
+Davy Preuveneers
+Wouter Joosen
+imec-DistriNet, KU Leuven
+imec-DistriNet, KU Leuven"
+b9cad920a00fc0e997fc24396872e03f13c0bb9c,Face liveness detection under bad illumination conditions,"FACE LIVENESS DETECTION UNDER BAD ILLUMINATION CONDITIONS
+Bruno Peixoto, Carolina Michelassi, and Anderson Rocha
+University of Campinas (Unicamp)
+Campinas, SP, Brazil"
+b908edadad58c604a1e4b431f69ac8ded350589a,Deep Face Feature for Face Alignment,"Deep Face Feature for Face Alignment
+Boyi Jiang, Juyong Zhang, Bailin Deng, Yudong Guo and Ligang Liu"
+b9f2a755940353549e55690437eb7e13ea226bbf,Unsupervised Feature Learning from Videos for Discovering and Recognizing Actions,"Unsupervised Feature Learning from Videos for Discovering and Recognizing Actions
+Carolina Redondo-Cabrera
+Roberto J. López-Sastre"
+b9cedd1960d5c025be55ade0a0aa81b75a6efa61,Inexact Krylov Subspace Algorithms for Large Matrix Exponential Eigenproblem from Dimensionality Reduction,"INEXACT KRYLOV SUBSPACE ALGORITHMS FOR LARGE
+MATRIX EXPONENTIAL EIGENPROBLEM FROM
+DIMENSIONALITY REDUCTION
+GANG WU∗, TING-TING FENG† , LI-JIA ZHANG‡ , AND MENG YANG§"
+b971266b29fcecf1d5efe1c4dcdc2355cb188ab0,On the Reconstruction of Face Images from Deep Face Templates.,"MAI et al.: ON THE RECONSTRUCTION OF FACE IMAGES FROM DEEP FACE TEMPLATES
+On the Reconstruction of Face Images from
+Deep Face Templates
+Guangcan Mai, Kai Cao, Pong C. Yuen∗, Senior Member, IEEE, and Anil K. Jain, Life Fellow, IEEE"
+a158c1e2993ac90a90326881dd5cb0996c20d4f3,Symmetry as an Intrinsically Dynamic Feature,"OPEN ACCESS
+ISSN 2073-8994
+Article
+Vito Di Gesu 1,2,†, Marco E. Tabacchi 1,3,* and Bertrand Zavidovique 4
+DMA, Università degli Studi di Palermo, via Archirafi 34, 90123 Palermo, Italy
+CITC, Università degli Studi di Palermo, via Archirafi 34, 90123 Palermo, Itlay
+Istituto Nazionale di Ricerche Demopolis, via Col. Romey 7, 91100 Trapani, Italy
+IEF, Université Paris IX–Orsay, Paris, France; E-Mail: (B.Z.)
+Deceased on 15 March 2009.
+* Author to whom correspondence should be addressed; E-Mail:
+Received: 4 March 2010; in revised form: 23 March 2010 / Accepted: 29 March 2010 /
+Published: 1 April 2010"
+a15d9d2ed035f21e13b688a78412cb7b5a04c469,Object Detection Using Strongly-Supervised Deformable Part Models,"Object Detection Using
+Strongly-Supervised Deformable Part Models
+Hossein Azizpour1 and Ivan Laptev2
+Computer Vision and Active Perception Laboratory (CVAP), KTH, Sweden
+INRIA, WILLOW, Laboratoire d’Informatique de l’Ecole Normale Superieure"
+a1b1442198f29072e907ed8cb02a064493737158,Crowdsourcing Facial Responses to Online Videos,"Crowdsourcing Facial Responses
+to Online Videos
+Daniel McDuff, Student Member, IEEE, Rana El Kaliouby, Member, IEEE, and
+Rosalind W. Picard, Fellow, IEEE"
+a15c728d008801f5ffc7898568097bbeac8270a4,ForgetIT Deliverable Template,"www.forgetit-project.eu
+ForgetIT
+Concise Preservation by Combining Managed Forgetting
+nd Contextualized Remembering
+Grant Agreement No. 600826
+Deliverable D4.4
+Work-package
+Deliverable
+Deliverable Leader
+Quality Assessor
+Dissemination level
+Delivery date in Annex I
+Actual delivery date
+Revisions
+Status
+Keywords
+Information Consolidation and Con-
+entration
+D4.4:
+Information analysis, consolidation"
+a1132e2638a8abd08bdf7fc4884804dd6654fa63,Real-Time Video Face Recognition for Embedded Devices,"Real-Time Video Face Recognition
+for Embedded Devices
+Gabriel Costache, Sathish Mangapuram, Alexandru
+Drimbarean, Petronel Bigioi and Peter Corcoran
+Tessera, Galway,
+Ireland
+. Introduction
+This  chapter  will  address  the  challenges  of  real-time  video  face  recognition  systems
+implemented  in  embedded  devices.  Topics  to  be  covered  include:  the  importance  and
+hallenges of video face recognition in real life scenarios, describing a general architecture of
+generic  video  face  recognition  system  and  a  working  solution  suitable  for  recognizing
+faces  in  real-time  using  low  complexity  devices.  Each  component  of  the  system  will  be
+described  together  with  the  system’s  performance  on  a  database  of  video  samples  that
+resembles real life conditions.
+. Video face recognition
+Face recognition remains a very active topic in computer vision and receives attention from
+large  community  of  researchers  in  that  discipline.  Many  reasons  feed  this  interest;  the
+main being  the wide range of commercial, law enforcement and security applications that
+require  authentication.  The  progress  made  in  recent  years  on  the  methods  and  algorithms
+for data processing as well as the availability of new technologies makes it easier to study"
+a14ae81609d09fed217aa12a4df9466553db4859,Face Identification Using Large Feature Sets,"REVISED VERSION, JUNE 2011
+Face Identiﬁcation Using Large Feature Sets
+William Robson Schwartz, Huimin Guo, Jonghyun Choi, and Larry S. Davis, Fellow, IEEE"
+a1f1120653bb1bd8bd4bc9616f85fdc97f8ce892,Latent Embeddings for Zero-Shot Classification,"Latent Embeddings for Zero-shot Classiﬁcation
+Yongqin Xian1, Zeynep Akata1, Gaurav Sharma1,2,∗, Quynh Nguyen3, Matthias Hein3 and Bernt Schiele1
+MPI for Informatics
+IIT Kanpur
+Saarland University"
+a1e97c4043d5cc9896dc60ae7ca135782d89e5fc,"Re-identification of Humans in Crowds using Personal, Social and Environmental Constraints","IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
+Re-identiﬁcation of Humans in Crowds using
+Personal, Social and Environmental Constraints
+Shayan Modiri Assari, Member, IEEE, Haroon Idrees, Member, IEEE, and Mubarak Shah, Fellow, IEEE"
+ef940b76e40e18f329c43a3f545dc41080f68748,A Face Recognition and Spoofing Detection Adapted to Visually- Impaired People,"Research Article                                                                                                                              Volume 7 Issue No.3
+ISSN XXXX XXXX © 2017 IJESC
+A Face Recognition and Spoofing Detection Adapted to Visually-
+Impaired People
+Rutuja R. Dengale1, Bhagyashri S. Deshmukh 2, Anuja R. Mahangade3, Shivani V. Ujja inkar4
+K.K Wagh Institute of Engineering and Education Research, Nashik, India
+Depart ment of Co mputer Engineering
+Abstrac t:
+According to estimates by the world Health organization, about 285 million people suffer fro m so me kind of v isual disabilit ies of
+which 39 million are  blind, resulting in  0.7 of the word population. As many v isual impaired peoples in  the word they are  unable
+to recognize the people who is standing in front of them and some peoples who have problem to re me mbe r na me of the person.
+They  can  easily  recognize   the  person  using  this  system.  A   co mputer  vision  technique  and  image  ana lysis  can  help  v isually
+the home using face identification and spoofing detection system. This system also provide feature to add newly  known people
+nd keep records of all peoples visiting their ho me.
+Ke ywor ds: face-recognition, spoofing detection, visually-impaired, system architecture.
+INTRODUCTION
+The  facia l  ana lysis  can  be  used  to  e xtract  very  useful  and
+relevant  information  in   order  to  help  people  with  visual
+impairment in several of  its tasks daily providing them with a
+greater  degree  of  autonomy  and  security.  Facia l  recognition"
+efd308393b573e5410455960fe551160e1525f49,Tracking Persons-of-Interest via Unsupervised Representation Adaptation,"Tracking Persons-of-Interest via
+Unsupervised Representation Adaptation
+Shun Zhang, Jia-Bin Huang, Jongwoo Lim, Yihong Gong, Jinjun Wang,
+Narendra Ahuja, and Ming-Hsuan Yang"
+ef230e3df720abf2983ba6b347c9d46283e4b690,QUIS-CAMPI: an annotated multi-biometrics data feed from surveillance scenarios,"Page 1 of 20
+QUIS-CAMPI: An Annotated Multi-biometrics Data Feed From
+Surveillance Scenarios
+João Neves1,*, Juan Moreno2, Hugo Proença3
+IT - Instituto de Telecomunicações, University of Beira Interior
+Department of Computer Science, University of Beira Interior
+IT - Instituto de Telecomunicações, University of Beira Interior"
+ef4ecb76413a05c96eac4c743d2c2a3886f2ae07,Modeling the importance of faces in natural images,"Modeling the Importance of Faces in Natural Images
+Jin B.a, Yildirim G.a, Lau C.a, Shaji A.a, Ortiz Segovia M.b and S¨usstrunk S.a
+EPFL, Lausanne, Switzerland;
+Oc´e, Paris, France"
+ef032afa4bdb18b328ffcc60e2dc5229cc1939bc,Attribute-enhanced metric learning for face retrieval,"Fang and Yuan EURASIP Journal on Image and Video
+Processing  (2018) 2018:44
+https://doi.org/10.1186/s13640-018-0282-x
+EURASIP Journal on Image
+nd Video Processing
+RESEARCH
+Open Access
+Attribute-enhanced metric learning for
+face retrieval
+Yuchun Fang*
+nd Qiulong Yuan"
+ef5531711a69ed687637c48930261769465457f0,Studio2Shop: from studio photo shoots to fashion articles,"Studio2Shop: from studio photo shoots to fashion articles
+Julia Lasserre1, Katharina Rasch1 and Roland Vollgraf
+Zalando Research, Muehlenstr. 25, 10243 Berlin, Germany
+Keywords:
+omputer vision, deep learning, fashion, item recognition, street-to-shop"
+ef559d5f02e43534168fbec86707915a70cd73a0,DeepInsight: Multi-Task Multi-Scale Deep Learning for Mental Disorder Diagnosis,"DING, HUO, HU, LU: DEEPINSIGHT
+DeepInsight: Multi-Task Multi-Scale Deep
+Learning for Mental Disorder Diagnosis
+Mingyu Ding1
+Yuqi Huo2
+Jun Hu2
+Zhiwu Lu1
+School of Information
+Renmin University of China
+Beijing, 100872, China
+Beijing Key Laboratory
+of Big Data Management
+nd Analysis Methods
+Beijing, 100872, China"
+efa08283656714911acff2d5022f26904e451113,Active Object Localization in Visual Situations,"Active Object Localization in Visual Situations
+Max H. Quinn, Anthony D. Rhodes, and Melanie Mitchell"
+ef999ab2f7b37f46445a3457bf6c0f5fd7b5689d,Improving face verification in photo albums by combining facial recognition and metadata with cross-matching,"Calhoun: The NPS Institutional Archive
+DSpace Repository
+Theses and Dissertations
+. Thesis and Dissertation Collection, all items
+017-12
+Improving face verification in photo albums by
+ombining facial recognition and metadata
+with cross-matching
+Bouthour, Khoubeib
+Monterey, California: Naval Postgraduate School
+http://hdl.handle.net/10945/56868
+Downloaded from NPS Archive: Calhoun"
+c32fb755856c21a238857b77d7548f18e05f482d,Multimodal Emotion Recognition for Human-Computer Interaction: A Survey,"Multimodal Emotion Recognition for Human-
+Computer Interaction: A Survey
+School of Computer and Communication Engineering, University of Science and Technology Beijing, 100083 Beijing, China.
+Michele Mukeshimana, Xiaojuan Ban, Nelson Karani, Ruoyi Liu"
+c3beae515f38daf4bd8053a7d72f6d2ed3b05d88,ACL 2014 52nd Annual Meeting of the Association for Computational Linguistics TACL Papers,"ACL201452ndAnnualMeetingoftheAssociationforComputationalLinguisticsTACLPapersJune23-25,2014Baltimore,Maryland,USA"
+c3dc4f414f5233df96a9661609557e341b71670d,Utterance independent bimodal emotion recognition in spontaneous communication,"Tao et al. EURASIP Journal on Advances in Signal Processing 2011, 2011:4
+http://asp.eurasipjournals.com/content/2011/1/4
+RESEARCH
+Utterance independent bimodal emotion
+recognition in spontaneous communication
+Jianhua Tao*, Shifeng Pan, Minghao Yang, Ya Li, Kaihui Mu and Jianfeng Che
+Open Access"
+c3b3636080b9931ac802e2dd28b7b684d6cf4f8b,Face Recognition via Local Directional Pattern,"International Journal of Security and Its Applications
+Vol. 7, No. 2, March, 2013
+Face Recognition via Local Directional Pattern
+Dong-Ju Kim*, Sang-Heon Lee and Myoung-Kyu Sohn
+Division of IT Convergence, Daegu Gyeongbuk Institute of Science & Technology
+50-1, Sang-ri, Hyeonpung-myeon, Dalseong-gun, Daegu, Korea."
+c398684270543e97e3194674d9cce20acaef3db3,Comparative Face Soft Biometrics for Human Identification,"Chapter 2
+Comparative Face Soft Biometrics for
+Human Identiﬁcation
+Nawaf Yousef Almudhahka, Mark S. Nixon and Jonathon S. Hare"
+c3285a1d6ec6972156fea9e6dc9a8d88cd001617,Extreme 3D Face Reconstruction: Seeing Through Occlusions,
+c3bcc4ee9e81ce9c5c0845f34e9992872a8defc0,A New Scheme for Image Recognition Using Higher-Order Local Autocorrelation and Factor Analysis,"MVA2005  IAPR  Conference on Machine VIsion Applications, May 16-18, 2005 Tsukuba Science City, Japan
+A New Scheme for Image Recognition Using Higher-Order Local
+Autocorrelation and Factor Analysis
+Naoyuki Nomotoy, Yusuke Shinoharay, Takayoshi Shirakiy, Takumi Kobayashiy, Nobuyuki Otsuy yyy
+yThe University of Tokyo
+Tokyo, Japan
+yyyAIST
+Tukuba, Japan
+f shiraki, takumi, otsug"
+c32383330df27625592134edd72d69bb6b5cff5c,Intrinsic Illumination Subspace for Lighting Insensitive Face Recognition,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 42, NO. 2, APRIL 2012
+Intrinsic Illumination Subspace for Lighting
+Insensitive Face Recognition
+Chia-Ping Chen and Chu-Song Chen, Member, IEEE"
+c32f04ccde4f11f8717189f056209eb091075254,Analysis and Synthesis of Behavioural Specific Facial Motion,"Analysis and Synthesis of Behavioural Speciﬁc
+Facial Motion
+Lisa Nanette Gralewski
+A dissertation submitted to the University of Bristol in accordance with the requirements
+for the degree of Doctor of Philosophy in the Faculty of Engineering, Department of
+Computer Science.
+February 2007
+71657 words"
+c30e4e4994b76605dcb2071954eaaea471307d80,Feature Selection for Emotion Recognition based on Random Forest,
+c37a971f7a57f7345fdc479fa329d9b425ee02be,A Novice Guide towards Human Motion Analysis and Understanding,"A Novice Guide towards Human Motion Analysis and Understanding
+Dr. Ahmed Nabil Mohamed"
+c3fb2399eb4bcec22723715556e31c44d086e054,Face recognition based on SIGMA sets of image features,"014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP)
+978-1-4799-2893-4/14/$31.00 ©2014 IEEE
+. INTRODUCTION"
+c37de914c6e9b743d90e2566723d0062bedc9e6a,Joint and Discriminative Dictionary Learning for Facial Expression Recognition,"©2016 Society for Imaging Science and Technology
+DOI: 10.2352/ISSN.2470-1173.2016.11.IMAWM-455
+Joint  and  Discriminative  Dictionary  Learning
+Expression Recognition
+for  Facial
+Sriram Kumar, Behnaz Ghoraani, Andreas Savakis"
+c4f1fcd0a5cdaad8b920ee8188a8557b6086c1a4,The Ignorant Led by the Blind: A Hybrid Human–Machine Vision System for Fine-Grained Categorization,"Int J Comput Vis (2014) 108:3–29
+DOI 10.1007/s11263-014-0698-4
+The Ignorant Led by the Blind: A Hybrid Human–Machine Vision
+System for Fine-Grained Categorization
+Steve Branson · Grant Van Horn · Catherine Wah ·
+Pietro Perona · Serge Belongie
+Received: 7 March 2013 / Accepted: 8 January 2014 / Published online: 20 February 2014
+© Springer Science+Business Media New York 2014"
+c43862db5eb7e43e3ef45b5eac4ab30e318f2002,Provable Self-Representation Based Outlier Detection in a Union of Subspaces,"Provable Self-Representation Based Outlier Detection in a Union of Subspaces
+Chong You, Daniel P. Robinson, Ren´e Vidal
+Johns Hopkins University, Baltimore, MD, 21218, USA"
+c4dcf41506c23aa45c33a0a5e51b5b9f8990e8ad,Understanding Activity: Learning the Language of Action,"Understanding Activity: Learning the Language of Action
+Randal Nelson and Yiannis Aloimonos
+Univ. of Rochester and Maryland
+.1 Overview
+Understanding observed activity is an important
+problem, both from the standpoint of practical applications,
+nd as a central issue in attempting to describe the
+phenomenon of intelligence. On the practical side, there are a
+large number of applications that would benefit from
+improved machine ability to analyze activity. The most
+prominent are various surveillance scenarios. The current
+emphasis on homeland security has brought this issue to the
+forefront, and resulted in considerable work on mostly low-
+level detection schemes. There are also applications in
+medical diagnosis and household assistants that, in the long
+run, may be even more important. In addition, there are
+numerous scientific projects, ranging from monitoring of
+weather conditions to observation of animal behavior that
+would be facilitated by automatic understanding of activity.
+From a scientific standpoint, understanding activity"
+c42a8969cd76e9f54d43f7f4dd8f9b08da566c5f,Towards Unconstrained Face Recognition Using 3D Face Model,"Towards Unconstrained Face Recognition
+Using 3D Face Model
+Zahid Riaz1, M. Saquib Sarfraz2 and Michael Beetz1
+Intelligent Autonomous Systems (IAS), Technical University of Munich, Garching
+Computer Vision Research Group, COMSATS Institute of Information
+Technology, Lahore
+Germany
+Pakistan
+. Introduction
+Over the last couple of decades, many commercial systems are available to identify human
+faces. However, face recognition is still an outstanding challenge against different kinds of
+real world variations especially facial poses, non-uniform lightings and facial expressions.
+Meanwhile the face recognition technology has extended its role from biometrics and security
+pplications to human robot interaction (HRI). Person identity is one of the key tasks while
+interacting with intelligent machines/robots, exploiting the non intrusive system security
+nd authentication of the human interacting with the system. This capability further helps
+machines to learn person dependent traits and interaction behavior to utilize this knowledge
+for tasks manipulation. In such scenarios acquired face images contain large variations which
+demands an unconstrained face recognition system.
+Fig. 1. Biometric analysis of past few years has been shown in ﬁgure showing the"
+eac6aee477446a67d491ef7c95abb21867cf71fc,A Survey of Sparse Representation: Algorithms and Applications,"JOURNAL
+A survey of sparse representation: algorithms and
+pplications
+Zheng Zhang, Student Member, IEEE, Yong Xu, Senior Member, IEEE,
+Jian Yang, Member, IEEE, Xuelong Li, Fellow, IEEE, and David Zhang, Fellow, IEEE"
+ea079334121a0ba89452036e5d7f8e18f6851519,Unsupervised incremental learning of deep descriptors from video streams,"UNSUPERVISED INCREMENTAL LEARNING OF DEEP DESCRIPTORS
+FROM VIDEO STREAMS
+Federico Pernici and Alberto Del Bimbo
+MICC – University of Florence"
+eac1b644492c10546a50f3e125a1f790ec46365f,"Chained Multi-stream Networks Exploiting Pose, Motion, and Appearance for Action Classification and Detection","Chained Multi-stream Networks Exploiting Pose, Motion, and Appearance for
+Action Classiﬁcation and Detection
+Mohammadreza Zolfaghari , Gabriel L. Oliveira, Nima Sedaghat, and Thomas Brox
+University of Freiburg
+Freiburg im Breisgau, Germany"
+ea482bf1e2b5b44c520fc77eab288caf8b3f367a,Flexible Orthogonal Neighborhood Preserving Embedding,Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
+eafda8a94e410f1ad53b3e193ec124e80d57d095,Observer-Based Measurement of Facial Expression With the Facial Action Coding System,"Jeffrey F. Cohn
+Zara Ambadar
+Paul Ekman
+Observer-Based Measurement of Facial Expression
+With the Facial Action Coding System
+Facial expression has been a focus of emotion research for over
+hundred years (Darwin, 1872/1998). It is central to several
+leading theories of emotion (Ekman, 1992; Izard, 1977;
+Tomkins, 1962) and has been the focus of at times heated
+debate about issues in emotion science (Ekman, 1973, 1993;
+Fridlund, 1992; Russell, 1994). Facial expression figures
+prominently in research on almost every aspect of emotion,
+including psychophysiology (Levenson, Ekman, & Friesen,
+990), neural bases (Calder et al., 1996; Davidson, Ekman,
+Saron, Senulis, & Friesen, 1990), development (Malatesta,
+Culver, Tesman, & Shephard, 1989; Matias & Cohn, 1993),
+perception (Ambadar, Schooler, & Cohn, 2005), social pro-
+esses (Hatfield, Cacioppo, & Rapson, 1992; Hess & Kirouac,
+000), and emotion disorder (Kaiser, 2002; Sloan, Straussa,
+Quirka, & Sajatovic, 1997), to name a few."
+ea85378a6549bb9eb9bcc13e31aa6a61b655a9af,Template Protection for PCA - LDA - based 3 D Face Recognition System,"Diplomarbeit
+Template Protection for PCA-LDA-based 3D
+Face Recognition System
+Daniel Hartung
+Technische Universität Darmstadt
+Fachbereich Informatik
+Fachgebiet Graphisch-Interaktive Systeme
+Fraunhoferstraße 5
+64283 Darmstadt
+Betreuer: Dipl.-Ing. Xuebing Zhou
+Prüfer: Prof. Dr. techn. Dieter W. Fellner"
+ea2ee5c53747878f30f6d9c576fd09d388ab0e2b,Viola-Jones Based Detectors: How Much Affects the Training Set?,"Viola-Jones based Detectors: How much affects
+the Training Set?
+Modesto Castrill´on-Santana, Daniel Hern´andez-Sosa, Javier Lorenzo-Navarro
+SIANI
+Edif. Central del Parque Cient´ıﬁco Tecnol´ogico
+Universidad de Las Palmas de Gran Canaria
+5017 - Spain"
+e1f790bbedcba3134277f545e56946bc6ffce48d,Image Retrieval Using Attribute Enhanced Sparse Code Words,"International Journal of Innovative Research in Science,
+Engineering and Technology
+(An ISO 3297: 2007 Certified Organization)
+Vol. 3, Issue 5, May 2014
+Sparse Code Words
+ISSN: 2319-8753
+Image Retrieval Using Attribute Enhanced
+M.Balaganesh1, N.Arthi2
+Associate Professor, Department of Computer Science and Engineering, SRV Engineering College, sembodai, india1
+P.G. Student, Department of Computer Science and Engineering, SRV Engineering College, sembodai, India 2"
+e1ab3b9dee2da20078464f4ad8deb523b5b1792e,Pre-Training CNNs Using Convolutional Autoencoders,"Pre-Training CNNs Using Convolutional
+Autoencoders
+Maximilian Kohlbrenner
+TU Berlin
+Russell Hofmann
+TU Berlin
+Sabbir Ahmmed
+TU Berlin
+Youssef Kashef
+TU Berlin"
+e19ebad4739d59f999d192bac7d596b20b887f78,Learning Gating ConvNet for Two-Stream based Methods in Action Recognition,"Learning Gating ConvNet for Two-Stream based Methods in Action
+Recognition
+Jiagang Zhu1,2, Wei Zou1, Zheng Zhu1,2"
+e1f6e2651b7294951b5eab5d2322336af1f676dc,Emotional Avatars: Appearance Augmentation and Animation based on Facial Expression Analysis,"Appl. Math. Inf. Sci. 9, No. 2L, 461-469 (2015)
+Applied Mathematics & Information Sciences
+An International Journal
+http://dx.doi.org/10.12785/amis/092L21
+Emotional Avatars: Appearance Augmentation and
+Animation based on Facial Expression Analysis
+Taehoon Cho, Jin-Ho Choi, Hyeon-Joong Kim and Soo-Mi Choi∗
+Department of Computer Science and Engineering, Sejong University, 98 Gunja, Gwangjin, Seoul 143-747, Korea
+Received: 22 May 2014, Revised: 23 Jul. 2014, Accepted: 24 Jul. 2014
+Published online: 1 Apr. 2015"
+e1d726d812554f2b2b92cac3a4d2bec678969368,Human Action Recognition Bases on Local Action Attributes,"J Electr Eng Technol.2015; 10(?): 30-40
+http://dx.doi.org/10.5370/JEET.2015.10.2.030
+ISSN(Print)
+975-0102
+ISSN(Online)  2093-7423
+Human Action Recognition Bases on Local Action Attributes
+Jing  Zhang*, Hong Liu*, Weizhi Nie† Lekha Chaisorn**, Yongkang Wong**
+nd Mohan S Kankanhalli**"
+e1e6e6792e92f7110e26e27e80e0c30ec36ac9c2,Ranking with Adaptive Neighbors,"TSINGHUA SCIENCE AND TECHNOLOGY
+ISSNll1007-0214
+0?/?? pp???–???
+DOI: 10.26599/TST.2018.9010000
+Volume 1, Number 1, Septembelr 2018
+Ranking with Adaptive Neighbors
+Muge Li, Liangyue Li, and Feiping Nie∗"
+cd9666858f6c211e13aa80589d75373fd06f6246,A Novel Time Series Kernel for Sequences Generated by LTI Systems,"A Novel Time Series Kernel for
+Sequences Generated by LTI Systems
+Liliana Lo Presti, Marco La Cascia
+V.le delle Scienze Ed.6, DIID, Universit´a degli studi di Palermo, Italy"
+cd596a2682d74bdfa7b7160dd070b598975e89d9,Mood Detection: Implementing a facial expression recognition system,"Mood Detection: Implementing a facial
+expression recognition system
+Neeraj Agrawal, Rob Cosgriff and Ritvik Mudur
+. Introduction
+Facial  expressions  play  a  significant  role  in  human  dialogue.  As  a  result,  there  has  been
+onsiderable work done on the recognition of emotional expressions and the  application of this
+research  will  be  beneficial  in  improving  human-machine  dialogue.  One  can  imagine  the
+improvements  to  computer  interfaces,  automated  clinical  (psychological)  research  or  even
+interactions between humans and autonomous robots.
+Unfortunately,  a  lot  of  the  literature  does  not  focus  on  trying  to  achieve  high  recognition  rates
+cross  multiple  databases.  In  this  project  we  develop  our  own  mood  detection  system  that
+ddresses  this  challenge.  The  system  involves  pre-processing  image  data  by  normalizing  and
+pplying a simple mask, extracting certain (facial) features using PCA and Gabor filters and then
+using SVMs for classification and recognition of expressions. Eigenfaces for each class are used
+to  determine  class-specific  masks  which  are  then  applied  to  the  image  data  and  used  to  train
+multiple,  one  against  the  rest,  SVMs.  We  find  that  simply  using  normalized  pixel  intensities
+works well with such an approach.
+Figure 1 – Overview of our system design
+. Image pre-processing
+We performed pre-processing on the images used to train and test our algorithms as follows:"
+cda4fb9df653b5721ad4fe8b4a88468a410e55ec,Gabor wavelet transform and its application,"Gabor wavelet transform and its application
+Wei-lun Chao R98942073"
+cd3005753012409361aba17f3f766e33e3a7320d,Multilinear Biased Discriminant Analysis: A Novel Method for Facial Action Unit Representation,"Multilinear Biased Discriminant Analysis: A Novel Method for Facial
+Action Unit Representation
+Mahmoud Khademi†, Mehran Safayani†and Mohammad T. Manzuri-Shalmani†
+: Sharif University of Tech., DSP Lab,"
+cd7a7be3804fd217e9f10682e0c0bfd9583a08db,Women also Snowboard: Overcoming Bias in Captioning Models,"Women also Snowboard:
+Overcoming Bias in Captioning Models
+Lisa Anne Hendricks * 1 Kaylee Burns * 1 Kate Saenko 2 Trevor Darrell 1 Anna Rohrbach 1"
+ccfcbf0eda6df876f0170bdb4d7b4ab4e7676f18,A Dynamic Appearance Descriptor Approach to Facial Actions Temporal Modeling,"JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JUNE 2011
+A Dynamic Appearance Descriptor Approach to
+Facial Actions Temporal Modelling
+Bihan Jiang, Student Member, IEEE, Michel Valstar, Member, IEEE, Brais Martinez, Member, IEEE, and
+Maja Pantic, Fellow, IEEE"
+cc3c273bb213240515147e8be68c50f7ea22777c,Gaining Insight Into Films Via Topic Modeling & Visualization,"Gaining Insight Into Films
+Via Topic Modeling & Visualization
+MISHA RABINOVICH, MFA
+YOGESH GIRDHAR, PHD
+KEYWORDS Collaboration, computer vision, cultural
+nalytics, economy of abundance, interactive data
+visualization
+We moved beyond misuse when the software actually
+ecame useful for film analysis with the addition of audio
+nalysis, subtitle analysis, facial recognition, and topic
+modeling. Using multiple types of visualizations and
+back-and-fourth workflow between people and AI
+we arrived at an approach for cultural analytics that
+an be used to review and develop film criticism. Finally,
+we present ways to apply these techniques to Database
+Cinema and other aspects of film and video creation.
+PROJECT DATE 2014
+URL http://misharabinovich.com/soyummy.html"
+cc8e378fd05152a81c2810f682a78c5057c8a735,Expression Invariant Face Recognition System based on Topographic Independent Component Analysis and Inner Product Classifier,"International Journal of Computer Sciences and Engineering    Open Access
+Research Paper                                          Volume-5, Issue-12                                          E-ISSN: 2347-2693
+Expression Invariant Face Recognition System based on Topographic
+Independent Component Analysis and Inner Product Classifier
+Aruna Bhat
+Department of Electrical Engineering, IIT Delhi, New Delhi, India
+*Corresponding Author:
+Available online at: www.ijcseonline.org
+Received: 07/Nov/2017, Revised: 22/Nov/2017, Accepted: 14/Dec/2017, Published: 31/Dec/2017"
+ccf43c62e4bf76b6a48ff588ef7ed51e87ddf50b,Nutraceuticals and Cosmeceuticals for Human Beings–An Overview,"American Journal of Food Science and Health
+Vol. 2, No. 2, 2016, pp. 7-17
+http://www.aiscience.org/journal/ajfsh
+ISSN: 2381-7216 (Print); ISSN: 2381-7224 (Online)
+Nutraceuticals and Cosmeceuticals for Human
+Beings–An Overview
+R. Ramasubramania Raja*
+Department of Pharmacognosy, Narayana Pharmacy College, Nellore, India"
+cc31db984282bb70946f6881bab741aa841d3a7c,Learning Grimaces by Watching TV,"ALBANIE, VEDALDI: LEARNING GRIMACES BY WATCHING TV
+Learning Grimaces by Watching TV
+Samuel Albanie
+http://www.robots.ox.ac.uk/~albanie
+Andrea Vedaldi
+http://www.robots.ox.ac.uk/~vedaldi
+Engineering Science Department
+Univeristy of Oxford
+Oxford, UK"
+cc91001f9d299ad70deb6453d55b2c0b967f8c0d,Performance Enhancement of Face Recognition in Smart TV Using Symmetrical Fuzzy-Based Quality Assessment,"OPEN ACCESS
+ISSN 2073-8994
+Article
+Performance Enhancement of Face Recognition in Smart TV
+Using Symmetrical Fuzzy-Based Quality Assessment
+Yeong Gon Kim, Won Oh Lee, Ki Wan Kim, Hyung Gil Hong and Kang Ryoung Park *
+Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu,
+Seoul 100-715, Korea; E-Mails: (Y.G.K.); (W.O.L.);
+(K.W.K.); (H.G.H.)
+*  Author to whom correspondence should be addressed; E-Mail:
+Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735.
+Academic Editor: Christopher Tyler
+Received: 31 March 2015 / Accepted: 21 August 2015 / Published: 25 August 2015"
+cc96eab1e55e771e417b758119ce5d7ef1722b43,An Empirical Study of Recent Face Alignment Methods,"An Empirical Study of Recent
+Face Alignment Methods
+Heng Yang, Xuhui Jia, Chen Change Loy and Peter Robinson"
+e64b683e32525643a9ddb6b6af8b0472ef5b6a37,Face Recognition and Retrieval in Video,"Face Recognition and Retrieval in Video
+Caifeng Shan"
+e6b45d5a86092bbfdcd6c3c54cda3d6c3ac6b227,Pairwise Relational Networks for Face Recognition,"Pairwise Relational Networks for Face
+Recognition
+Bong-Nam Kang1[0000−0002−6818−7532], Yonghyun Kim2[0000−0003−0038−7850],
+nd Daijin Kim1,2[0000−0002−8046−8521]
+Department of Creative IT Engineering, POSTECH, Korea
+Department of Computer Science and Engineering, POSTECH, Korea"
+e6865b000cf4d4e84c3fe895b7ddfc65a9c4aaec,"Tobias Siebenlist , Kathrin Knautz Chapter 15 . The critical role of the cold - start problem and incentive systems in emotional Web 2 . 0 services","Tobias Siebenlist, Kathrin Knautz
+Chapter 15. The critical role of the
+old-start problem and incentive systems
+in emotional Web 2.0 services"
+e6d689054e87ad3b8fbbb70714d48712ad84dc1c,Robust Facial Feature Tracking,"Robust Facial Feature Tracking
+Fabrice Bourel, Claude C. Chibelushi, Adrian A. Low
+School of Computing, Staffordshire University
+Stafford ST18 0DG"
+e6dc1200a31defda100b2e5ddb27fb7ecbbd4acd,Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction,"Flexible Manifold Embedding: A Framework
+for Semi-Supervised and Unsupervised
+Dimension Reduction
+Feiping Nie, Dong Xu, Member, IEEE, Ivor Wai-Hung Tsang, and Changshui Zhang, Member, IEEE
+, the linear regression function ("
+e6e5a6090016810fb902b51d5baa2469ae28b8a1,Energy-Efficient Deep In-memory Architecture for NAND Flash Memories,"Title
+Energy-Efficient Deep In-memory Architecture for NAND
+Flash Memories
+Archived version
+Accepted manuscript: the content is same as the published
+paper but without the final typesetting by the publisher
+Published version
+Published paper
+Authors (contact)
+0.1109/ISCAS.2018.8351458"
+e6178de1ef15a6a973aad2791ce5fbabc2cb8ae5,Improving Facial Landmark Detection via a Super-Resolution Inception Network,"Improving Facial Landmark Detection via a
+Super-Resolution Inception Network
+Martin Knoche, Daniel Merget, Gerhard Rigoll
+Institute for Human-Machine Communication
+Technical University of Munich, Germany"
+f9784db8ff805439f0a6b6e15aeaf892dba47ca0,"Comparing the performance of Emotion-Recognition Implementations in OpenCV, Cognitive Services, and Google Vision APIs","Comparing the performance of Emotion-Recognition Implementations
+in OpenCV, Cognitive Services, and Google Vision APIs
+LUIS ANTONIO BELTRÁN PRIETO, ZUZANA KOMÍNKOVÁ OPLATKOVÁ
+Department of Informatics and Artificial Intelligence
+Tomas Bata University in Zlín
+Nad Stráněmi 4511, 76005, Zlín
+CZECH REPUBLIC"
+f935225e7811858fe9ef6b5fd3fdd59aec9abd1a,Spatiotemporal dynamics and connectivity pattern differences between centrally and peripherally presented faces.,"www.elsevier.com/locate/ynimg
+Spatiotemporal dynamics and connectivity pattern differences
+etween centrally and peripherally presented faces
+Lichan Liu and Andreas A. Ioannides*
+Laboratory for Human Brain Dynamics, RIKEN Brain Science Institute (BSI), 2-1 Hirosawa, Wakoshi, Saitama, 351-0198, Japan
+Received 4 May 2005; revised 26 January 2006; accepted 6 February 2006
+Available online 24 March 2006
+Most neuroimaging studies on face processing used centrally presented
+images with a relatively large visual field. Images presented in this way
+ctivate widespread striate and extrastriate areas and make it difficult
+to study spatiotemporal dynamics and connectivity pattern differences
+from various parts of the visual field. Here we studied magneto-
+encephalographic responses in humans to centrally and peripherally
+presented faces for testing the hypothesis that processing of visual
+stimuli with facial expressions of emotions depends on where the
+stimuli are presented in the visual field. Using our tomographic and
+statistical parametric mapping analyses, we identified occipitotemporal
+reas activated by face stimuli more than by control conditions. V1/V2
+ctivity was significantly stronger for lower than central and upper
+visual field presentation. Fusiform activity, however, was significantly"
+f93606d362fcbe62550d0bf1b3edeb7be684b000,Nearest Neighbor Classifier Based on Nearest Feature Decisions,"The Computer Journal Advance Access published February 1, 2012
+© The Author 2012. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.
+For Permissions, please email:
+doi:10.1093/comjnl/bxs001
+Nearest Neighbor Classiﬁer Based
+on Nearest Feature Decisions
+Alex Pappachen James1,∗ and Sima Dimitrijev2
+Machine Intelligence Group, School of Computer Science, Indian Institute of Information Technology and
+Queensland Micro- and Nanotechnology Centre and Grifﬁth School of Engineering, Grifﬁth University,
+Management, Kerala, India
+Nathan, Australia
+Corresponding author:
+High feature dimensionality of realistic datasets adversely affects the recognition accuracy of nearest
+neighbor (NN) classiﬁers. To address this issue, we introduce a nearest feature classiﬁer that shifts
+the NN concept from the global-decision level to the level of individual features. Performance
+omparisons with 12 instance-based classiﬁers on 13 benchmark University of California Irvine
+lassiﬁcation datasets show average improvements of 6 and 3.5% in recognition accuracy and
+rea under curve performance measures, respectively. The statistical signiﬁcance of the observed
+performance improvements is veriﬁed by the Friedman test and by the post hoc Bonferroni–Dunn
+test. In addition, the application of the classiﬁer is demonstrated on face recognition databases, a"
+f997a71f1e54d044184240b38d9dc680b3bbbbc0,Deep Cross Modal Learning for Caricature Verification and Identification(CaVINet),"Deep Cross Modal Learning for Caricature Verification and
+Identification(CaVINet)
+https://lsaiml.github.io/CaVINet/
+Jatin Garg∗
+Indian Institute of Technology Ropar
+Himanshu Tolani∗
+Indian Institute of Technology Ropar
+Skand Vishwanath Peri∗
+Indian Institute of Technology Ropar
+Narayanan C Krishnan
+Indian Institute of Technology Ropar"
+f9d1f12070e5267afc60828002137af949ff1544,Maximum Entropy Binary Encoding for Face Template Protection,"Maximum Entropy Binary Encoding for Face Template Protection
+Rohit Kumar Pandey
+Yingbo Zhou
+Bhargava Urala Kota
+Venu Govindaraju
+University at Buffalo, SUNY
+{rpandey, yingbozh, buralako,"
+f0cee87e9ecedeb927664b8da44b8649050e1c86,Image Ordinal Classification and Understanding: Grid Dropout with Masking Label,"label:(1, 0, 1, 0, 1, 1, 1, 1, 1)Masking label:(0, 1, 1, 1, 0, 1, 1, 1, 1)Entire imageInput imageNeuron dropout’s gradCAMGrid dropout’s gradCAMFig.1.Above:imageordinalclassiﬁcationwithrandomlyblackoutpatches.Itiseasyforhumantorecognizetheageregardlessofthemissingpatches.Themaskinglabelisalsousefultoimageclassiﬁcation.Bottom:griddropout’sgrad-CAMisbetterthanthatofneurondropout.Thatistosay,griddropoutcanhelplearningfeaturerepresentation.problem[1].Withtheproliferationofconvolutionalneuralnetwork(CNN),workshavebeencarriedoutonordinalclas-siﬁcationwithCNN[1][2][3].Thoughgoodperformanceshavebeenloggedwithmoderndeeplearningapproaches,therearetwoproblemsinimageordinalclassiﬁcation.Ononehand,theamountofordinaltrainingdataisverylim-itedwhichprohibitstrainingcomplexmodelsproperly,andtomakemattersworse,collectinglargetrainingdatasetwithordinallabelisdifﬁcult,evenharderthanlabellinggenericdataset.Therefore,insufﬁcienttrainingdataincreasestheriskofoverﬁtting.Ontheotherhand,lessstudiesareconductedtounderstandwhatdeepmodelshavelearnedonordinaldata978-1-5386-1737-3/18/$31.00c(cid:13)2018IEEE"
+f0f4f16d5b5f9efe304369120651fa688a03d495,Temporal Generative Adversarial Nets,"Temporal Generative Adversarial Nets
+Masaki Saito∗
+Eiichi Matsumoto∗
+Preferred Networks inc., Japan
+{msaito,"
+f0ae807627f81acb63eb5837c75a1e895a92c376,Facial Landmark Detection using Ensemble of Cascaded Regressions,"International Journal of Emerging Engineering Research and Technology
+Volume 3, Issue 12, December 2015, PP 128-133
+ISSN 2349-4395 (Print) & ISSN 2349-4409 (Online)
+Facial  Landmark  Detection  using  Ensemble  of  Cascaded
+Regressions
+Martin Penev1*, Ognian Boumbarov2
+Faculty of Telecommunications, Technical University, Sofia, Bulgaria
+Faculty of Telecommunications, Technical University, Sofia, Bulgaria"
+f0a3f12469fa55ad0d40c21212d18c02be0d1264,Sparsity Sharing Embedding for Face Verification,"Sparsity Sharing Embedding for Face
+Veriﬁcation
+Donghoon Lee, Hyunsin Park, Junyoung Chung,
+Youngook Song, and Chang D. Yoo
+Department of Electrical Engineering, KAIST, Daejeon, Korea"
+f7b422df567ce9813926461251517761e3e6cda0,Face aging with conditional generative adversarial networks,"FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS
+Grigory Antipov(cid:63)†
+Moez Baccouche(cid:63)
+Jean-Luc Dugelay†
+(cid:63) Orange Labs, 4 rue Clos Courtel, 35512 Cesson-S´evign´e, France
+Eurecom, 450 route des Chappes, 06410 Biot, France"
+f79c97e7c3f9a98cf6f4a5d2431f149ffacae48f,Title On color texture normalization for active appearance models,"Provided by the author(s) and NUI Galway in accordance with publisher policies. Please cite the published
+version when available.
+Title
+On color texture normalization for active appearance models
+Author(s)
+Ionita, Mircea C.; Corcoran, Peter M.; Buzuloiu, Vasile
+Publication
+009-05-12
+Publication
+Information
+Ionita, M. C., Corcoran, P., & Buzuloiu, V. (2009). On Color
+Texture Normalization for Active Appearance Models. Image
+Processing, IEEE Transactions on, 18(6), 1372-1378.
+Publisher
+Link to
+publisher's
+version
+http://dx.doi.org/10.1109/TIP.2009.2017163
+Item record
+http://hdl.handle.net/10379/1350"
+f7dcadc5288653ec6764600c7c1e2b49c305dfaa,Interactive Image Search with Attributes by,"Copyright
+Adriana Ivanova Kovashka"
+f7de943aa75406fe5568fdbb08133ce0f9a765d4,Biometric Identification and Surveillance1,"Project 1.5: Human Identification at a Distance - Hornak, Adjeroh, Cukic, Gautum, & Ross
+Project 1.5
+Biometric Identification and Surveillance1
+Don Adjeroh, Bojan Cukic, Arun Ross – West Virginia University
+Year 5 Deliverable
+Technical Report:
+Research Challenges in Biometrics
+Indexed biography of relevant biometric research literature
+Donald Adjeroh, Bojan Cukic, Arun Ross
+April, 2014
+""This research was supported by the United States Department of Homeland Security through the National Center for Border Security
+nd Immigration (BORDERS) under grant number 2008-ST-061-BS0002. However, any opinions, findings, and conclusions or
+recommendations in this document are those of the authors and do not necessarily reflect views of the United States Department of
+Homeland Security."""
+f75852386e563ca580a48b18420e446be45fcf8d,Illumination Invariant Face Recognition,"ILLUMINATION INVARIANT FACE RECOGNITION
+Raghuraman Gopalan
+ENEE 631: Digital Image and Video Processing
+Instructor: Dr. K. J. Ray Liu
+Term Project - Spring 2006
+INTRODUCTION
+The  performance  of  the  Face  Recognition  algorithms  is  severely  affected  by  two
+important  factors:  the  change  in  Pose  and  Illumination  conditions  of  the  subjects.  The
+hanges in Illumination conditions of the subjects can be so drastic that, the variation in
+lighting will be of the similar order as that of the variation due to the change in subjects
+[1] and this can result in misclassification.
+For example, in the acquisition of the face of a person from a real time video, the
+mbient  conditions  will  cause  different  lighting  variations  on  the  tracked  face.  Some
+examples  of  images  with  different  illumination  conditions  are  shown  in  Fig.  1.  In  this
+project, we study some algorithms that are capable of performing Illumination Invariant
+Face Recognition. The performances of these algorithms were compared on the CMU-
+Illumination dataset [13], by using the entire face as the input to the algorithms. Then, a
+model  of  dividing  the  face  into  four  regions  is  proposed  and  the  performance  of  the
+lgorithms on these new features is analyzed."
+f77c9bf5beec7c975584e8087aae8d679664a1eb,Local Deep Neural Networks for Age and Gender Classification,"Local Deep Neural Networks for Age and Gender Classiﬁcation
+Zukang Liao, Stavros Petridis, Maja Pantic
+March 27, 2017"
+e8686663aec64f4414eba6a0f821ab9eb9f93e38,Improving shape-based face recognition by means of a supervised discriminant Hausdorff distance,"IMPROVING SHAPE-BASED FACE RECOGNITION BY MEANS OF A SUPERVISED
+DISCRIMINANT HAUSDORFF DISTANCE
+J.L. Alba
+, A. Pujol
+, A. L´opez
+nd J.J. Villanueva
+Signal Theory and Communications Department, University of Vigo, Spain
+Centre de Visio per Computador, Universitat Autonoma de Barcelona, Spain
+Digital Pointer MVT"
+e8fdacbd708feb60fd6e7843b048bf3c4387c6db,Deep Learning,"Deep Learning
+Andreas Eilschou
+Hinnerup Net A/S
+www.hinnerup.net
+July 4, 2014
+Introduction
+Deep learning is a topic in the ﬁeld of artiﬁcial intelligence (AI) and is a relatively
+new research area although based on the popular artiﬁcial neural networks (supposedly
+mirroring brain function). With the development of the perceptron in the 1950s and
+960s by Frank RosenBlatt, research began on artiﬁcial neural networks. To further
+mimic the architectural depth of the brain, researchers wanted to train a deep multi-
+layer neural network – this, however, did not happen until Geoffrey Hinton in 2006
+introduced Deep Belief Networks [1].
+Recently, the topic of deep learning has gained public interest. Large web companies such
+s Google and Facebook have a focused research on AI and an ever increasing amount
+of compute power, which has led to researchers ﬁnally being able to produce results
+that are of interest to the general public. In July 2012 Google trained a deep learning
+network on YouTube videos with the remarkable result that the network learned to
+recognize humans as well as cats [6], and in January this year Google successfully used
+deep learning on Street View images to automatically recognize house numbers with"
+e8b2a98f87b7b2593b4a046464c1ec63bfd13b51,CMS-RCNN: Contextual Multi-Scale Region-based CNN for Unconstrained Face Detection,"CMS-RCNN: Contextual Multi-Scale
+Region-based CNN for Unconstrained Face
+Detection
+Chenchen Zhu*, Student, IEEE, Yutong Zheng*, Student, IEEE,
+Khoa Luu, Member, IEEE, Marios Savvides, Senior Member, IEEE"
+e85a255a970ee4c1eecc3e3d110e157f3e0a4629,Fusing Hierarchical Convolutional Features for Human Body Segmentation and Clothing Fashion Classification,"Fusing Hierarchical Convolutional Features for Human Body Segmentation and
+Clothing Fashion Classiﬁcation
+Zheng Zhang, Chengfang Song, Qin Zou∗
+School of Computer Science, Wuhan University, P.R. China
+E-mails: {zhangzheng, songchf,"
+e8d1b134d48eb0928bc999923a4e092537e106f6,Weighted Multi-region Convolutional Neural Network for Action Recognition with Low-latency Online Prediction,"WEIGHTED MULTI-REGION CONVOLUTIONAL NEURAL NETWORK FOR ACTION
+RECOGNITION WITH LOW-LATENCY ONLINE PREDICTION
+Yunfeng Wang(cid:63), Wengang Zhou(cid:63), Qilin Zhang†, Xiaotian Zhu(cid:63), Houqiang Li(cid:63)
+(cid:63)University of Science and Technology of China, Hefei, Anhui, China
+HERE Technologies, Chicago, Illinois, USA"
+e8c6c3fc9b52dffb15fe115702c6f159d955d308,Linear Subspace Learning for Facial Expression Analysis,"Linear Subspace Learning for
+Facial Expression Analysis
+Caifeng Shan
+Philips Research
+The Netherlands
+. Introduction
+Facial  expression,  resulting  from  movements  of  the  facial  muscles,  is  one  of  the  most
+powerful, natural, and immediate means for human beings to communicate their emotions
+nd intentions. Some examples of facial expressions are shown in Fig. 1. Darwin (1872) was
+the  first  to  describe  in  detail  the  specific  facial  expressions  associated  with  emotions  in
+nimals  and  humans;  he  argued  that  all  mammals  show  emotions  reliably  in  their  faces.
+Psychological  studies  (Mehrabian,  1968;  Ambady  &  Rosenthal,  1992)  indicate  that  facial
+expressions, with other non-verbal cues, play a major and fundamental role in face-to-face
+ommunication.
+Fig. 1. Facial expressions of George W. Bush.
+Machine  analysis  of  facial  expressions,  enabling  computers  to  analyze  and  interpret  facial
+expressions  as  humans  do,  has  many  important  applications  including  intelligent  human-
+omputer  interaction,  computer  animation,  surveillance  and  security,  medical  diagnosis,
+law  enforcement,  and  awareness  system  (Shan,  2007).  Driven  by  its  potential  applications
+nd  theoretical  interests  of  cognitive  and  psychological  scientists,  automatic  facial"
+fab83bf8d7cab8fe069796b33d2a6bd70c8cefc6,Draft: Evaluation Guidelines for Gender Classification and Age Estimation,"Draft: Evaluation Guidelines for Gender
+Classiﬁcation and Age Estimation
+Tobias Gehrig, Matthias Steiner, Hazım Kemal Ekenel
+{tobias.gehrig,
+July 1, 2011
+Introduction
+In previous research on gender classiﬁcation and age estimation did not use a
+standardised evaluation procedure. This makes comparison the different ap-
+proaches dif‌f‌icult.
+Thus we propose here a benchmarking and evaluation protocol for gender
+lassiﬁcation as well as age estimation to set a common ground for future re-
+search in these two areas.
+The evaluations are designed such that there is one scenario under controlled
+labratory conditions and one under uncontrolled real life conditions.
+The datasets were selected with the criteria of being publicly available for
+research purposes.
+File lists for the folds corresponding to the individual benchmarking proto-
+ols will be provided over our website at http://face.cs.kit.edu/befit. We
+will provide two kinds of folds for each of the tasks and conditions: one set of
+folds using the whole dataset and one set of folds using a reduced dataset, which"
+fa08a4da5f2fa39632d90ce3a2e1688d147ece61,Supplementary material for “ Unsupervised Creation of Parameterized Avatars ” 1 Summary of Notations,"Supplementary material for
+“Unsupervised Creation of Parameterized Avatars”
+Summary of Notations
+Tab. 1 itemizes the symbols used in the submission. Fig. 2,3,4 of the main text illustrate many of these
+symbols.
+DANN results
+Fig. 1 shows side by side samples of the original image and the emoji generated by the method of [1].
+As can be seen, these results do not preserve the identity very well, despite considerable effort invested in
+ﬁnding suitable architectures.
+Multiple Images Per Person
+Following [4], we evaluate the visual quality that is obtained per person and not just per image, by testing
+TOS on the Facescrub dataset [3]. For each person p, we considered the set of their images Xp, and selected
+the emoji that was most similar to their source image, i.e., the one for which:
+||f (x) − f (e(c(G(x))))||.
+rgmin
+Fig. 2 depicts the results obtained by this selection method on sample images form the Facescrub dataset
+(it is an extension of Fig. 7 of the main text). The ﬁgure also shows, for comparison, the DTN [4] result for
+the same image.
+Detailed Architecture of the Various Networks
+In this section we describe the architectures of the networks used in for the emoji and avatar experiments."
+fa24bf887d3b3f6f58f8305dcd076f0ccc30272a,Interval Insensitive Loss for Ordinal Classification,"JMLR: Workshop and Conference Proceedings 39:189–204, 2014
+ACML 2014
+Interval Insensitive Loss for Ordinal Classiﬁcation
+Kostiantyn Antoniuk
+Vojtˇech Franc
+V´aclav Hlav´aˇc
+Center for Machine Perception, Department of Cybernetics, Faculty of Electrical Engineering, Czech
+Technical University in Prague, Technick´a 2, 166 27 Prague 6 Czech Republic
+Editor: Dinh Phung and Hang Li"
+fafe69a00565895c7d57ad09ef44ce9ddd5a6caa,Gaussian Mixture Models for Human Face Recognition under Illumination Variations,"Applied Mathematics, 2012, 3, 2071-2079
+http://dx.doi.org/10.4236/am.2012.312A286 Published Online December 2012 (http://www.SciRP.org/journal/am)
+Gaussian Mixture Models for Human Face Recognition
+under Illumination Variations
+Information Systems and Decision Sciences Department, Mihaylo College of Business and Economics,
+California State University, Fullerton, USA
+Email:
+Sinjini Mitra
+Received August 18, 2012; revised September 18, 2012; accepted September 25, 2012"
+faca1c97ac2df9d972c0766a296efcf101aaf969,Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition,"Sympathy for the Details: Dense Trajectories and Hybrid
+Classification Architectures for Action Recognition
+C´esar Roberto de Souza1,2, Adrien Gaidon1, Eleonora Vig3, Antonio Manuel L´opez2
+Computer Vision Group, Xerox Research Center Europe, Meylan, France
+Centre de Visi´o per Computador, Universitat Aut`onoma de Barcelona, Bellaterra, Spain
+German Aerospace Center, Wessling, Germany
+{cesar.desouza,"
+fab60b3db164327be8588bce6ce5e45d5b882db6,Maximum A Posteriori Estimation of Distances Between Deep Features in Still-to-Video Face Recognition,"Maximum A Posteriori Estimation of Distances
+Between Deep Features in Still-to-Video Face
+Recognition
+Andrey V. Savchenko
+National Research University Higher School of Economics
+Laboratory of Algorithms and Technologies for Network Analysis,
+6 Rodionova St., Nizhny Novgorod, Russia
+Natalya S. Belova
+National Research University Higher School of Economics
+0 Myasnitskaya St., Moscow, Russia
+September 2, 2018"
+fad895771260048f58d12158a4d4d6d0623f4158,Audio-visual emotion recognition for natural human-robot interaction,"Audio-Visual Emotion
+Recognition For Natural
+Human-Robot Interaction
+Dissertation zur Erlangung des akademischen Grades
+Doktor der Ingenieurwissenschaften (Dr.-Ing.)
+vorgelegt von
+Ahmad Rabie
+n der Technischen Fakultät der Universität Bielefeld
+5. März 2010"
+ff8315c1a0587563510195356c9153729b533c5b,Zapping Index:Using Smile to Measure Advertisement Zapping Likelihood,"Zapping Index:Using Smile to Measure
+Advertisement Zapping Likelihood
+Songfan Yang, Member, IEEE, Mehran Kafai, Member, IEEE,
+Le An, Student Member, IEEE, and Bir Bhanu, Fellow, IEEE"
+ff44d8938c52cfdca48c80f8e1618bbcbf91cb2a,Towards Video Captioning with Naming: A Novel Dataset and a Multi-modal Approach,"Towards Video Captioning with Naming: a
+Novel Dataset and a Multi-Modal Approach
+Stefano Pini, Marcella Cornia, Lorenzo Baraldi, Rita Cucchiara
+Dipartimento di Ingegneria “Enzo Ferrari”
+Universit`a degli Studi di Modena e Reggio Emilia"
+fffefc1fb840da63e17428fd5de6e79feb726894,Fine-Grained Age Estimation in the wild with Attention LSTM Networks,"Fine-Grained Age Estimation in the wild with
+Attention LSTM Networks
+Ke Zhang, Member, IEEE, Na Liu, Xingfang Yuan, Student Member, IEEE, Xinyao Guo, Ce Gao,
+nd Zhenbing Zhao Member, IEEE,"
+ff398e7b6584d9a692e70c2170b4eecaddd78357,Title of dissertation : FACE RECOGNITION AND VERIFICATION IN UNCONSTRAINED ENVIRIONMENTS,
+ffd81d784549ee51a9b0b7b8aaf20d5581031b74,Performance Analysis of Retina and DoG Filtering Applied to Face Images for Training Correlation Filters,"Performance Analysis of Retina and DoG
+Filtering Applied to Face Images for Training
+Correlation Filters
+Everardo Santiago Ram(cid:19)(cid:16)rez1, Jos(cid:19)e (cid:19)Angel Gonz(cid:19)alez Fraga1, Omar (cid:19)Alvarez
+Xochihua1, Everardo Gutierrez L(cid:19)opez1, and Sergio Omar Infante Prieto2
+Facultad de Ciencias, Universidad Aut(cid:19)onoma de Baja California,
+Carretera Transpeninsular Tijuana-Ensenada, N(cid:19)um. 3917, Colonia Playitas,
+Ensenada, Baja California, C.P. 22860
+{everardo.santiagoramirez,angel_fraga,
+Facultad de Ingenier(cid:19)(cid:16)a, Arquitectura y Dise~no, Universidad Aut(cid:19)onoma de Baja
+California, Carretera Transpeninsular Tijuana-Ensenada, N(cid:19)um. 3917, Colonia
+Playitas, Ensenada, Baja California, C.P. 22860"
+ff01bc3f49130d436fca24b987b7e3beedfa404d,Fuzzy System-Based Face Detection Robust to In-Plane Rotation Based on Symmetrical Characteristics of a Face,"Article
+Fuzzy System-Based Face Detection Robust to
+In-Plane Rotation Based on Symmetrical
+Characteristics of a Face
+Hyung Gil Hong, Won Oh Lee, Yeong Gon Kim, Ki Wan Kim, Dat Tien Nguyen and
+Kang Ryoung Park *
+Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu,
+Seoul 100-715, Korea; (H.G.H.); (W.O.L.); (Y.G.K.);
+(K.W.K.); (D.T.N.)
+* Correspondence: Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735
+Academic Editor: Angel Garrido
+Received: 15 June 2016; Accepted: 29 July 2016; Published: 3 August 2016"
+ffc9d6a5f353e5aec3116a10cf685294979c63d9,Eigenphase-based face recognition: a comparison of phase- information extraction methods,"Eigenphase-based face recognition: a comparison of phase-
+information extraction methods
+Slobodan Ribarić, Marijo Maračić
+Faculty of Electrical Engineering and Computing,
+University of Zagreb, Unska 3, 10 000 Zagreb
+E-mail:"
+ff8ef43168b9c8dd467208a0b1b02e223b731254,BreakingNews: Article Annotation by Image and Text Processing,"BreakingNews: Article Annotation by
+Image and Text Processing
+Arnau Ramisa*, Fei Yan*, Francesc Moreno-Noguer,
+nd Krystian Mikolajczyk"
+ffcbedb92e76fbab083bb2c57d846a2a96b5ae30,Sparse Dictionary Learning and Domain Adaptation for Face and Action Recognition,
+ff7bc7a6d493e01ec8fa2b889bcaf6349101676e,Facial expression recognition with spatiotemporal local descriptors_v3.rtf,"Facial expression recognition with spatiotemporal local
+descriptors
+Guoying Zhao, Matti Pietikäinen
+Machine  Vision  Group,  Infotech  Oulu  and  Department  of  Electrical  and
+Information Engineering, P. O. Box 4500 FI-90014 University of Oulu, Finland
+{gyzhao,"
+ff46c41e9ea139d499dd349e78d7cc8be19f936c,A Novel Method for Movie Character Identification and its Facial Expression Recognition,"International Journal of Modern Engineering Research (IJMER)
+www.ijmer.com              Vol.3, Issue.3, May-June. 2013 pp-1339-1342             ISSN: 2249-6645
+A Novel Method for Movie Character Identification and its
+Facial Expression Recognition
+M. Dharmateja Purna, 1 N. Praveen2
+M.Tech, Sri Sunflower College of Engineering & Technology, Lankapalli
+Asst. Professor, Dept. of ECE, Sri Sunflower College of Engineering & Technology, Lankapalli"
+ff5dd6f96e108d8233220cc262bc282229c1a582,Robust Facial Marks Detection Method Using AAM And SURF,"Ziaul Haque Choudhury, K.M. Mehata / International Journal of Engineering Research and
+Applications (IJERA) ISSN: 2248-9622   www.ijera.com
+Vol. 2, Issue 6, November- December 2012, pp.708-715
+Robust Facial Marks Detection Method Using AAM And SURF
+Ziaul Haque Choudhury, K.M. Mehata
+Dept. of Information Technology, B.S. Abdur Rahman University, Chennai-48, India
+Dept. of Computer Science & Engineering, B.S. Abdur Rahman University, Chennai-48, India"
+c588c89a72f89eed29d42f34bfa5d4cffa530732,Attributes2Classname: A Discriminative Model for Attribute-Based Unsupervised Zero-Shot Learning,"Attributes2Classname: A discriminative model for attribute-based
+unsupervised zero-shot learning
+Berkan Demirel1,3, Ramazan Gokberk Cinbis2, Nazli Ikizler-Cinbis3
+HAVELSAN Inc., 2Bilkent University, 3Hacettepe University"
+c50d73557be96907f88b59cfbd1ab1b2fd696d41,Semiconductor sidewall shape estimation,"JournalofElectronicImaging13(3),474–485(July2004).
+Semiconductor sidewall shape estimation
+Philip R. Bingham
+Jeffery R. Price
+Kenneth W. Tobin
+Thomas P. Karnowski
+Oak Ridge National Laboratory
+Oak Ridge, Tennessee 37831-6010
+E-mail:"
+c574c72b5ef1759b7fd41cf19a9dcd67e5473739,"COGNIMUSE: a multimodal video database annotated with saliency, events, semantics and emotion with application to summarization","Zlatintsi et al. EURASIP Journal on Image and Video Processing  (2017) 2017:54
+DOI 10.1186/s13640-017-0194-1
+EURASIP Journal on Image
+nd Video Processing
+RESEARCH
+Open Access
+COGNIMUSE: a multimodal video
+database annotated with saliency, events,
+semantics and emotion with application to
+summarization
+Athanasia Zlatintsi1*
+Niki Efthymiou1, Katerina Pastra4, Alexandros Potamianos1 and Petros Maragos1
+, Petros Koutras1, Georgios Evangelopoulos2, Nikolaos Malandrakis3,"
+c5a561c662fc2b195ff80d2655cc5a13a44ffd2d,Using Language to Learn Structured Appearance Models for Image Annotation,"Using Language to Learn Structured Appearance
+Models for Image Annotation
+Michael Jamieson, Student Member, IEEE, Afsaneh Fazly, Suzanne Stevenson, Sven Dickinson, Member, IEEE,
+Sven Wachsmuth, Member, IEEE"
+c5c379a807e02cab2e57de45699ababe8d13fb6d,Facial Expression Recognition Using Sparse Representation,"Facial Expression Recognition Using Sparse Representation
+SHIQING ZHANG 1, XIAOMING ZHAO 2, BICHENG LEI 1
+School of Physics and Electronic Engineering
+Taizhou University
+Taizhou 318000
+CHINA
+2Department of Computer Science
+Taizhou University
+Taizhou 318000
+CHINA"
+c5ea084531212284ce3f1ca86a6209f0001de9d1,Audio-visual speech processing for multimedia localisation,"Audio-Visual Speech Processing for
+Multimedia Localisation
+Matthew Aaron Benatan
+Submitted in accordance with the requirements
+for the degree of Doctor of Philosophy
+The University of Leeds
+School of Computing
+September 2016"
+c5844de3fdf5e0069d08e235514863c8ef900eb7,A Study on Similarity Computations in Template Matching Technique for Identity Verification,"Lam S K et al. / (IJCSE) International Journal on Computer Science and Engineering
+Vol. 02, No. 08, 2010, 2659-2665
+A Study on Similarity Computations in Template
+Matching Technique for Identity Verification
+Lam, S. K., Yeong, C. Y., Yew, C. T., Chai, W. S., Suandi, S. A.
+Intelligent Biometric Group, School of Electrical and Electronic Engineering
+Engineering Campus, Universiti Sains Malaysia
+4300 Nibong Tebal, Pulau Pinang, MALAYSIA
+Email:"
+c590c6c171392e9f66aab1bce337470c43b48f39,Emotion Recognition by Machine Learning Algorithms using Psychophysiological Signals,"Emotion Recognition by Machine Learning Algorithms using
+Psychophysiological Signals
+Eun-Hye Jang, 2Byoung-Jun Park, 3Sang-Hyeob Kim, 4Jin-Hun Sohn
+, 2, 3 BT Convergence Technology Research Department, Electronics and Telecommunications
+Research Institute, 138 Gajeongno, Yuseong-gu, Daejeon, 305-700, Republic of Korea,
+*4Department of Psychology/Brain Research Institute, Chungnam National University 220,
+Gung-dong, Yuseong-gu, Daejeon, 305-765, Republic of Korea,"
+c2c3ff1778ed9c33c6e613417832505d33513c55,"Multimodal Biometric Person Authentication Using Fingerprint, Face Features","Multimodal Biometric Person Authentication
+Using Fingerprint, Face Features
+Tran Binh Long1, Le Hoang Thai2, and Tran Hanh1
+Department of Computer Science, University of Lac Hong 10 Huynh Van Nghe,
+DongNai 71000, Viet Nam
+Department of Computer Science, Ho Chi Minh City University of Science
+27 Nguyen Van Cu, HoChiMinh 70000, Viet Nam"
+c27f64eaf48e88758f650e38fa4e043c16580d26,Title of the proposed research project: Subspace analysis using Locality Preserving Projection and its applications for image recognition,"Title of the proposed research project: Subspace analysis using Locality Preserving
+Projection and its applications for image recognition
+Research area: Data manifold learning for pattern recognition
+Contact Details:
+Name: Gitam C Shikkenawis
+Email Address:
+University:  Dhirubhai  Ambani  Institute  of  Information  and  Communication  Technology
+(DA-IICT), Gandhinagar."
+c220f457ad0b28886f8b3ef41f012dd0236cd91a,Crystal Loss and Quality Pooling for Unconstrained Face Verification and Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
+Crystal Loss and Quality Pooling for
+Unconstrained Face Veriﬁcation and Recognition
+Rajeev Ranjan, Member, IEEE, Ankan Bansal, Hongyu Xu, Member, IEEE,
+Swami Sankaranarayanan, Member, IEEE, Jun-Cheng Chen, Member, IEEE,
+Carlos D Castillo, Member, IEEE, and Rama Chellappa, Fellow, IEEE"
+c254b4c0f6d5a5a45680eb3742907ec93c3a222b,A Fusion-based Gender Recognition Method Using Facial Images,"A Fusion-based Gender Recognition Method
+Using Facial Images
+Benyamin Ghojogh, Saeed Bagheri Shouraki, Hoda Mohammadzade*, Ensieh Iranmehr"
+c2e6daebb95c9dfc741af67464c98f1039127627,Efficient Measuring of Facial Action Unit Activation Intensities using Active Appearance Models,"MVA2013 IAPR International Conference on Machine Vision Applications, May 20-23, 2013, Kyoto, JAPAN
+Ef‌f‌icient Measuring of Facial Action Unit Activation Intensities
+using Active Appearance Models
+Daniel Haase1, Michael Kemmler1, Orlando Guntinas-Lichius2, Joachim Denzler1
+Computer Vision Group, Friedrich Schiller University of Jena, Germany
+Department of Otolaryngology, University Hospital Jena, Germany"
+f6f06be05981689b94809130e251f9e4bf932660,An Approach to Illumination and Expression Invariant Multiple Classifier Face Recognition,"An Approach to Illumination and Expression Invariant
+International Journal of Computer Applications (0975 – 8887)
+Volume 91 – No.15, April 2014
+Multiple Classifier Face Recognition
+Dalton Meitei Thounaojam
+National Institute of Technology
+Silchar
+Assam: 788010
+India
+Hidangmayum Saxena Devi
+National Institute of Technology
+Silchar
+Assam: 788010
+India
+Romesh Laishram
+Manipur Institute of Technology
+Imphal West: 795001
+India"
+f6ca29516cce3fa346673a2aec550d8e671929a6,Algorithm for Face Matching Using Normalized Cross - Correlation,"International Journal of Engineering and Advanced Technology (IJEAT)
+ISSN: 2249 – 8958, Volume-2, Issue-4, April 2013
+Algorithm for Face Matching Using Normalized
+Cross-Correlation
+C. Saravanan, M. Surender"
+f67a73c9dd1e05bfc51219e70536dbb49158f7bc,A Gaussian Mixture Model for Classifying the Human Age using DWT and Sammon Map,"Journal of Computer Science 10 (11): 2292-2298, 2014
+ISSN: 1549-3636
+© 2014 Nithyashri and Kulanthaivel, This open access article is distributed under a Creative Commons Attribution
+(CC-BY) 3.0 license
+A GAUSSIAN MIXTURE MODEL FOR CLASSIFYING THE
+HUMAN AGE USING DWT AND SAMMON MAP
+J. Nithyashri and 2G. Kulanthaivel
+Department of Computer Science and Engineering, Sathyabama University, Chennai, India
+Department of Electronics Engineering, NITTTR, Chennai, India
+Received 2014-05-08; Revised 2014-05-23; Accepted 2014-11-28"
+f6c70635241968a6d5fd5e03cde6907022091d64,Measuring Deformations and Illumination Changes in Images with Applications to Face Recognition,
+f6ce34d6e4e445cc2c8a9b8ba624e971dd4144ca,Cross-Label Suppression: A Discriminative and Fast Dictionary Learning With Group Regularization,"Cross-label Suppression: A Discriminative and Fast
+Dictionary Learning with Group Regularization
+Xiudong Wang and Yuantao Gu∗
+April 24, 2017"
+f6fa97fbfa07691bc9ff28caf93d0998a767a5c1,K2-means for Fast and Accurate Large Scale Clustering,"k2-means for fast and accurate large scale clustering
+Eirikur Agustsson
+Computer Vision Lab
+D-ITET
+ETH Zurich
+Radu Timofte
+Computer Vision Lab
+D-ITET
+ETH Zurich
+Luc Van Gool
+ESAT, KU Leuven
+D-ITET, ETH Zurich"
+f6cf2108ec9d0f59124454d88045173aa328bd2e,Robust User Identification Based on Facial Action Units Unaffected by Users' Emotions,"Robust user identiﬁcation based on facial action units
+unaffected by users’ emotions
+Ricardo Buettner
+Aalen University, Germany"
+f68f20868a6c46c2150ca70f412dc4b53e6a03c2,Differential Evolution to Optimize Hidden Markov Models Training: Application to Facial Expression Recognition,"Differential Evolution to Optimize
+Hidden Markov Models Training:
+Application to Facial Expression
+Recognition
+Khadoudja Ghanem, Amer Draa, Elvis Vyumvuhore and
+Ars`ene Simbabawe
+MISC Laboratory, Constantine 2 University, Constantine, Algeria
+The base system in this paper uses Hidden Markov
+Models (HMMs) to model dynamic relationships among
+facial features in facial behavior interpretation and un-
+derstanding field. The input of HMMs is a new set
+of derived features from geometrical distances obtained
+from detected and automatically tracked facial points.
+Numerical data representation which is in the form of
+multi-time series is transformed to a symbolic repre-
+sentation in order to reduce dimensionality, extract the
+most pertinent information and give a meaningful repre-
+sentation to humans. The main problem of the use of
+HMMs is that the training is generally trapped in local
+minima, so we used the Differential Evolution (DE)"
+e9ed17fd8bf1f3d343198e206a4a7e0561ad7e66,Cognitive Learning for Social Robot through Facial Expression from Video Input,"International Journal of Enhanced Research in Science Technology & Engineering, ISSN: 2319-7463
+Vol. 3 Issue 1, January-2014, pp: (362-365), Impact Factor: 1.252, Available online at: www.erpublications.com
+Cognitive Learning for Social Robot through
+Facial Expression from Video Input
+Neeraj Rai1, Deepak Rai2
+Department of Automation & Robotics, 2Department of Computer Science & Engg.
+,2Ajay Kumar Garg Engineering College, Ghaziabad, UP, India"
+e988be047b28ba3b2f1e4cdba3e8c94026139fcf,Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition,"Multi-Task Convolutional Neural Network for
+Pose-Invariant Face Recognition
+Xi Yin and Xiaoming Liu Member, IEEE,"
+e9d43231a403b4409633594fa6ccc518f035a135,Deformable Part Models with CNN Features,"Deformable Part Models with CNN Features
+Pierre-Andr´e Savalle1, Stavros Tsogkas1,2, George Papandreou3, Iasonas
+Kokkinos1,2
+Ecole Centrale Paris,2 INRIA, 3TTI-Chicago (cid:63)"
+e9fcd15bcb0f65565138dda292e0c71ef25ea8bb,Analysing Facial Regions for Face Recognition Using Forensic Protocols,"Repositorio Institucional de la Universidad Autónoma de Madrid
+https://repositorio.uam.es
+Esta es la versión de autor de la comunicación de congreso publicada en:
+This is an author produced version of a paper published in:
+Highlights on Practical Applications of Agents and Multi-Agent Systems:
+International Workshops of PAAMS. Communications in Computer and
+Information Science, Volumen 365. Springer, 2013. 223-230
+DOI:    http://dx.doi.org/10.1007/978-3-642-38061-7_22
+Copyright:  © 2013 Springer-Verlag
+El acceso a la versión del editor puede requerir la suscripción del recurso
+Access to the published version may require subscription"
+e9363f4368b04aeaa6d6617db0a574844fc59338,BenchIP: Benchmarking Intelligence Processors,"BENCHIP: Benchmarking Intelligence
+Processors
+Jinhua Tao1, Zidong Du1,2, Qi Guo1,2, Huiying Lan1, Lei Zhang1
+Shengyuan Zhou1, Lingjie Xu3, Cong Liu4, Haifeng Liu5, Shan Tang6
+Allen Rush7,Willian Chen7, Shaoli Liu1,2, Yunji Chen1, Tianshi Chen1,2
+ICT CAS,2Cambricon,3Alibaba Infrastructure Service, Alibaba Group
+IFLYTEK,5JD,6RDA Microelectronics,7AMD"
+f16a605abb5857c39a10709bd9f9d14cdaa7918f,Fast greyscale road sign model matching and recognition,"Fast greyscale road sign model matching
+nd recognition
+Sergio Escalera and Petia Radeva
+Centre de Visió per Computador
+Edifici O – Campus UAB, 08193 Bellaterra, Barcelona, Catalonia, Spain"
+f1aa120fb720f6cfaab13aea4b8379275e6d40a2,InverseFaceNet: Deep Single-Shot Inverse Face Rendering From A Single Image,"InverseFaceNet: Deep Single-Shot Inverse Face Rendering From A Single Image
+Hyeongwoo Kim1
+Justus Thies2
+Max-Planck-Institute for Informatics
+Michael Zollhöfer1
+Christian Richardt3
+University of Erlangen-Nuremberg 3 University of Bath
+Christian Theobalt1
+Ayush Tewari1
+Figure 1. Our single-shot deep inverse face renderer InverseFaceNet obtains a high-quality geometry, reflectance and illumination estimate
+from just a single input image. We jointly recover the face pose, shape, expression, reflectance and incident scene illumination. From left to
+right: input photo, our estimated face model, its geometry, and the pointwise Euclidean error compared to Garrido et al. [14]."
+f1ba2fe3491c715ded9677862fea966b32ca81f0,Face Tracking and Recognition in Videos : HMM Vs KNN,"ISSN: 2321-7782 (Online)
+Volume 1, Issue 7, December 2013
+International Journal of Advance Research in
+Computer Science and Management Studies
+Research Paper
+Available online at: www.ijarcsms.com
+Face Tracking and Recognition in Videos:
+HMM Vs KNN
+Madhumita R. Baviskar
+Assistant Professor
+Department of Computer Engineering
+MIT College of Engineering (Pune University)
+Pune - India"
+f1d090fcea63d9f9e835c49352a3cd576ec899c1,Single-hidden Layer Feedforward Neual network training using class geometric information,"Iosifidis, A., Tefas, A., & Pitas, I. (2015). Single-Hidden Layer Feedforward
+Neual Network Training Using Class Geometric Information. In . J. J.
+Merelo, A. Rosa, J. M. Cadenas, A. Dourado, K. Madani, & J. Filipe (Eds.),
+Computational Intelligence: International Joint Conference, IJCCI 2014
+Rome, Italy, October 22-24, 2014 Revised Selected Papers. (Vol. III, pp.
+51-364). (Studies in Computational Intelligence; Vol. 620). Springer. DOI:
+0.1007/978-3-319-26393-9_21
+Peer reviewed version
+Link to published version (if available):
+0.1007/978-3-319-26393-9_21
+Link to publication record in Explore Bristol Research
+PDF-document
+University of Bristol - Explore Bristol Research
+General rights
+This document is made available in accordance with publisher policies. Please cite only the published
+version using the reference above. Full terms of use are available:
+http://www.bristol.ac.uk/pure/about/ebr-terms.html"
+f113aed343bcac1021dc3e57ba6cc0647a8f5ce1,A Survey on Mining of Weakly Labeled Web Facial Images and Annotation,"International Journal of Science and Research (IJSR)
+ISSN (Online): 2319-7064
+Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611
+A Survey on Mining of Weakly Labeled Web Facial
+Images and Annotation
+Tarang Boharupi1, Pranjali Joshi2
+Pune Institute of Computer Technology, Pune, India
+Professor, Pune Institute of Computer Technology, Pune, India
+the  proposed  system  which"
+f19777e37321f79e34462fc4c416bd56772031bf,Literature Review of Image Compression Algorithm,"International Journal of Scientific & Engineering Research, Volume 3, Issue 6, June-2012                                                                                         1
+ISSN 2229-5518
+Literature Review of Image Compression Algorithm
+Dr. B. Chandrasekhar
+Padmaja.V.K
+email:                                                           email::
+Jawaharlal Technological University, Anantapur"
+f19ab817dd1ef64ee94e94689b0daae0f686e849,Blickrichtungsunabhängige Erkennung von Personen in Bild- und Tiefendaten,"TECHNISCHE UNIVERSIT¨AT M ¨UNCHEN
+Lehrstuhl f¨ur Mensch-Maschine-Kommunikation
+Blickrichtungsunabh¨angige Erkennung von
+Personen in Bild- und Tiefendaten
+Andre St¨ormer
+Vollst¨andiger Abdruck der von der Fakult¨at f¨ur Elektrotechnik und Informationstechnik
+der Technischen Universit¨at M¨unchen zur Erlangung des akademischen Grades eines
+Doktor-Ingenieurs (Dr.-Ing.)
+genehmigten Dissertation.
+Vorsitzender:
+Univ.-Prof. Dr.-Ing. Thomas Eibert
+Pr¨ufer der Dissertation:
+. Univ.-Prof. Dr.-Ing. habil. Gerhard Rigoll
+. Univ.-Prof. Dr.-Ing. Horst-Michael Groß,
+Technische Universit¨at Ilmenau
+Die Dissertation wurde am 16.06.2009 bei der Technischen Universit¨at M¨unchen einge-
+reicht und durch die Fakult¨at f¨ur Elektrotechnik und Informationstechnik am 30.10.2009
+ngenommen."
+e76798bddd0f12ae03de26b7c7743c008d505215,Joint Max Margin and Semantic Features for Continuous Event Detection in Complex Scenes,
+e7cac91da51b78eb4a28e194d3f599f95742e2a2,"Positive Feeling, Negative Meaning: Visualizing the Mental Representations of In-Group and Out-Group Smiles","RESEARCH ARTICLE
+Positive Feeling, Negative Meaning:
+Visualizing the Mental Representations of In-
+Group and Out-Group Smiles
+Andrea Paulus1☯*, Michaela Rohr1☯, Ron Dotsch2,3, Dirk Wentura1
+Saarland University, Saarbrücken, Germany, 2 Utrecht University, Utrecht, the Netherlands,
+Behavioural Science Institute, Radboud University, Nijmegen, the Netherlands
+☯ These authors contributed equally to this work."
+e78394213ae07b682ce40dc600352f674aa4cb05,Expression-invariant three-dimensional face recognition,"Expression-invariant three-dimensional face recognition
+Alexander M. Bronstein
+Email:
+Michael M. Bronstein
+Ron Kimmel
+Computer Science Department,
+Technion – Israel Institute of Technology,
+Haifa 32000, Israel
+One of the hardest problems in face recognition is dealing with facial expressions. Finding an
+expression-invariant representation of the face could be a remedy for this problem. We suggest
+treating faces as deformable surfaces in the context of Riemannian geometry, and propose to ap-
+proximate facial expressions as isometries of the facial surface. This way, we can deﬁne geometric
+invariants of a given face under different expressions. One such invariant is constructed by iso-
+metrically embedding the facial surface structure into a low-dimensional flat space. Based on this
+pproach, we built an accurate three-dimensional face recognition system that is able to distinguish
+etween identical twins under various facial expressions. In this chapter we show how under the
+near-isometric model assumption, the dif‌f‌icult problem of face recognition in the presence of facial
+expressions can be solved in a relatively simple way.
+0.1 Introduction
+It is well-known that some characteristics or behavior patterns of the human body are strictly"
+e7b6887cd06d0c1aa4902335f7893d7640aef823,Modelling of Facial Aging and Kinship: A Survey,"Modelling of Facial Aging and Kinship: A Survey
+Markos Georgopoulos, Yannis Panagakis, and Maja Pantic,"
+cbca355c5467f501d37b919d8b2a17dcb39d3ef9,Super-resolution of Very Low Resolution Faces from Videos,"CANSIZOGLU, JONES: SUPER-RESOLUTION OF VERY LR FACES FROM VIDEOS
+Super-resolution of Very Low-Resolution
+Faces from Videos
+Esra Ataer-Cansizoglu
+Michael Jones
+Mitsubishi Electric Research Labs
+(MERL)
+Cambridge, MA, USA"
+cbcf5da9f09b12f53d656446fd43bc6df4b2fa48,Face Recognition using Gray level Co-occurrence Matrix and Snap Shot Method of the Eigen Face,"ISSN: 2277-3754
+ISO 9001:2008 Certified
+International Journal of Engineering and Innovative Technology (IJEIT)
+Volume 2, Issue 6, December 2012
+Face Recognition using Gray level Co-occurrence
+Matrix and Snap Shot Method of the Eigen Face
+Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University, Kanchipuram, India
+M. Madhu, R. Amutha
+SSN College of Engineering, Chennai, India"
+cb004e9706f12d1de83b88c209ac948b137caae0,Face Aging Effect Simulation Using Hidden Factor Analysis Joint Sparse Representation,"Face Aging Effect Simulation using Hidden Factor
+Analysis Joint Sparse Representation
+Hongyu Yang, Student Member, IEEE, Di Huang, Member, IEEE, Yunhong Wang, Member, IEEE, Heng Wang,
+nd Yuanyan Tang, Fellow, IEEE"
+cb08f679f2cb29c7aa972d66fe9e9996c8dfae00,Action Understanding with Multiple Classes of Actors,"JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014
+Action Understanding
+with Multiple Classes of Actors
+Chenliang Xu, Member, IEEE, Caiming Xiong, and Jason J. Corso, Senior Member, IEEE"
+cb84229e005645e8623a866d3d7956c197f85e11,Disambiguating Visual Verbs,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. X, NO. X, MONTH 201X
+Disambiguating Visual Verbs
+Spandana Gella, Frank Keller, and Mirella Lapata"
+cbe859d151466315a050a6925d54a8d3dbad591f,Gaze shifts as dynamical random sampling,"GAZE SHIFTS AS DYNAMICAL RANDOM SAMPLING
+Giuseppe Boccignone
+Mario Ferraro
+Dipartimento di Scienze dell’Informazione
+Universit´a di Milano
+Via Comelico 39/41
+0135 Milano, Italy"
+f842b13bd494be1bbc1161dc6df244340b28a47f,An Improved Face Recognition Technique Based on Modular Multi-directional Two-dimensional Principle Component Analysis Approach,"An Improved Face Recognition Technique Based
+on Modular Multi-directional Two-dimensional
+Principle Component Analysis Approach
+Department of    Physics and Electronic Engineering, Hanshan Normal University, Chaozhou, 521041, China
+Xiaoqing Dong
+Department of    Physics and Electronic Engineering, Hanshan Normal University, Chaozhou, 521041, China
+Email:
+Hongcai Chen
+Email:"
+f8c94afd478821681a1565d463fc305337b02779,Design and Implementation of Robust Face Recognition System for Uncontrolled Pose and Illumination Changes,"www.semargroup.org,
+www.ijsetr.com
+ISSN 2319-8885
+Vol.03,Issue.25
+September-2014,
+Pages:5079-5085
+Design and Implementation of Robust Face Recognition System for
+Uncontrolled Pose and Illumination Changes
+VIJAYA BHASKAR TALARI
+, VENKATESWARLU PRATTI
+PG Scholar, Dept of ECE, LITAM, JNTUK, Andhrapradesh, India, Email:
+Assistant Professor, Dept of ECE, LITAM, JNTUK, Andhrapradesh, India, Email:"
+f8ec92f6d009b588ddfbb47a518dd5e73855547d,Extreme Learning Machine Ensemble Using Bagging for Facial Expression Recognition,"J Inf Process Syst, Vol.10, No.3, pp.443~458, September 2014
+ISSN 1976-913X (Print)
+ISSN 2092-805X (Electronic)
+Extreme Learning Machine Ensemble Using
+Bagging for Facial Expression Recognition
+Deepak Ghimire* and Joonwhoan Lee*"
+f8ed5f2c71e1a647a82677df24e70cc46d2f12a8,Artificial Neural Network Design and Parameter Optimization for Facial Expressions Recognition,"International Journal of Scientific & Engineering Research, Volume 2, Issue 12, December-2011                                                                                         1
+ISSN 2229-5518
+Artificial Neural Network Design and Parameter
+Optimization for Facial Expressions Recognition
+Ammar A. Alzaydi"
+f8f872044be2918de442ba26a30336d80d200c42,Facial Emotion Recognition Techniques : A Survey,"IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 03, 2015 | ISSN (online): 2321-0613
+Facial Emotion Recognition Techniques: A Survey
+Namita Rathore1 Rohit Miri2
+,2Department of Computer Science and Engineering
+,2Dr C V Raman Institute of Science and Technology
+defense
+systems,
+surveillance"
+f8a5bc2bd26790d474a1f6cc246b2ba0bcde9464,"KDEF-PT: Valence, Emotional Intensity, Familiarity and Attractiveness Ratings of Angry, Neutral, and Happy Faces","ORIGINAL RESEARCH
+published: 19 December 2017
+doi: 10.3389/fpsyg.2017.02181
+KDEF-PT: Valence, Emotional
+Intensity, Familiarity and
+Attractiveness Ratings of Angry,
+Neutral, and Happy Faces
+Margarida V. Garrido* and Marília Prada
+Instituto Universitário de Lisboa (ISCTE-IUL), CIS – IUL, Lisboa, Portugal
+The Karolinska Directed Emotional Faces (KDEF)
+is one of the most widely used
+human facial expressions database. Almost a decade after the original validation study
+(Goeleven et al., 2008), we present subjective rating norms for a sub-set of 210 pictures
+which depict 70 models (half female) each displaying an angry, happy and neutral facial
+expressions. Our main goals were to provide an additional and updated validation
+to this database, using a sample from a different nationality (N = 155 Portuguese
+students, M = 23.73 years old, SD = 7.24) and to extend the number of subjective
+dimensions used to evaluate each image. Speciﬁcally, participants reported emotional
+labeling (forced-choice task) and evaluated the emotional intensity and valence of the
+expression, as well as the attractiveness and familiarity of the model (7-points rating"
+ce85d953086294d989c09ae5c41af795d098d5b2,Bilinear Analysis for Kernel Selection and Nonlinear Feature Extraction,"This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.
+Bilinear Analysis for Kernel Selection and
+Nonlinear Feature Extraction
+Shu Yang, Shuicheng Yan, Member, IEEE, Chao Zhang, and Xiaoou Tang, Senior Member, IEEE"
+ce9a61bcba6decba72f91497085807bface02daf,Eigen-harmonics faces: face recognition under generic lighting,"Eigen-Harmonics Faces: Face Recognition under Generic Lighting
+Laiyun Qing1,2, Shiguang Shan2, Wen Gao1,2
+Graduate School, CAS, Beijing, China, 100080
+ICT-ISVISION Joint R&D Laboratory for Face Recognition, CAS, Beijing, China, 100080
+Emails: {lyqing, sgshan, wgao}jdl.ac.cn"
+cef6cffd7ad15e7fa5632269ef154d32eaf057af,Emotion Detection Through Facial Feature Recognition,"Emotion Detection Through Facial Feature
+Recognition
+James Pao
+through  consistent"
+cebfafea92ed51b74a8d27c730efdacd65572c40,Matching 2.5D face scans to 3D models,"JANUARY 2006
+Matching 2.5D Face Scans to 3D Models
+Xiaoguang Lu, Student Member, IEEE, Anil K. Jain, Fellow, IEEE, and
+Dirk Colbry, Student Member, IEEE"
+ce54e891e956d5b502a834ad131616786897dc91,Face Recognition Using LTP Algorithm,"International Journal of Science and Research (IJSR)
+ISSN (Online): 2319-7064
+Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611
+Face Recognition Using LTP Algorithm
+Richa Sharma1, Rohit Arora2
+ECE & KUK
+Assistant Professor (ECE)
+Volume 4 Issue 12, December 2015
+Licensed Under Creative Commons Attribution CC BY
+www.ijsr.net
+  Variation  in  luminance:  Third  main  challenge  that
+ppears in face recognition process is the luminance. Due
+to variation in the luminance the representation get varied
+from  the  original  image.  The  person  with  same  poses
+expression and seen from same viewpoint can be appear
+very different due to variation in lightening."
+ce6f459462ea9419ca5adcc549d1d10e616c0213,A Survey on Face Identification Methodologies in Videos,"A Survey on Face Identification Methodologies in
+Videos
+Student, M.Tech  CSE ,Department of Computer Science
+& Engineering ,G.H.Raisoni College of Engineering &
+Technology for Women, Nagpur, Maharashtra, India.
+Deepti Yadav"
+ce933821661a0139a329e6c8243e335bfa1022b1,Temporal Modeling Approaches for Large-scale Youtube-8M Video Understanding,"Temporal Modeling Approaches for Large-scale
+Youtube-8M Video Understanding
+Fu Li, Chuang Gan, Xiao Liu, Yunlong Bian, Xiang Long, Yandong Li, Zhichao Li, Jie Zhou, Shilei Wen
+Baidu IDL & Tsinghua University"
+e0dedb6fc4d370f4399bf7d67e234dc44deb4333,Supplementary Material: Multi-Task Video Captioning with Video and Entailment Generation,"Supplementary Material: Multi-Task Video Captioning with Video and
+Entailment Generation
+Ramakanth Pasunuru and Mohit Bansal
+UNC Chapel Hill
+{ram,
+Experimental Setup
+.1 Datasets
+.1.1 Video Captioning Datasets
+YouTube2Text or MSVD The Microsoft Re-
+search Video Description Corpus (MSVD) or
+YouTube2Text (Chen and Dolan, 2011) is used
+for our primary video captioning experiments. It
+has 1970 YouTube videos in the wild with many
+diverse captions in multiple languages for each
+video. Caption annotations to these videos are
+ollected using Amazon Mechanical Turk (AMT).
+All our experiments use only English captions. On
+verage, each video has 40 captions, and the over-
+ll dataset has about 80, 000 unique video-caption
+pairs. The average clip duration is roughly 10 sec-"
+e096b11b3988441c0995c13742ad188a80f2b461,DeepProposals: Hunting Objects and Actions by Cascading Deep Convolutional Layers,"Noname manuscript No.
+(will be inserted by the editor)
+DeepProposals: Hunting Objects and Actions by Cascading
+Deep Convolutional Layers
+Amir Ghodrati · Ali Diba · Marco Pedersoli · Tinne Tuytelaars · Luc
+Van Gool
+Received: date / Accepted: date"
+e0939b4518a5ad649ba04194f74f3413c793f28e,Mind-reading machines : automated inference of complex mental states Rana,"Technical Report
+UCAM-CL-TR-636
+ISSN 1476-2986
+Number 636
+Computer Laboratory
+Mind-reading machines:
+utomated inference
+of complex mental states
+Rana Ayman el Kaliouby
+July 2005
+5 JJ Thomson Avenue
+Cambridge CB3 0FD
+United Kingdom
+phone +44 1223 763500
+http://www.cl.cam.ac.uk/"
+e0ed0e2d189ff73701ec72e167d44df4eb6e864d,Recognition of static and dynamic facial expressions: a study review,"Recognition of static and dynamic facial expressions: a study review
+Estudos de Psicologia, 18(1), janeiro-março/2013, 125-130
+Nelson Torro Alves
+Federal University of Paraíba"
+e065a2cb4534492ccf46d0afc81b9ad8b420c5ec,SFace: An Efficient Network for Face Detection in Large Scale Variations,"SFace: An Ef‌f‌icient Network for Face Detection
+in Large Scale Variations
+Jianfeng Wang12∗, Ye Yuan 1†, Boxun Li†, Gang Yu† and Sun Jian†
+College of Software, Beihang University∗
+Megvii Inc. (Face++)†"
+e013c650c7c6b480a1b692bedb663947cd9d260f,Robust Image Analysis With Sparse Representation on Quantized Visual Features,"Robust Image Analysis With Sparse Representation
+on Quantized Visual Features
+Bing-Kun Bao, Guangyu Zhu, Jialie Shen, and Shuicheng Yan, Senior Member, IEEE"
+46a4551a6d53a3cd10474ef3945f546f45ef76ee,Robust and continuous estimation of driver gaze zone by dynamic analysis of multiple face videos,"014 IEEE Intelligent Vehicles Symposium (IV)
+June 8-11, 2014. Dearborn, Michigan, USA
+978-1-4799-3637-3/14/$31.00 ©2014 IEEE"
+4686bdcee01520ed6a769943f112b2471e436208,Fast search based on generalized similarity measure,"Utsumi et al. IPSJ Transactions on Computer Vision and
+Applications  (2017) 9:11
+DOI 10.1186/s41074-017-0024-5
+IPSJ Transactions on Computer
+Vision and Applications
+EXPRESS PAPER
+Open Access
+Fast search based on generalized
+similarity measure
+Yuzuko Utsumi*†, Tomoya Mizuno†, Masakazu Iwamura and Koichi Kise"
+4688787d064e59023a304f7c9af950d192ddd33e,Investigating the Discriminative Power of Keystroke Sound,"Investigating the Discriminative Power of Keystroke
+Sound
+Joseph Roth Student Member, IEEE,, Xiaoming Liu, Member, IEEE, Arun Ross, Senior Member, IEEE,
+nd Dimitris Metaxas, Member, IEEE"
+46f2611dc4a9302e0ac00a79456fa162461a8c80,Spatio-Temporal Channel Correlation Networks for Action Classification,"for Action Classiﬁcation
+Ali Diba1,4,(cid:63), Mohsen Fayyaz3,(cid:63), Vivek Sharma2, M.Mahdi Arzani4, Rahman
+Yousefzadeh4, Juergen Gall3, Luc Van Gool1,4
+ESAT-PSI, KU Leuven, 2CV:HCI, KIT, Karlsruhe, 3University of Bonn, 4Sensifai"
+466a5add15bb5f91e0cfd29a55f5fb159a7980e5,Video Repeat Recognition and Mining by Visual Features,"Video Repeat Recognition and Mining by Visual
+Features
+Xianfeng Yang1and Qi Tian"
+46f3b113838e4680caa5fc8bda6e9ae0d35a038c,Automated Dermoscopy Image Analysis of Pigmented Skin Lesions,"Cancers 2010, 2, 262-273; doi:10.3390/cancers2020262
+OPEN ACCESS
+ancers
+ISSN 2072-6694
+www.mdpi.com/journal/cancers
+Review
+Automated Dermoscopy Image Analysis of Pigmented Skin
+Lesions
+Alfonso Baldi 1,2,*, Marco Quartulli 3, Raffaele Murace 2, Emanuele Dragonetti 2,
+Mario Manganaro 3, Oscar Guerra 3 and Stefano Bizzi 3
+Department of Biochemistry, Section of Pathology, Second University of Naples, Via L. Armanni
+5, 80138 Naples, Italy
+Futura-onlus, Via Pordenone 2, 00182 Rome, Italy; E-Mail:
+ACS, Advanced Computer Systems, Via della Bufalotta 378, 00139 Rome, Italy
+*  Author to whom correspondence should be addressed; E-Mail:
+Fax: +390815569693.
+Received: 23 February 2010; in revised form: 15 March 2010 / Accepted: 25 March 2010 /
+Published: 26 March 2010"
+46538b0d841654a0934e4c75ccd659f6c5309b72,A Novel Approach to Generate Face Biometric Template Using Binary Discriminating Analysis,"Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.1, February 2014
+A NOVEL APPROACH TO GENERATE FACE
+BIOMETRIC TEMPLATE USING BINARY
+DISCRIMINATING ANALYSIS
+Shraddha S. Shinde1 and Prof. Anagha P. Khedkar2
+P.G. Student, Department of Computer Engineering, MCERC, Nashik (M.S.), India.
+Associate Professor, Department of Computer Engineering,
+MCERC, Nashik (M.S.), India"
+469ee1b00f7bbfe17c698ccded6f48be398f2a44,SURVEy: Techniques for Aging Problems in Face Recognition,"MIT International Journal of Computer Science and Information Technology, Vol. 4, No. 2, August 2014, pp. 82-88
+ISSN 2230-7621©MIT Publications
+SURVEy: Techniques for
+Aging Problems in Face Recognition
+Aashmi
+Sakshi Sahni
+Sakshi Saxena
+Scholar, Computer Science Engg. Dept.
+Moradabad Institute of Technology
+Scholar, Computer Science Engg. Dept.
+Moradabad Institute of Technology
+Scholar, Computer Science Engg. Dept.
+Moradabad Institute of Technology
+Moradabad, U.P., INDIA
+Moradabad, U.P., INDIA
+Moradabad, U.P., INDIA
+E-mail:
+E-mail:
+E-mail:"
+4682fee7dc045aea7177d7f3bfe344aabf153bd5,Tabula rasa: Model transfer for object category detection,"Tabula Rasa: Model Transfer for
+Object Category Detection
+Yusuf Aytar & Andrew Zisserman,
+Department of Engineering Science
+Oxford
+(Presented by Elad Liebman)"
+2c8743089d9c7df04883405a31b5fbe494f175b4,Real-time full-body human gender recognition in (RGB)-D data,"Washington State Convention Center
+Seattle, Washington, May 26-30, 2015
+978-1-4799-6922-7/15/$31.00 ©2015 IEEE"
+2c93c8da5dfe5c50119949881f90ac5a0a4f39fe,Advanced local motion patterns for macro and micro facial expression recognition,"Advanced local motion patterns for macro and micro facial
+expression recognition
+B. Allaerta,∗, IM. Bilascoa, C. Djerabaa
+Univ. Lille, CNRS, Centrale Lille, UMR 9189 - CRIStAL -
+Centre de Recherche en Informatique Signal et Automatique de Lille, F-59000 Lille, France"
+2c34bf897bad780e124d5539099405c28f3279ac,Robust Face Recognition via Block Sparse Bayesian Learning,"Robust Face Recognition via Block Sparse Bayesian Learning
+Taiyong Li1,2, Zhilin Zhang3,4,∗
+School of Financial Information Engineering, Southwestern University of Finance and Economics, Chengdu 610074,
+China
+Institute of Chinese Payment System, Southwestern University of Finance and Economics, Chengdu 610074, China
+Department of Electrical and Computer Engineering, University of California at San Diego, La Jolla, CA 92093-0407,
+Samsung R&D Institute America - Dallas, 1301 East Lookout Drive, Richardson, TX 75082, USA"
+2cc4ae2e864321cdab13c90144d4810464b24275,Face Recognition Using Optimized 3D Information from Stereo Images,"Face Recognition Using Optimized 3D
+Information from Stereo Images
+Changhan Park1 and Joonki Paik2
+Advanced Technology R&D Center, Samsung Thales Co., Ltd., 2Graduate School of
+Advanced Imaging Science, Multimedia, and Film Chung-Ang University, Seoul
+Korea
+. Introduction
+Human  biometric  characteristics  are  unique,  so  it  can  not  be  easily  duplicated  [1].  Such
+information
+includes;  facial,  hands,  torso,  fingerprints,  etc.  Potential  applications,
+economical  efficiency,  and  user  convenience  make  the  face  detection  and  recognition
+technique an important commodity compared to other biometric features [2], [3]. It can also
+use a low-cost personal computer (PC) camera instead of expensive equipments, and require
+minimal user interface. Recently, extensive research using 3D face data has been carried out
+in  order  to  overcome  the  limits  of  2D  face  detection  and  feature  extraction  [2],  which
+includes  PCA  [3],  neural  networks  (NN)  [4],  support  vector  machines  (SVM)  [5],  hidden
+markov models (HMM) [6], and linear discriminant analysis (LDA) [7]. Among them, PCA
+nd  LDA  methods  with  self-learning  method  are  most  widely  used  [3].  The  frontal  face
+image  database  provides  fairly  high  recognition  rate.  However,  if  the  view  data  of  facial
+rotation,  illumination  and  pose  change  is  not  acquired,  the  correct  recognition  rate"
+2cac8ab4088e2bdd32dcb276b86459427355085c,A Face-to-Face Neural Conversation Model,"A Face-to-Face Neural Conversation Model
+Hang Chu1
+Daiqing Li1 Sanja Fidler1
+University of Toronto 2Vector Institute
+{chuhang1122, daiqing,"
+2c2786ea6386f2d611fc9dbf209362699b104f83,1)local Feature Representations for Facial Expression Recognition Based on Differences of Gray Color Values of Neighboring Pixels,1)LOCAL FEATURE REPRESENTATIONS FOR FACIAL EXPRESSION RECOGNITION BASED ON DIFFERENCES OF GRAY COLOR VALUES OF NEIGHBORING PIXELS        Mohammad Shahidul Islam          A Dissertation Submitted in Partial  Fulfillment of the Requirement for the Degree of  Doctor of Philosophy (Computer Science and Information Systems) School of Applied Statistics National Institute of Development Administration 2013
+2c92839418a64728438c351a42f6dc5ad0c6e686,Pose-Aware Face Recognition in the Wild,"Pose-Aware Face Recognition in the Wild
+Iacopo Masi1
+Prem Natarajan2
+USC Institute for Robotics and Intelligent Systems (IRIS), Los Angeles, CA
+G´erard Medioni1
+Stephen Rawls2
+USC Information Sciences Institute (ISI), Marina Del Rey, CA"
+2c848cc514293414d916c0e5931baf1e8583eabc,An automatic facial expression recognition system evaluated by different classifiers,"An automatic facial expression recognition system
+evaluated by different classiﬁers
+Caroline Silva∗, Andrews Sobral∗ and Raissa Tavares Vieira†
+Programa de P´os-Graduac¸˜ao em Mecatrˆonica
+Universidade Federal da Bahia,
+Email:
+Email:
+Department of Electrical Engineering - EESC/USP
+Email:"
+2c883977e4292806739041cf8409b2f6df171aee,Are Haar-Like Rectangular Features for Biometric Recognition Reducible?,"Aalborg Universitet
+Are Haar-like Rectangular Features for Biometric Recognition Reducible?
+Nasrollahi, Kamal; Moeslund, Thomas B.
+Published in:
+Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
+DOI (link to publication from Publisher):
+0.1007/978-3-642-41827-3_42
+Publication date:
+Document Version
+Early version, also known as pre-print
+Link to publication from Aalborg University
+Citation for published version (APA):
+Nasrollahi, K., & Moeslund, T. B. (2013). Are Haar-like Rectangular Features for Biometric Recognition
+Reducible? In J. Ruiz-Shulcloper, & G. Sanniti di Baja (Eds.), Progress in Pattern Recognition, Image Analysis,
+Computer Vision, and Applications (Vol. 8259, pp. 334-341). Springer Berlin Heidelberg: Springer Publishing
+Company.  Lecture Notes in Computer Science, DOI: 10.1007/978-3-642-41827-3_42
+General rights
+Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners
+nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.
+? Users may download and print one copy of any publication from the public portal for the purpose of private study or research."
+2cdd9e445e7259117b995516025fcfc02fa7eebb,Temporal Exemplar-Based Bayesian Networks for Facial Expression Recognition,"Title
+Temporal Exemplar-based Bayesian Networks for facial
+expression recognition
+Author(s)
+Shang, L; Chan, KP
+Citation
+Proceedings - 7Th International Conference On Machine
+Learning And Applications, Icmla 2008, 2008, p. 16-22
+Issued Date
+http://hdl.handle.net/10722/61208
+Rights
+This work is licensed under a Creative Commons Attribution-
+NonCommercial-NoDerivatives 4.0 International License.;
+International Conference on Machine Learning and Applications
+Proceedings. Copyright © IEEE.; ©2008 IEEE. Personal use of
+this material is permitted. However, permission to
+reprint/republish this material for advertising or promotional
+purposes or for creating new collective works for resale or
+redistribution to servers or lists, or to reuse any copyrighted
+omponent of this work in other works must be obtained from"
+2c5d1e0719f3ad7f66e1763685ae536806f0c23b,AENet: Learning Deep Audio Features for Video Analysis,"AENet: Learning Deep Audio Features for Video
+Analysis
+Naoya Takahashi, Member, IEEE, Michael Gygli, Member, IEEE, and Luc Van Gool, Member, IEEE"
+2c8f24f859bbbc4193d4d83645ef467bcf25adc2,Classification in the Presence of Label Noise: A Survey,"Classiﬁcation in the Presence of
+Label Noise: a Survey
+Benoît Frénay and Michel Verleysen, Member, IEEE"
+2cdde47c27a8ecd391cbb6b2dea64b73282c7491,Order-aware Convolutional Pooling for Video Based Action Recognition,"ORDER-AWARE CONVOLUTIONAL POOLING FOR VIDEO BASED ACTION RECOGNITION
+Order-aware Convolutional Pooling for Video Based
+Action Recognition
+Peng Wang, Lingqiao Liu, Chunhua Shen, and Heng Tao Shen"
+2cf5f2091f9c2d9ab97086756c47cd11522a6ef3,MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation,"MPIIGaze: Real-World Dataset and Deep
+Appearance-Based Gaze Estimation
+Xucong Zhang, Yusuke Sugano∗, Mario Fritz, Andreas Bulling"
+2c4b96f6c1a520e75eb37c6ee8b844332bc0435c,Automatic Emotion Recognition in Robot-Children Interaction for ASD Treatment,"Automatic Emotion Recognition in Robot-Children Interaction for ASD
+Treatment
+Marco Leo, Marco Del Coco, Pierluigi Carcagn`ı, Cosimo Distante
+ISASI UOS Lecce
+Campus Universitario via Monteroni sn, 73100 Lecce Italy
+Massimo Bernava, Giovanni Pioggia
+ISASI UOS Messina
+Giuseppe Palestra
+Univerisita’ di Bari
+Marine Institute, via Torre Bianca, 98164 Messina Italy
+Via Orabona 4, 70126 Bari, Italy"
+790aa543151312aef3f7102d64ea699a1d15cb29,Confidence-Weighted Local Expression Predictions for Occlusion Handling in Expression Recognition and Action Unit Detection,"Conﬁdence-Weighted Local Expression Predictions for
+Occlusion Handling in Expression Recognition and Action
+Unit detection
+Arnaud Dapogny1
+Kevin Bailly1
+Séverine Dubuisson1
+Sorbonne Universités, UPMC Univ Paris 06, CNRS, ISIR UMR 7222
+place Jussieu 75005 Paris"
+79f6a8f777a11fd626185ab549079236629431ac,Pradeep RavikumarDiscriminative Object Categorization with External Semantic Knowledge,"Copyright
+Sung Ju Hwang"
+79b669abf65c2ca323098cf3f19fa7bdd837ff31,Efficient tensor based face recognition,"Deakin Research Online
+This is the published version:
+Rana, Santu, Liu, Wanquan, Lazarescu, Mihai and Venkatesh, Svetha 2008, Efficient tensor
+ased face recognition, in ICPR 2008 : Proceedings of the 19th International Conference on
+Pattern Recognition, IEEE, Washington, D. C., pp. 1-4.
+Available from Deakin Research Online:
+http://hdl.handle.net/10536/DRO/DU:30044585
+Reproduced with the kind permissions of the copyright owner.
+Personal use of this material is permitted. However, permission to reprint/republish this
+material for advertising or promotional purposes or for creating new collective works for
+resale or redistribution to servers or lists, or to reuse any copyrighted component of this work
+in other works must be obtained from the IEEE.
+Copyright : 2008, IEEE"
+79dd787b2877cf9ce08762d702589543bda373be,Face detection using SURF cascade,"Face Detection Using SURF Cascade
+Jianguo Li, Tao Wang, Yimin Zhang
+Intel Labs China"
+2d294c58b2afb529b26c49d3c92293431f5f98d0,Maximum Margin Projection Subspace Learning for Visual Data Analysis,"Maximum Margin Projection Subspace Learning
+for Visual Data Analysis
+Symeon Nikitidis, Anastasios Tefas, Member, IEEE, and Ioannis Pitas, Fellow, IEEE"
+2d05e768c64628c034db858b7154c6cbd580b2d5,FACIAL EXPRESSION RECOGNITION : Machine Learning using C #,"Neda Firoz et al, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.8, August- 2015, pg. 431-446
+Available Online at www.ijcsmc.com
+International Journal of Computer Science and Mobile Computing
+A Monthly Journal of Computer Science and Information Technology
+IJCSMC, Vol. 4, Issue. 8, August 2015, pg.431 – 446
+RESEARCH ARTICLE
+ISSN 2320–088X
+FACIAL EXPRESSION RECOGNITION:
+Machine Learning using C#
+Author: Neda Firoz
+Advisor: Dr. Prashant Ankur Jain"
+2d072cd43de8d17ce3198fae4469c498f97c6277,Random Cascaded-Regression Copse for Robust Facial Landmark Detection,"Random Cascaded-Regression Copse for Robust
+Facial Landmark Detection
+Zhen-Hua Feng, Student Member, IEEE, Patrik Huber, Josef Kittler, Life Member, IEEE, William Christmas,
+nd Xiao-Jun Wu"
+2d71e0464a55ef2f424017ce91a6bcc6fd83f6c3,A Survey on:Image Process using Two-Stage Crawler,"International Journal of Computer Applications (0975 – 8887)
+National Conference on Advancements in Computer & Information Technology (NCACIT-2016)
+A Survey on: Image Process using Two- Stage Crawler
+Nilesh Wani
+Assistant Professor
+SPPU, Pune
+Department of Computer Engg
+Department of Computer Engg
+Department of Computer Engg
+Dipak Bodade
+BE Student
+SPPU, Pune
+Savita Gunjal
+BE Student
+SPPU, Pune
+Varsha Mahadik
+BE Student
+Department of Computer Engg
+SPPU, Pune
+dditional"
+2d8d089d368f2982748fde93a959cf5944873673,Visually Guided Spatial Relation Extraction from Text,"Proceedings of NAACL-HLT 2018, pages 788–794
+New Orleans, Louisiana, June 1 - 6, 2018. c(cid:13)2018 Association for Computational Linguistics"
+2df4d05119fe3fbf1f8112b3ad901c33728b498a,Multi-task Learning for Structured Output Prediction,"Facial landmark detection using structured output deep
+neural networks
+Souﬁane Belharbi ∗1, Cl´ement Chatelain∗1, Romain H´erault∗1, and S´ebastien
+Adam∗2
+LITIS EA 4108, INSA de Rouen, Saint ´Etienne du Rouvray 76800, France
+LITIS EA 4108, UFR des Sciences, Universit´e de Rouen, France.
+September 24, 2015"
+4188bd3ef976ea0dec24a2512b44d7673fd4ad26,Nonlinear Non-Negative Component Analysis Algorithms,"Nonlinear Non-Negative Component
+Analysis Algorithms
+Stefanos Zafeiriou, Member, IEEE, and Maria Petrou, Senior Member, IEEE"
+41000c3a3344676513ef4bfcd392d14c7a9a7599,A Novel Approach For Generating Face Template Using Bda,"A NOVEL APPROACH FOR GENERATING FACE
+TEMPLATE USING BDA
+Shraddha S. Shinde1 and Prof. Anagha P. Khedkar2
+P.G. Student, Department of Computer Engineering, MCERC, Nashik (M.S.), India.
+Associate Professor, Department of Computer Engineering, MCERC, Nashik (M.S.),
+India"
+414715421e01e8c8b5743c5330e6d2553a08c16d,PoTion : Pose MoTion Representation for Action Recognition,"PoTion: Pose MoTion Representation for Action Recognition
+Philippe Weinzaepfel2
+Inria∗
+NAVER LABS Europe
+J´erˆome Revaud2 Cordelia Schmid1
+Vasileios Choutas1,2"
+41ab4939db641fa4d327071ae9bb0df4a612dc89,Interpreting Face Images by Fitting a Fast Illumination-Based 3D Active Appearance Model,"Interpreting Face Images by Fitting a Fast
+Illumination-Based 3D Active Appearance
+Model
+Salvador E. Ayala-Raggi, Leopoldo Altamirano-Robles, Janeth Cruz-Enriquez
+Instituto Nacional de Astrof´ısica, ´Optica y Electr´onica,
+Luis Enrique Erro #1, 72840 Sta Ma. Tonantzintla. Pue., M´exico
+Coordinaci´on de Ciencias Computacionales
+{saraggi, robles,"
+41a6196f88beced105d8bc48dd54d5494cc156fb,Using facial images for the diagnosis of genetic syndromes: A survey,"015 International Conference on
+Communications, Signal
+Processing, and their Applications
+(ICCSPA 2015)
+Sharjah, United Arab Emirates
+7-19 February 2015
+IEEE Catalog Number:
+ISBN:
+CFP1574T-POD
+978-1-4799-6533-5"
+41de109bca9343691f1d5720df864cdbeeecd9d0,Facial Emotion Recognition: A Survey and Real-World User Experiences in Mixed Reality,"Article
+Facial Emotion Recognition: A Survey and
+Real-World User Experiences in Mixed Reality
+Dhwani Mehta, Mohammad Faridul Haque Siddiqui and Ahmad Y. Javaid * ID
+EECS Department, The University of Toledo, Toledo, OH 43606, USA; (D.M.);
+(M.F.H.S.)
+* Correspondence: Tel.: +1-419-530-8260
+Received: 10 December 2017; Accepted: 26 January 2018; Published: 1 Febuary 2018"
+41d9a240b711ff76c5448d4bf4df840cc5dad5fc,Image Similarity Using Sparse Representation and Compression Distance,"JOURNAL DRAFT, VOL. X, NO. X, APR 2013
+Image Similarity Using Sparse Representation
+nd Compression Distance
+Tanaya Guha, Student Member, IEEE, and Rabab K Ward, Fellow, IEEE"
+419a6fca4c8d73a1e43003edc3f6b610174c41d2,A component based approach improves classification of discrete facial expressions over a holistic approach,"A Component Based Approach Improves Classiﬁcation of Discrete
+Facial Expressions Over a Holistic Approach
+Kenny Hong, and Stephan K. Chalup, Senior Member, IEEE and Robert A.R. King"
+4180978dbcd09162d166f7449136cb0b320adf1f,Real-time head pose classification in uncontrolled environments with Spatio-Temporal Active Appearance Models,"Real-time head pose classiﬁcation in uncontrolled environments
+with Spatio-Temporal Active Appearance Models
+Miguel Reyes∗ and Sergio Escalera+ and Petia Radeva +
+Matematica Aplicada i Analisi ,Universitat de Barcelona, Barcelona, Spain
++ Matematica Aplicada i Analisi, Universitat de Barcelona, Barcelona, Spain
++ Matematica Aplicada i Analisi, Universitat de Barcelona, Barcelona, Spain"
+413a184b584dc2b669fbe731ace1e48b22945443,Human Pose Co-Estimation and Applications,"Human Pose Co-Estimation and Applications
+Marcin Eichner and Vittorio Ferrari"
+83b7578e2d9fa60d33d9336be334f6f2cc4f218f,The S-HOCK dataset: Analyzing crowds at the stadium,"The S-HOCK Dataset: Analyzing Crowds at the Stadium
+Davide Conigliaro1,3, Paolo Rota2, Francesco Setti3, Chiara Bassetti3, Nicola Conci4, Nicu Sebe4, Marco Cristani1,
+University of Verona. 2Vienna Institute of Technology. 3ISTC–CNR (Trento). 4University of Trento.
+The topic of crowd modeling in computer vision usually assumes a sin-
+gle generic typology of crowd, which is very simplistic. In this paper we
+dopt a taxonomy that is widely accepted in sociology, focusing on a partic-
+ular category, the spectator crowd, which is formed by people “interested in
+watching something speciﬁc that they came to see” [1]. This can be found
+t the stadiums, amphitheaters, cinema, etc.
+In particular, we propose a
+novel dataset, the Spectators Hockey (S-HOCK), which deals with 4 hockey
+matches during an international tournament.
+The dataset is unique in the crowd literature, and in general in the
+surveillance realm. The dataset analyzes the crowd at different levels of
+detail. At the highest level, it models the network of social connections
+mong the public (who knows whom in the neighborhood), what is the sup-
+ported team and what has been the best action in the match; all of this has
+een obtained by interviews at the stadium. At a medium level, spectators
+re localized, and information regarding the pose of their heads and body is
+given. Finally, at a lowest level, a ﬁne grained speciﬁcation of all the actions"
+83ca4cca9b28ae58f461b5a192e08dffdc1c76f3,Detecting emotional stress from facial expressions for driving safety,"DETECTING EMOTIONAL STRESS FROM FACIAL EXPRESSIONS FOR DRIVING SAFETY
+Hua Gao, Anil Y¨uce, Jean-Philippe Thiran
+Signal Processing Laboratory (LTS5),
+´Ecole Polytechnique F´ed´erale de Lausanne, Switzerland"
+831fbef657cc5e1bbf298ce6aad6b62f00a5b5d9,Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning,
+832e1d128059dd5ed5fa5a0b0f021a025903f9d5,Pairwise Conditional Random Forests for Facial Expression Recognition,"Pairwise Conditional Random Forests for Facial Expression Recognition
+Arnaud Dapogny1
+Kevin Bailly1
+S´everine Dubuisson1
+Sorbonne Universit´es, UPMC Univ Paris 06, CNRS, ISIR UMR 7222, 4 place Jussieu 75005 Paris"
+83e093a07efcf795db5e3aa3576531d61557dd0d,Facial Landmark Localization Using Robust Relationship Priors and Approximative Gibbs Sampling,"Facial Landmark Localization using Robust
+Relationship Priors and Approximative Gibbs
+Sampling
+Karsten Vogt, Oliver M¨uller and J¨orn Ostermann
+Institut f¨ur Informationsverarbeitung (tnt)
+Leibniz Universit¨at Hannover, Germany
+{vogt, omueller,"
+83b4899d2899dd6a8d956eda3c4b89f27f1cd308,A Robust Approach for Eye Localization Under Variable Illuminations,"-4244-1437-7/07/$20.00 ©2007 IEEE
+I - 377
+ICIP 2007"
+8323af714efe9a3cadb31b309fcc2c36c8acba8f,Automatic Real-Time Facial Expression Recognition for Signed Language Translation,"Automatic Real-Time
+Facial Expression Recognition
+for Signed Language Translation
+Jacob Richard Whitehill
+A thesis submitted in partial fulﬁllment of the requirements for the de-
+gree of Magister Scientiae in the Department of Computer Science,
+University of the Western Cape.
+May 2006"
+83fd5c23204147844a0528c21e645b757edd7af9,USDOT number localization and recognition from vehicle side-view NIR images,"USDOT Number Localization and Recognition From Vehicle Side-View NIR
+Images
+Orhan Bulan, Safwan Wshah, Ramesh Palghat, Vladimir Kozitsky and Aaron Burry
+Palo Alto Research Center (PARC)
+800 Phillips Rd. Webster NY 14580"
+8323529cf37f955fb3fc6674af6e708374006a28,Evaluation of Face Resolution for Expression Analysis,"Evaluation of Face Resolution for Expression Analysis
+Ying-li Tian
+IBM T. J. Watson Research Center,
+PO Box 704, Yorktown Heights, NY 10598
+Email:"
+8395cf3535a6628c3bdc9b8d0171568d551f5ff0,Entropy Non-increasing Games for the Improvement of Dataflow Programming,"Entropy Non-increasing Games for the
+Improvement of Dataflow Programming
+Norbert B´atfai, Ren´at´o Besenczi, Gerg˝o Bogacsovics,
+Fanny Monori∗
+February 16, 2017"
+834f5ab0cb374b13a6e19198d550e7a32901a4b2,Face Translation between Images and Videos using Identity-aware CycleGAN,"Face Translation between Images and Videos using Identity-aware CycleGAN
+Zhiwu Huang†, Bernhard Kratzwald†, Danda Pani Paudel†, Jiqing Wu†, Luc Van Gool†‡
+Computer Vision Lab, ETH Zurich, Switzerland
+VISICS, KU Leuven, Belgium
+{zhiwu.huang, paudel, jwu,"
+8320dbdd3e4712cca813451cd94a909527652d63,Ear Biometrics,"EAR BIOMETRICS
+Mark Burge
+nd Wilhelm Burger
+Johannes Kepler University(cid:1) Institute of Systems Science(cid:1) A(cid:2)
+urge(cid:1)cast(cid:2)uni(cid:3)linz(cid:2)ac(cid:2)at"
+837e99301e00c2244023a8a48ff98d7b521c93ac,Local Feature Evaluation for a Constrained Local Model Framework,"Local Feature Evaluation for a Constrained
+Local Model Framework
+Maiya Hori(B), Shogo Kawai, Hiroki Yoshimura, and Yoshio Iwai
+Graduate School of Engineering, Tottori University,
+01 Minami 4-chome, Koyama-cho, Tottori 680-8550, Japan"
+834b15762f97b4da11a2d851840123dbeee51d33,Landmark-free smile intensity estimation,"Landmark-free smile intensity estimation
+J´ulio C´esar Batista, Olga R. P. Bellon and Luciano Silva
+IMAGO Research Group - Universidade Federal do Paran´a
+Fig. 1. Overview of our method for smile intensity estimation"
+833f6ab858f26b848f0d747de502127406f06417,Learning weighted similarity measurements for unconstrained face recognition,"978-1-4244-5654-3/09/$26.00 ©2009 IEEE
+ICIP 2009"
+8309e8f27f3fb6f2ac1b4343a4ad7db09fb8f0ff,Generic versus Salient Region-Based Partitioning for Local Appearance Face Recognition,"Generic versus Salient Region-based Partitioning
+for Local Appearance Face Recognition
+Hazım Kemal Ekenel and Rainer Stiefelhagen
+Computer Science Depatment, Universit¨at Karlsruhe (TH)
+Am Fasanengarten 5, Karlsruhe 76131, Germany
+http://isl.ira.uka.de/cvhci"
+1b02b9413b730b96b91d16dcd61b2420aef97414,Détection de marqueurs affectifs et attentionnels de personnes âgées en interaction avec un robot. (Audio-visual detection of emotional (laugh and smile) and attentional markers for elderly people in social interaction with a robot),"Détection de marqueurs affectifs et attentionnels de
+personnes âgées en interaction avec un robot
+Fan Yang
+To cite this version:
+Fan Yang. Détection de marqueurs affectifs et attentionnels de personnes âgées en interaction
+vec un robot.
+Intelligence artificielle [cs.AI]. Université Paris-Saclay, 2015. Français. <NNT :
+015SACLS081>. <tel-01280505>
+HAL Id: tel-01280505
+https://tel.archives-ouvertes.fr/tel-01280505
+Submitted on 29 Feb 2016
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entific research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destinée au dépôt et à la diffusion de documents
+scientifiques de niveau recherche, publiés ou non,"
+1b55c4e804d1298cbbb9c507497177014a923d22,Incremental Class Representation Learning for Face Recognition,"Incremental Class Representation
+Learning for Face Recognition
+Degree’s Thesis
+Audiovisual Systems Engineering
+Author:
+Advisors: Elisa Sayrol, Josep Ramon Morros
+Eric Presas Valga
+Universitat Politècnica de Catalunya (UPC)
+016 - 2017"
+1b6394178dbc31d0867f0b44686d224a19d61cf4,EPML: Expanded Parts Based Metric Learning for Occlusion Robust Face Verification,"EPML: Expanded Parts based Metric Learning for
+Occlusion Robust Face Veriﬁcation
+Gaurav Sharma, Fr´ed´eric Jurie, Patrick P´erez
+To cite this version:
+Gaurav Sharma, Fr´ed´eric Jurie, Patrick P´erez. EPML: Expanded Parts based Metric Learning
+for Occlusion Robust Face Veriﬁcation. Asian Conference on Computer Vision, Nov 2014, -,
+Singapore. pp.1-15, 2014. <hal-01070657>
+HAL Id: hal-01070657
+https://hal.archives-ouvertes.fr/hal-01070657
+Submitted on 2 Oct 2014
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entiﬁc research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destin´ee au d´epˆot et `a la diffusion de documents
+scientiﬁques de niveau recherche, publi´es ou non,
+´emanant des ´etablissements d’enseignement et de"
+1bdef21f093c41df2682a07f05f3548717c7a3d1,Towards Automated Classification of Emotional Facial Expressions,"Towards Automated Classiﬁcation of Emotional Facial Expressions
+Lewis J. Baker Vanessa LoBue
+Elizabeth Bonawitz & Patrick Shafto
+Department of Mathematics and Computer Science, 2Department of Psychology
+Rutgers University – Newark, 101 Warren St., Newark, NJ, 07102 USA"
+1b150248d856f95da8316da868532a4286b9d58e,Analyzing 3D Objects in Cluttered Images,"Analyzing 3D Objects in Cluttered Images
+Mohsen Hejrati
+UC Irvine
+Deva Ramanan
+UC Irvine"
+1be498d4bbc30c3bfd0029114c784bc2114d67c0,Age and Gender Estimation of Unfiltered Faces,"Age and Gender Estimation of Unﬁltered Faces
+Eran Eidinger, Roee Enbar, Tal Hassner*"
+1bbec7190ac3ba34ca91d28f145e356a11418b67,Explorer Action Recognition with Dynamic Image Networks,"Action Recognition with Dynamic Image Networks
+Citation for published version:
+Bilen, H, Fernando, B, Gravves, E & Vedaldi, A 2017, 'Action Recognition with Dynamic Image Networks'
+IEEE Transactions on Pattern Analysis and Machine Intelligence. DOI: 10.1109/TPAMI.2017.2769085
+Digital Object Identifier (DOI):
+0.1109/TPAMI.2017.2769085
+Link:
+Link to publication record in Edinburgh Research Explorer
+Document Version:
+Peer reviewed version
+Published In:
+IEEE Transactions on Pattern Analysis and Machine Intelligence
+General rights
+Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s)
+nd / or other copyright owners and it is a condition of accessing these publications that users recognise and
+bide by the legal requirements associated with these rights.
+Take down policy
+The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer
+ontent complies with UK legislation. If you believe that the public display of this file breaches copyright please
+ontact providing details, and we will remove access to the work immediately and"
+1b3587363d37dd197b6adbcfa79d49b5486f27d8,Multimodal Grounding for Language Processing,"Multimodal Grounding for Language Processing
+Lisa Beinborn◦∗3
+Teresa Botschen∗(cid:52)
+Iryna Gurevych (cid:52)
+Language Technology Lab, University of Duisburg-Essen
+(cid:52) Ubiquitous Knowledge Processing Lab (UKP) and Research Training Group AIPHES
+Department of Computer Science, Technische Universit¨at Darmstadt
+www.ukp.tu-darmstadt.de"
+1b300a7858ab7870d36622a51b0549b1936572d4,Dynamic Facial Expression Recognition With Atlas Construction and Sparse Representation,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TIP.2016.2537215, IEEE
+Transactions on Image Processing
+Dynamic Facial Expression Recognition with Atlas
+Construction and Sparse Representation
+Yimo Guo, Guoying Zhao, Senior Member, IEEE, and Matti Pietik¨ainen, Fellow, IEEE"
+1b90507f02967ff143fce993a5abbfba173b1ed0,Gradient-DCT (G-DCT) descriptors,"Image Processing Theory, Tools and Applications
+Gradient-DCT (G-DCT) Descriptors
+Radovan Fusek, Eduard Sojka
+Technical University of Ostrava, FEECS, Department of Computer Science,
+7. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic
+e-mail:"
+1b1173a3fb33f9dfaf8d8cc36eb0bf35e364913d,Registration Invariant Representations for Expression Detection,"DICTA
+DICTA 2010 Submission #147. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
+Registration Invariant Representations for Expression Detection
+Anonymous DICTA submission
+Paper ID 147"
+1b0a071450c419138432c033f722027ec88846ea,Looking at faces in a vehicle: A deep CNN based approach and evaluation,"Windsor Oceanico Hotel, Rio de Janeiro, Brazil, November 1-4, 2016
+978-1-5090-1889-5/16/$31.00 ©2016 IEEE"
+1b3b01513f99d13973e631c87ffa43904cd8a821,HMM recognition of expressions in unrestrained video intervals,"HMM RECOGNITION OF EXPRESSIONS IN UNRESTRAINED VIDEO INTERVALS
+José Luis Landabaso, Montse Pardàs, Antonio Bonafonte
+Universitat Politècnica de Catalunya, Barcelona, Spain"
+1be18a701d5af2d8088db3e6aaa5b9b1d54b6fd3,Enhancement of Fast Face Detection Algorithm Based on a Cascade of Decision Trees,"ENHANCEMENT OF FAST FACE DETECTION ALGORITHM BASED ON A CASCADE OF
+DECISION TREES
+V. V. Khryashchev a, *, A. A. Lebedev a, A. L. Priorov a
+YSU, Yaroslavl, Russia - (vhr,
+Commission II, WG II/5
+KEY WORDS: Face Detection, Cascade Algorithm, Decision Trees."
+1b70bbf7cdfc692873ce98dd3c0e191580a1b041,Enhancing Performance of Face Recognition System Using Independent Component Analysis,"International Research Journal of Engineering and Technology (IRJET)        e-ISSN: 2395 -0056
+Volume: 03 Issue: 10 | Oct -2016                      www.irjet.net                                                                 p-ISSN: 2395-0072
+Enhancing Performance of Face Recognition
+System Using Independent Component Analysis
+Dipti Rane1, Prof. Uday Bhave2, and Asst Prof. Manimala Mahato3
+Student, Computer Science, Shah and Anchor Kuttchi Engineering College, Mumbai, India 1
+Guide, HOD, Computer Science, Shah and Anchor Kuttchi Engineering College, Mumbai, India 2
+Co-Guide, Assistant Prof., Computer Science, Shah and Anchor Kuttchi Engineering College, Mumbai, India 3
+---------------------------------------------------------------------***---------------------------------------------------------------------
+ards, tokens and keys. Biometric based methods examine"
+1b71d3f30238cb6621021a95543cce3aab96a21b,Fine-grained Video Classification and Captioning,"Fine-grained Video Classiﬁcation and Captioning
+Farzaneh Mahdisoltani1,2, Guillaume Berger2, Waseem Gharbieh2
+David Fleet1, Roland Memisevic2
+{farzaneh,
+University of Toronto1, Twenty Billion Neurons2"
+1b4f6f73c70353869026e5eec1dd903f9e26d43f,Robust Subjective Visual Property Prediction from Crowdsourced Pairwise Labels,"Robust Subjective Visual Property Prediction
+from Crowdsourced Pairwise Labels
+Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Jiechao Xiong,
+Shaogang Gong, Yizhou Wang, and Yuan Yao"
+1bc23c771688109bed9fd295ce82d7e702726327,Sparse Modeling of High - Dimensional Data for Learning and Vision,(cid:13) 2011 Jianchao Yang
+7711a7404f1f1ac3a0107203936e6332f50ac30c,Action Classification and Highlighting in Videos,"Action Classiﬁcation and Highlighting in Videos
+Atousa Torabi
+Disney Research Pittsburgh
+Leonid Sigal
+Disney Research Pittsburgh"
+778c9f88839eb26129427e1b8633caa4bd4d275e,Pose pooling kernels for sub-category recognition,"Pose Pooling Kernels for Sub-category Recognition
+Ning Zhang
+ICSI & UC Berkeley
+Ryan Farrell
+ICSI & UC Berkeley
+Trever Darrell
+ICSI & UC Berkeley"
+7789a5d87884f8bafec8a82085292e87d4e2866f,A Unified Tensor-based Active Appearance Face Model,"A Uniﬁed Tensor-based Active Appearance Face
+Model
+Zhen-Hua Feng, Member, IEEE, Josef Kittler, Life Member, IEEE, William Christmas, and Xiao-Jun Wu,
+Member, IEEE"
+778bff335ae1b77fd7ec67404f71a1446624331b,Hough Forest-Based Facial Expression Recognition from Video Sequences,"Hough Forest-based Facial Expression Recognition from
+Video Sequences
+Gabriele Fanelli, Angela Yao, Pierre-Luc Noel, Juergen Gall, and Luc Van Gool
+BIWI, ETH Zurich http://www.vision.ee.ethz.ch
+VISICS, K.U. Leuven http://www.esat.kuleuven.be/psi/visics"
+7726a6ab26a1654d34ec04c0b7b3dd80c5f84e0d,Content-aware compression using saliency-driven image retargeting,"CONTENT-AWARE COMPRESSION USING SALIENCY-DRIVEN IMAGE RETARGETING
+Fabio Z¨und*†, Yael Pritch*, Alexander Sorkine-Hornung*, Stefan Mangold*, Thomas Gross†
+*Disney Research Zurich
+ETH Zurich"
+7754b708d6258fb8279aa5667ce805e9f925dfd0,Facial Action Unit Recognition by Exploiting Their Dynamic and Semantic Relationships,"Facial Action Unit Recognition by Exploiting
+Their Dynamic and Semantic Relationships
+Yan Tong, Student Member, IEEE, Wenhui Liao, Member, IEEE, and Qiang Ji, Senior Member, IEEE"
+77db171a523fc3d08c91cea94c9562f3edce56e1,Gauss-Laguerre wavelet textural feature fusion with geometrical information for facial expression identification,"Poursaberi et al. EURASIP Journal on Image and Video Processing 2012, 2012:17
+http://jivp.eurasipjournals.com/content/2012/1/17
+R ES EAR CH
+Open Access
+Gauss–Laguerre wavelet textural feature fusion
+with geometrical information for facial expression
+identification
+Ahmad Poursaberi1*, Hossein Ahmadi Noubari2, Marina Gavrilova1 and Svetlana N Yanushkevich1"
+77037a22c9b8169930d74d2ce6f50f1a999c1221,Robust Face Recognition With Kernelized Locality-Sensitive Group Sparsity Representation,"Robust Face Recognition With Kernelized
+Locality-Sensitive Group Sparsity  Representation
+Shoubiao Tan, Xi Sun, Wentao Chan, Lei Qu, and Ling    Shao"
+779ad364cae60ca57af593c83851360c0f52c7bf,Steerable Pyramids Feature Based Classification Using Fisher Linear Discriminant for Face Recognition,"Steerable Pyramids Feature Based Classiﬁcation Using Fisher
+Linear Discriminant for Face Recognition
+EL AROUSSI MOHAMED1
+EL HASSOUNI MOHAMMED12
+GHOUZALI SANAA1
+RZIZA MOHAMMED1
+ABOUTAJDINE DRISS1
+GSCM-LRIT, Faculty of Sciences, Mohammed V University-Agdal, Rabat, Morocco
+DESTEC, FLSHR Mohammed V University-Agdal, Rabat, Morocco
+PO.Box 1014, Rabat, Morocco"
+77d31d2ec25df44781d999d6ff980183093fb3de,The Multiverse Loss for Robust Transfer Learning,"The Multiverse Loss for Robust Transfer Learning
+Supplementary
+. Omitted proofs
+for which the joint loss:
+m(cid:88)
+L(F r, br, D, y)
+J(F 1, b1...F m, bm, D, y) =
+is bounded by:
+mL∗(D, y) ≤ J(F 1, b1...F m, bm, D, y)
+m−1(cid:88)
+≤ mL∗(D, y) +
+Alλd−j+1
+where [A1 . . . Am−1] are bounded parameters.
+We provide proofs that were omitted from the paper for
+lack of space. We follow the same theorem numbering as in
+the paper.
+Lemma 1. The minimizers F ∗, b∗ of L are not unique, and
+it holds that for any vector v ∈ Rc and scalar s, the solu-
+tions F ∗ + v1(cid:62)
+Proof. denoting V = v1(cid:62)"
+486840f4f524e97f692a7f6b42cd19019ee71533,DeepVisage: Making Face Recognition Simple Yet With Powerful Generalization Skills,"DeepVisage: Making face recognition simple yet with powerful generalization
+skills
+Abul Hasnat1, Julien Bohn´e2, Jonathan Milgram2, St´ephane Gentric2, and Liming Chen1
+Laboratoire LIRIS, ´Ecole centrale de Lyon, 69134 Ecully, France.
+Safran Identity & Security, 92130 Issy-les-Moulineaux, France.
+{julien.bohne, stephane.gentric,"
+48186494fc7c0cc664edec16ce582b3fcb5249c0,P-CNN: Pose-Based CNN Features for Action Recognition,"P-CNN: Pose-based CNN Features for Action Recognition
+Guilhem Ch´eron∗ †
+Ivan Laptev∗
+INRIA
+Cordelia Schmid†"
+48499deeaa1e31ac22c901d115b8b9867f89f952,Interim Report of Final Year Project HKU-Face : A Large Scale Dataset for Deep Face Recognition,"Interim Report of Final Year Project
+HKU-Face: A Large Scale Dataset for
+Deep Face Recognition
+Haicheng Wang
+035140108
+Haoyu Li
+035141841
+COMP4801 Final Year Project
+Project Code: 17007"
+486a82f50835ea888fbc5c6babf3cf8e8b9807bc,Face Search at Scale: 80 Million Gallery,"MSU TECHNICAL REPORT MSU-CSE-15-11, JULY 24, 2015
+Face Search at Scale: 80 Million Gallery
+Dayong Wang, Member, IEEE, Charles Otto, Student Member, IEEE, Anil K. Jain, Fellow, IEEE"
+4850af6b54391fc33c8028a0b7fafe05855a96ff,Discovering useful parts for pose estimation in sparsely annotated datasets,"Discovering Useful Parts for Pose Estimation in Sparsely Annotated Datasets
+Mikhail Breslav1, Tyson L. Hedrick2, Stan Sclaroff1, and Margrit Betke1
+Department of Computer Science and 2Department of Biology
+Boston University and 2University of North Carolina"
+48a5b6ee60475b18411a910c6084b3a32147b8cd,Pedestrian Attribute Recognition with Part-based CNN and Combined Feature Representations,"Pedestrian attribute recognition with part-based CNN
+nd combined feature representations
+Yiqiang Chen, Stefan Duffner, Andrei Stoian, Jean-Yves Dufour, Atilla
+Baskurt
+To cite this version:
+Yiqiang Chen, Stefan Duffner, Andrei Stoian, Jean-Yves Dufour, Atilla Baskurt. Pedestrian attribute
+recognition with part-based CNN and combined feature representations. VISAPP2018, Jan 2018,
+Funchal, Portugal. <hal-01625470>
+HAL Id: hal-01625470
+https://hal.archives-ouvertes.fr/hal-01625470
+Submitted on 21 Jun 2018
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entific research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destinée au dépôt et à la diffusion de documents
+scientifiques de niveau recherche, publiés ou non,"
+487df616e981557c8e1201829a1d0ec1ecb7d275,Acoustic Echo Cancellation Using a Vector-Space-Based Adaptive Filtering Algorithm,"Acoustic Echo Cancellation Using a Vector-Space-Based
+Adaptive Filtering Algorithm
+Yu Tsao, Member IEEE, Shih-Hau Fang*, Senior Member IEEE, and Yao Shiao"
+48cfc5789c246c6ad88ff841701204fc9d6577ed,Age Invariant Face Recognition Based on DCT Feature Extraction and Kernel Fisher Analysis,"J Inf Process Syst, Vol.12, No.3, pp.392~409, September 2016
+ISSN 1976-913X (Print)
+ISSN 2092-805X (Electronic)
+Age Invariant Face Recognition Based on DCT
+Feature Extraction and Kernel Fisher Analysis
+Leila Boussaad*, Mohamed Benmohammed**, and Redha Benzid***"
+70f189798c8b9f2b31c8b5566a5cf3107050b349,The challenge of face recognition from digital point-and-shoot cameras,"The Challenge of Face Recognition from Digital Point-and-Shoot Cameras
+J. Ross Beveridge∗
+Geof H. Givens§
+W. Todd Scruggs¶
+P. Jonathon Phillips†
+Yui Man Lui∗
+Kevin W. Bowyer(cid:107)
+David Bolme‡
+Mohammad Nayeem Teli∗
+Patrick J. Flynn(cid:107)
+Bruce A. Draper∗,
+Hao Zhang∗
+Su Cheng†"
+70109c670471db2e0ede3842cbb58ba6be804561,Zero-Shot Visual Recognition via Bidirectional Latent Embedding,"Noname manuscript No.
+(will be inserted by the editor)
+Zero-Shot Visual Recognition via Bidirectional Latent Embedding
+Qian Wang · Ke Chen
+Received: date / Accepted: date"
+706236308e1c8d8b8ba7749869c6b9c25fa9f957,Crowdsourced data collection of facial responses,"Crowdsourced Data Collection of Facial Responses
+Daniel McDuff
+MIT Media Lab
+Cambridge
+02139, USA
+Rosalind Picard
+MIT Media Lab
+Cambridge
+02139, USA
+Rana el Kaliouby
+MIT Media Lab
+Cambridge
+02139, USA"
+706b9767a444de4fe153b2f3bff29df7674c3161,Fast Metric Learning For Deep Neural Networks,"Fast Metric Learning For Deep Neural Networks
+Henry Gouk1, Bernhard Pfahringer1, and Michael Cree2
+Department of Computer Science, University of Waikato, Hamilton, New Zealand
+School of Engineering, University of Waikato, Hamilton, New Zealand"
+70569810e46f476515fce80a602a210f8d9a2b95,Apparent Age Estimation from Face Images Combining General and Children-Specialized Deep Learning Models,"Apparent Age Estimation from Face Images Combining General and
+Children-Specialized Deep Learning Models
+Grigory Antipov1
+, Moez Baccouche1, Sid-Ahmed Berrani1, Jean-Luc Dugelay2
+Orange Labs – France Telecom, 4 rue Clos Courtel, 35512 Cesson-S´evign´e, France
+Eurecom, 450 route des Chappes, 06410 Biot, France"
+70e79d7b64f5540d309465620b0dab19d9520df1,Facial Expression Recognition System Using Extreme Learning Machine,"International Journal of Scientific & Engineering Research, Volume 8, Issue 3, March-2017
+ISSN 2229-5518
+Facial Expression Recognition System
+Using Extreme Learning Machine
+Firoz Mahmud, Dr. Md. Al Mamun"
+7003d903d5e88351d649b90d378f3fc5f211282b,Facial Expression Recognition using Gabor Wavelet,"International Journal of Computer Applications (0975 – 8887)
+Volume 68– No.23, April 2013
+Facial Expression Recognition using Gabor Wavelet
+Mahesh Kumbhar
+ENTC SVERI’S COE (Poly),
+Pandharpur,
+Solapur, India
+Manasi Patil
+ENTC SVERI’S COE,
+Pandharpur,
+Solapur, India
+Ashish Jadhav
+ENTC SVERI’S COE (Poly),
+Pandharpur,
+Solapur, India"
+70bf1769d2d5737fc82de72c24adbb7882d2effd,Face Detection in Intelligent Ambiences with Colored Illumination,"Face detection in intelligent ambiences with colored illumination
+Christina Katsimerou, Judith A. Redi, Ingrid Heynderickx
+Department of Intelligent Systems
+TU Delft
+Delft, The Netherlands"
+1e058b3af90d475bf53b3f977bab6f4d9269e6e8,Manifold Relevance Determination,"Manifold Relevance Determination
+Andreas C. Damianou
+Dept. of Computer Science & Shefﬁeld Institute for Translational Neuroscience, University of Shefﬁeld, UK
+Carl Henrik Ek
+KTH – Royal Institute of Technology, CVAP Lab, Stockholm, Sweden
+Michalis K. Titsias
+Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Oxford OX3 7BN, UK
+Neil D. Lawrence
+Dept. of Computer Science & Shefﬁeld Institute for Translational Neuroscience, University of Shefﬁeld, UK"
+1e799047e294267087ec1e2c385fac67074ee5c8,Automatic Classification of Single Facial Images,"IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 21, NO. 12, DECEMBER 1999
+Short Papers___________________________________________________________________________________________________
+Automatic Classification of
+Single Facial Images
+Michael J. Lyons, Julien Budynek, and
+Shigeru Akamatsu"
+1eb4ea011a3122dc7ef3447e10c1dad5b69b0642,Contextual Visual Recognition from Images and Videos,"Contextual Visual Recognition from Images and Videos
+Georgia Gkioxari
+Jitendra Malik
+Electrical Engineering and Computer Sciences
+University of California at Berkeley
+Technical Report No. UCB/EECS-2016-132
+http://www.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-132.html
+July 19, 2016"
+1e7ae86a78a9b4860aa720fb0fd0bdc199b092c3,A Brief Review of Facial Emotion Recognition Based on Visual Information,"Article
+A Brief Review of Facial Emotion Recognition Based
+on Visual Information
+Byoung Chul Ko ID
+Department of Computer Engineering, Keimyung University, Daegu 42601, Korea;
+Tel.: +82-10-3559-4564
+Received: 6 December 2017; Accepted: 25 January 2018; Published: 30 January 2018"
+1e8eee51fd3bf7a9570d6ee6aa9a09454254689d,Face Search at Scale,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TPAMI.2016.2582166, IEEE
+Transactions on Pattern Analysis and Machine Intelligence
+Face Search at Scale
+Dayong Wang, Member, IEEE, Charles Otto, Student Member, IEEE, Anil K. Jain, Fellow, IEEE"
+1eec03527703114d15e98ef9e55bee5d6eeba736,Automatic identification of persons in TV series,"UNIVERSITÄT KARLSRUHE (TH)
+FAKULTÄT FÜR INFORMATIK
+INTERACTIVE SYSTEMS LABS
+Prof. Dr. A. Waibel
+DIPLOMA THESIS
+Automatic identiﬁcation
+of persons in TV series
+SUBMITTED BY
+Mika Fischer
+MAY 2008
+ADVISORS
+M.Sc. Hazım Kemal Ekenel
+Dr.-Ing. Rainer Stiefelhagen"
+1e07500b00fcd0f65cf30a11f9023f74fe8ce65c,Whole space subclass discriminant analysis for face recognition,"WHOLE SPACE SUBCLASS DISCRIMINANT ANALYSIS FOR FACE RECOGNITION
+Bappaditya Mandal, Liyuan Li, Vijay Chandrasekhar and Joo Hwee Lim
+Email: {bmandal, lyli, vijay,
+Institute for Infocomm Research, A*STAR, Singapore"
+1ef1f33c48bc159881c5c8536cbbd533d31b0e9a,Identity-based Adversarial Training of Deep CNNs for Facial Action Unit Recognition,"Z. ZHANG ET AL.: ADVERSARIAL TRAINING FOR ACTION UNIT RECOGNITION
+Identity-based Adversarial Training of Deep
+CNNs for Facial Action Unit Recognition
+Zheng Zhang
+Shuangfei Zhai
+Lijun Yin
+Department of Computer Science
+State University of New York at
+Binghamton
+NY, USA."
+1e8394cc9fe7c2392aa36fb4878faf7e78bbf2de,Zero-Shot Object Recognition System Based on Topic Model,"TO APPEAR IN IEEE THMS
+Zero-Shot Object Recognition System
+ased on Topic Model
+Wai Lam Hoo and Chee Seng Chan"
+1ecb56e7c06a380b3ce582af3a629f6ef0104457,"A New Way of Discovery of Belief, Desire and Intention in the BDI Agent-Based Software Modeling","List of Contents Vol.8
+Contents of
+Journal of Advanced Computational
+Intelligence and Intelligent Informatics
+Volume 8
+Vol.8 No.1, January 2004
+Editorial:
+o Special Issue on Selected Papers from Humanoid,
+Papers:
+o Dynamic Color Object Recognition Using Fuzzy
+Nano-technology, Information Technology,
+Communication and Control, Environment, and
+Management (HNICEM’03).
+Elmer P. Dadios
+Papers:
+o A New Way of Discovery of Belief, Desire and
+Intention  in the BDI Agent-Based Software
+Modeling .
+Chang-Hyun Jo
+o Integration of Distributed Robotic Systems"
+1e64b2d2f0a8a608d0d9d913c4baee6973995952,Dominant and Complementary Multi-Emotional Facial Expression Recognition Using C-Support Vector Classification,"DOMINANT AND
+COMPLEMENTARY MULTI-
+EMOTIONAL FACIAL
+EXPRESSION RECOGNITION
+USING C-SUPPORT VECTOR
+CLASSIFICATION
+Christer Loob, Pejman Rasti, Iiris Lusi, Julio C. S. Jacques
+Junior, Xavier Baro, Sergio Escalera, Tomasz Sapinski,
+Dorota Kaminska and Gholamreza Anbarjafari"
+1e21b925b65303ef0299af65e018ec1e1b9b8d60,Unsupervised Cross-Domain Image Generation,"Under review as a conference paper at ICLR 2017
+UNSUPERVISED CROSS-DOMAIN IMAGE GENERATION
+Yaniv Taigman, Adam Polyak & Lior Wolf
+Facebook AI Research
+Tel-Aviv, Israel"
+1ee27c66fabde8ffe90bd2f4ccee5835f8dedbb9,9 Entropy Regularization,"Entropy Regularization
+Yves Grandvalet
+Yoshua Bengio
+The problem of semi-supervised induction consists in learning a decision rule from
+labeled and unlabeled data. This task can be undertaken by discriminative methods,
+provided that learning criteria are adapted consequently. In this chapter, we moti-
+vate the use of entropy regularization as a means to bene(cid:12)t from unlabeled data in
+the framework of maximum a posteriori estimation. The learning criterion is derived
+from clearly stated assumptions and can be applied to any smoothly parametrized
+model of posterior probabilities. The regularization scheme favors low density sep-
+ration, without any modeling of the density of input features. The contribution
+of unlabeled data to the learning criterion induces local optima, but this problem
+an be alleviated by deterministic annealing. For well-behaved models of posterior
+probabilities, deterministic annealing EM provides a decomposition of the learning
+problem in a series of concave subproblems. Other approaches to the semi-supervised
+problem are shown to be close relatives or limiting cases of entropy regularization.
+A series of experiments illustrates the good behavior of the algorithm in terms of
+performance and robustness with respect to the violation of the postulated low den-
+sity separation assumption. The minimum entropy solution bene(cid:12)ts from unlabeled
+data and is able to challenge mixture models and manifold learning in a number of"
+1ee3b4ba04e54bfbacba94d54bf8d05fd202931d,Celebrity Face Recognition using Deep Learning,"Indonesian Journal of Electrical Engineering and Computer Science
+Vol. 12, No. 2, November 2018, pp. 476~481
+ISSN: 2502-4752, DOI: 10.11591/ijeecs.v12.i2.pp476-481
+      476
+Celebrity Face Recognition using Deep Learning
+Nur Ateqah Binti Mat Kasim1, Nur Hidayah Binti Abd Rahman2, Zaidah Ibrahim3,
+Nur Nabilah Abu Mangshor4
+,2,3Faculty of Computer and Mathematical Sciences, UniversitiTeknologi MARA (UiTM),
+Faculty of Computer and Mathematical Sciences, UniversitiTeknologi MARA (UiTM),
+Shah Alam, Selangor, Malaysia
+Campus Jasin, Melaka, Malaysia
+Article Info
+Article history:
+Received May 29, 2018
+Revised Jul 30, 2018
+Accepted Aug 3, 2018
+Keywords:
+AlexNet
+Convolutional neural network
+Deep learning"
+1e41a3fdaac9f306c0ef0a978ae050d884d77d2a,Robust Object Recognition with Cortex-Like Mechanisms,"Robust Object Recognition with
+Cortex-Like Mechanisms
+Thomas Serre, Lior Wolf, Stanley Bileschi, Maximilian Riesenhuber, and
+Tomaso Poggio, Member, IEEE"
+1e1e66783f51a206509b0a427e68b3f6e40a27c8,Semi-supervised Estimation of Perceived Age from Face Images,"SEMI-SUPERVISED ESTIMATION OF PERCEIVED AGE
+FROM FACE IMAGES
+VALWAY Technology Center, NEC Soft, Ltd., Tokyo, Japan
+Kazuya Ueki
+Masashi Sugiyama
+Keywords:"
+1efaa128378f988965841eb3f49d1319a102dc36,Hierarchical binary CNNs for landmark localization with limited resources,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015
+Hierarchical binary CNNs for landmark
+localization with limited resources
+Adrian Bulat and Georgios Tzimiropoulos"
+8451bf3dd6bcd946be14b1a75af8bbb65a42d4b2,Consensual and Privacy-Preserving Sharing of Multi-Subject and Interdependent Data,"Consensual and Privacy-Preserving Sharing of
+Multi-Subject and Interdependent Data
+Alexandra-Mihaela Olteanu
+EPFL, UNIL–HEC Lausanne
+K´evin Huguenin
+UNIL–HEC Lausanne
+Italo Dacosta
+Jean-Pierre Hubaux"
+84e4b7469f9c4b6c9e73733fa28788730fd30379,Projective complex matrix factorization for facial expression recognition,"Duong et al. EURASIP Journal on Advances in Signal Processing  (2018) 2018:10
+DOI 10.1186/s13634-017-0521-9
+EURASIP Journal on Advances
+in Signal Processing
+R ES EAR CH
+Projective complex matrix factorization for
+facial expression recognition
+Viet-Hang Duong1, Yuan-Shan Lee1, Jian-Jiun Ding2, Bach-Tung Pham1, Manh-Quan Bui1, Pham The Bao2
+nd Jia-Ching Wang1,3*
+Open Access"
+84fa126cb19d569d2f0147bf6f9e26b54c9ad4f1,Improved Boosting Performance by Explicit Handling of Ambiguous Positive Examples,"Improved Boosting Performance by Explicit
+Handling of Ambiguous Positive Examples
+Miroslav Kobetski and Josephine Sullivan"
+84508e846af3ac509f7e1d74b37709107ba48bde,Use of the Septum as a Reference Point in a Neurophysiologic Approach to Facial Expression Recognition,"Use of the Septum as a Reference Point in a Neurophysiologic Approach to
+Facial Expression Recognition
+Igor Stankovic and Montri Karnjanadecha
+Department of Computer Engineering, Faculty of Engineering,
+Prince of Songkla University, Hat Yai, Songkhla, 90112 Thailand
+Telephone: (66)080-7045015, (66)074-287-357
+E-mail:"
+841a5de1d71a0b51957d9be9d9bebed33fb5d9fa,PCANet: A Simple Deep Learning Baseline for Image Classification?,"PCANet: A Simple Deep Learning Baseline for
+Image Classiﬁcation?
+Tsung-Han Chan, Member, IEEE, Kui Jia, Shenghua Gao, Jiwen Lu, Senior Member, IEEE,
+Zinan Zeng, and Yi Ma, Fellow, IEEE"
+8411fe1142935a86b819f065cd1f879f16e77401,Facial Recognition using Modified Local Binary Pattern and Random Forest,"International Journal of Artificial Intelligence & Applications (IJAIA), Vol. 4, No. 6, November 2013
+Facial Recognition using Modified Local Binary
+Pattern and Random Forest
+Brian O’Connor and Kaushik Roy
+Department of Computer Science,
+North Carolina A&T State University,
+Greensboro, NC 27411"
+849f891973ad2b6c6f70d7d43d9ac5805f1a1a5b,ResNet Backbone Proposals Classification Loss Regression Loss Classification Loss Regression Loss RPN Classification Branch Box Regression Branch Conv Conv,"Detecting Faces Using Region-based Fully
+Convolutional Networks
+Yitong Wang Xing Ji Zheng Zhou Hao Wang Zhifeng Li∗
+Tencent AI Lab, China"
+4adca62f888226d3a16654ca499bf2a7d3d11b71,Models of Semantic Representation with Visual Attributes,"Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, pages 572–582,
+Soﬁa, Bulgaria, August 4-9 2013. c(cid:13)2013 Association for Computational Linguistics"
+4a2d54ea1da851151d43b38652b7ea30cdb6dfb2,Direct recognition of motion-blurred faces,"Direct Recognition of Motion Blurred Faces
+Kaushik Mitra, Priyanka Vageeswaran and Rama Chellappa"
+4ab84f203b0e752be83f7f213d7495b04b1c4c79,Concave Losses for Robust Dictionary Learning,"CONCAVE LOSSES FOR ROBUST DICTIONARY LEARNING
+Rafael Will M. de Araujo, R. Hirata Jr ∗
+Alain Rakotomamonjy †
+University of S˜ao Paulo
+Institute of Mathematics and Statistics
+Rua do Mat˜ao, 1010 – 05508-090 – S˜ao Paulo-SP, Brazil
+Universit´e de Rouen Normandie
+LITIS EA 4108
+76800 Saint- ´Etienne-du-Rouvray, France"
+4a3758f283b7c484d3f164528d73bc8667eb1591,Attribute Enhanced Face Aging with Wavelet-based Generative Adversarial Networks,"Attribute Enhanced Face Aging with Wavelet-based Generative Adversarial
+Networks
+Yunfan Liu, Qi Li, and Zhenan Sun∗
+Center for Research on Intelligent Perception and Computing, CASIA
+National Laboratory of Pattern Recognition, CASIA
+{qli,"
+4a4da3d1bbf10f15b448577e75112bac4861620a,"Face , Expression , and Iris Recognition","FACE, EXPRESSION, AND IRIS RECOGNITION
+USING LEARNING-BASED APPROACHES
+Guodong Guo
+A dissertation submitted in partial fulﬁllment of
+the requirements for the degree of
+Doctor of Philosophy
+(Computer Sciences)
+t the
+UNIVERSITY OF WISCONSIN–MADISON"
+4abd49538d04ea5c7e6d31701b57ea17bc349412,Recognizing Fine-Grained and Composite Activities Using Hand-Centric Features and Script Data,"Recognizing Fine-Grained and Composite Activities
+using Hand-Centric Features and Script Data
+Marcus Rohrbach · Anna Rohrbach · Michaela Regneri ·
+Sikandar Amin · Mykhaylo Andriluka · Manfred Pinkal · Bernt Schiele"
+4a0f98d7dbc31497106d4f652968c708f7da6692,Real-time eye gaze direction classification using convolutional neural network,"Real-time Eye Gaze Direction Classiﬁcation Using
+Convolutional Neural Network
+Anjith George, Member, IEEE, and Aurobinda Routray, Member, IEEE"
+4a1a5316e85528f4ff7a5f76699dfa8c70f6cc5c,Face Recognition using Local Features based on Two-layer Block Model,"MVA2005  IAPR  Conference on Machine VIsion Applications, May 16-18, 2005 Tsukuba Science City, Japan
+Face Recognition using Local Features based on Two-layer Block M odel
+W onjun Hwang1          Ji-Yeun Kim        Seokcheol Kee
+Computing Lab.,
+Samsung Advanced Institute of Technology
+ombined  by  Yang  and  etc  [7].  The  sparsification  of  LFA
+helps the reduction of dimension of image in LDA scheme
+nd  local  topological  property  is  more  useful  than  holistic
+property of PCA in recognition, but there is still structural
+problem  because  the  method  to  select  the  features  is
+designed  for  minimization  of  reconstruction  error,  not  for
+increasing discriminability in face model.
+In  this  paper,  we  proposed  the  novel  recognition
+lgorithm  to  merge LFA  and LDA  method. We do  not use
+the existing sparsification method for selecting features but
+dopt  the  two-layer  block  model  to  make  several  groups
+with  topographic  local  features  in  similar  position.  Each
+local  block,  flocked  local  features,  can  represent  its  own
+local  property  and  at
+time  holistic  face"
+4a2062ba576ca9e9a73b6aa6e8aac07f4d9344b9,Fusing Deep Convolutional Networks for Large Scale Visual Concept Classification,"Fusing Deep Convolutional Networks for Large
+Scale Visual Concept Classiﬁcation
+Hilal Ergun and Mustafa SertB
+Department of Computer Engineering
+Bas¸kent University
+06810 Ankara, TURKEY"
+4ac3cd8b6c50f7a26f27eefc64855134932b39be,Robust Facial Landmark Detection via a Fully-Convolutional Local-Global Context Network,"Robust Facial Landmark Detection
+via a Fully-Convolutional Local-Global Context Network
+Daniel Merget
+Matthias Rock
+Gerhard Rigoll
+Technical University of Munich"
+4abaebe5137d40c9fcb72711cdefdf13d9fc3e62,Dimension Reduction for Regression with Bottleneck Neural Networks,"Dimension Reduction for Regression
+with Bottleneck Neural Networks
+Elina Parviainen
+BECS, Aalto University School of Science and Technology, Finland"
+4aeb87c11fb3a8ad603311c4650040fd3c088832,Self-paced Mixture of Regressions,"Proceedings of the Twenty-Sixth International Joint Conference on Artiﬁcial Intelligence (IJCAI-17)
+SamplesSelected SamplesOutliersMoRSPMoR (ours)6361242024Figure1:Inter-componentimbalanceandintra-componentoutliersinMixtureofRegression(MoR)approaches.StandardMoRcannotlearnaccurateregressors(denotedbythedashedlines).Byintroduc-inganovelself-pacedscheme,ourSPMoRapproach(denotedbythesolidlines)selectsbalancedandconﬁdenttrainingsamplesfromeachcomponent,whilepreventlearningfromtheoutliersthroughoutthetrainingprocedure.theywillbeinevitablybiasedbydatadistribution:lowre-gressionerrorindenselysampledspacewhilehigherrorineverywhereelse.Foraddressingtheissuesofthedatadiscontinuityandheterogeneity,thedivide-and-conquerapproacheswerepro-posedlately.Thecoreideaistolearntocombinemultiplelocalregressors.Forinstance,thehierarchical-based[Hanetal.,2015]andtree-basedregression[HaraandChellappa,2014]makehardpartitionsrecursively,andthesubsetsofsam-plesmaynotbehomogeneousforlearninglocalregressors.WhileMixtureofRegressions(MoR)[Jacobsetal.,1991;JordanandXu,1995]distributesregressionerroramonglocalregressorsbymaximizinglikelihoodinthejointinput-outputspace.Theseapproachesreduceoverallerrorbyﬁttingre-gressionlocallyandreliefsthebiasbydiscontinuousdatadistribution.Unfortunately,theaforementionedapproachesstillcannotachievesatisfactoryperformancewhenapplyinginsomereal-worldapplications.Themainreasonisthattheseapproachestendtobesensitivetotheintra-componentoutliers(i.e.,thenoisytrainingdataresidingincertaincomponents)andtheinter-componentimbalance(i.e.,thedifferentamountsoftrain-"
+4a3d96b2a53114da4be3880f652a6eef3f3cc035,A Dictionary Learning-Based 3D Morphable Shape Model,"A Dictionary Learning-Based
+D Morphable Shape Model
+Claudio Ferrari
+, Giuseppe Lisanti, Stefano Berretti
+, Senior Member, IEEE, and Alberto Del Bimbo"
+4a6fcf714f663618657effc341ae5961784504c7,Scaling Up Class-Specific Kernel Discriminant Analysis for Large-Scale Face Verification,"Scaling up Class-Speciﬁc Kernel Discriminant
+Analysis for large-scale Face Veriﬁcation
+Alexandros Iosiﬁdis, Senior Member, IEEE, and Moncef Gabbouj, Fellow, IEEE"
+24115d209e0733e319e39badc5411bbfd82c5133,Long-Term Recurrent Convolutional Networks for Visual Recognition and Description,"Long-term Recurrent Convolutional Networks for
+Visual Recognition and Description
+Jeff Donahue, Lisa Anne Hendricks, Marcus Rohrbach, Subhashini Venugopalan, Sergio Guadarrama,
+Kate Saenko, Trevor Darrell"
+24c442ac3f6802296d71b1a1914b5d44e48b4f29,Pose and Expression-Coherent Face Recovery in the Wild,"Pose and expression-coherent face recovery in the wild
+Xavier P. Burgos-Artizzu
+Joaquin Zepeda
+Technicolor, Cesson-S´evign´e, France
+Franc¸ois Le Clerc
+Patrick P´erez"
+245f8ec4373e0a6c1cae36cd6fed5a2babed1386,Lucas Kanade Optical Flow Computation from Superpixel based Intensity Region for Facial Expression Feature Extraction,"J. Appl. Environ. Biol. Sci., 7(3S)1-10, 2017
+© 2017, TextRoad Publication
+ISSN: 2090-4274
+Journal of Applied Environmental
+nd Biological Sciences
+www.textroad.com
+Lucas Kanade Optical Flow Computation from Superpixel based Intensity
+Region for Facial Expression Feature Extraction
+Halina Hassan1,2, Abduljalil Radman1, Shahrel Azmin Suandi1, Sazali Yaacob2
+Intelligent Biometric Group, School of Electrical and Electronics Engineering, Universiti Sains Malaysia,
+Electrical, Electronics and Automation Section, Universiti Kuala Lumpur Malaysian Spanish Institute, 09000
+Engineering Campus, 14300 Nibong Tebal, Pulau Pinang, Malaysia
+Kulim Hi-Tech Park, Kedah, Malaysia
+Received: February 21, 2017
+Accepted: May 14, 2017"
+24e099e77ae7bae3df2bebdc0ee4e00acca71250,Robust Face Alignment Under Occlusion via Regional Predictive Power Estimation,"Robust face alignment under occlusion via regional predictive power
+estimation.
+Heng Yang; Xuming He; Xuhui Jia; Patras, I
+© 2015 IEEE
+For additional information about this publication click this link.
+http://qmro.qmul.ac.uk/xmlui/handle/123456789/22467
+Information about this research object was correct at the time of download; we occasionally
+make corrections to records, please therefore check the published record when citing. For
+more information contact"
+2450c618cca4cbd9b8cdbdb05bb57d67e63069b1,A connexionist approach for robust and precise facial feature detection in complex scenes,"A Connexionist Approach for Robust and Precise Facial Feature Detection in
+Complex Scenes
+Stefan Duffner and Christophe Garcia
+France Telecom Research & Development
+, rue du Clos Courtel
+5512 Cesson-S´evign´e, France
+fstefan.duffner,"
+244b57cc4a00076efd5f913cc2833138087e1258,Warped Convolutions: Efficient Invariance to Spatial Transformations,"Warped Convolutions: Efﬁcient Invariance to Spatial Transformations
+Jo˜ao F. Henriques 1 Andrea Vedaldi 1"
+24869258fef8f47623b5ef43bd978a525f0af60e,Données multimodales pour l ’ analyse d ’ image,"UNIVERSITÉDEGRENOBLENoattribuéparlabibliothèqueTHÈSEpourobtenirlegradedeDOCTEURDEL’UNIVERSITÉDEGRENOBLESpécialité:MathématiquesetInformatiquepréparéeauLaboratoireJeanKuntzmanndanslecadredel’ÉcoleDoctoraleMathématiques,SciencesetTechnologiesdel’Information,InformatiqueprésentéeetsoutenuepubliquementparMatthieuGuillauminle27septembre2010ExploitingMultimodalDataforImageUnderstandingDonnéesmultimodalespourl’analysed’imageDirecteursdethèse:CordeliaSchmidetJakobVerbeekJURYM.ÉricGaussierUniversitéJosephFourierPrésidentM.AntonioTorralbaMassachusettsInstituteofTechnologyRapporteurMmeTinneTuytelaarsKatholiekeUniversiteitLeuvenRapporteurM.MarkEveringhamUniversityofLeedsExaminateurMmeCordeliaSchmidINRIAGrenobleExaminatriceM.JakobVerbeekINRIAGrenobleExaminateur"
+2465fc22e03faf030e5a319479a95ef1dfc46e14,Influence of different feature selection approaches on the performance of emotion recognition methods based on SVM,"______________________________________________________PROCEEDING OF THE 20TH CONFERENCE OF FRUCT ASSOCIATION
+Influence of Different Feature Selection Approaches
+on the Performance of Emotion Recognition
+Methods Based on SVM
+Daniil Belkov, Konstantin Purtov, Vladimir Kublanov
+Ural Federal University (UrFU)
+Yekaterinburg, Russia
+d.d.belkov,"
+24ff832171cb774087a614152c21f54589bf7523,Beat-Event Detection in Action Movie Franchises,"Beat-Event Detection in Action Movie Franchises
+Danila Potapov
+Matthijs Douze
+Jerome Revaud
+Zaid Harchaoui
+Cordelia Schmid"
+247a6b0e97b9447850780fe8dbc4f94252251133,Facial action unit detection: 3D versus 2D modality,"Facial Action Unit Detection: 3D versus 2D Modality
+Arman Savran
+Electrical and Electronics Engineering
+Bo˘gazic¸i University, Istanbul, Turkey
+B¨ulent Sankur
+Electrical and Electronics Engineering
+Bo˘gazic¸i University, Istanbul, Turkey
+M. Taha Bilge
+Department of Psychology
+Bo˘gazic¸i University, Istanbul, Turkey"
+230527d37421c28b7387c54e203deda64564e1b7,Person Re-identification: System Design and Evaluation Overview,"Person Re-identiﬁcation: System Design and
+Evaluation Overview
+Xiaogang Wang and Rui Zhao"
+23172f9a397f13ae1ecb5793efd81b6aba9b4537,Defining Visually Descriptive Language,"Proceedings of the 2015 Workshop on Vision and Language (VL’15), pages 10–17,
+Lisbon, Portugal, 18 September 2015. c(cid:13)2015 Association for Computational Linguistics."
+236a4f38f79a4dcc2183e99b568f472cf45d27f4,Randomized Clustering Forests for Image Classification,"Randomized Clustering Forests
+for Image Classification
+Frank Moosmann, Student Member, IEEE, Eric Nowak, Student Member, IEEE, and
+Frederic Jurie, Member, IEEE Computer Society"
+230c4a30f439700355b268e5f57d15851bcbf41f,EM Algorithms for Weighted-Data Clustering with Application to Audio-Visual Scene Analysis,"EM Algorithms for Weighted-Data Clustering
+with Application to Audio-Visual Scene Analysis
+Israel D. Gebru, Xavier Alameda-Pineda, Florence Forbes and Radu Horaud"
+237fa91c8e8098a0d44f32ce259ff0487aec02cf,Bidirectional PCA with assembled matrix distance metric for image recognition,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 36, NO. 4, AUGUST 2006
+Bidirectional PCA With Assembled Matrix
+Distance Metric for Image Recognition
+Wangmeng Zuo, David Zhang, Senior Member, IEEE, and Kuanquan Wang, Member, IEEE"
+2331df8ca9f29320dd3a33ce68a539953fa87ff5,Extended Isomap for Pattern Classification,"Extended Isomap for Pattern Classiﬁcation
+Ming-Hsuan Yang
+Honda Fundamental Research Labs
+Mountain View, CA 94041"
+23ba9e462151a4bf9dfc3be5d8b12dbcfb7fe4c3,Determining Mood from Facial Expressions,"CS 229 Project, Fall 2014
+Matthew Wang
+Spencer Yee
+Determining Mood from Facial Expressions
+Introduction
+Facial expressions play an extremely important role in human communication. As
+society continues to make greater use of human-machine interactions, it is important for
+machines to be able to interpret facial expressions in order to improve their
+uthenticity. If machines can be trained to determine mood to a better extent than
+humans can, especially for more subtle moods, then this could be useful in fields such as
+ounseling. This could also be useful for gauging reactions of large audiences in various
+ontexts, such as political talks.
+The results of this project could also be applied to recognizing other features of facial
+expressions, such as determining when people are purposefully suppressing emotions or
+lying. The ability to recognize different facial expressions could also improve technology
+that recognizes to whom specific faces belong. This could in turn be used to search a
+large number of pictures for a specific photo, which is becoming increasingly difficult, as
+storing photos digitally has been extremely common in the past decade. The possibilities
+re endless.
+II  Data and Features"
+238fc68b2e0ef9f5ec043d081451902573992a03,Enhanced Local Gradient Order Features and Discriminant Analysis for Face Recognition,"Enhanced Local Gradient Order Features and
+Discriminant Analysis for Face Recognition
+Chuan-Xian Ren, Zhen Lei, Member, IEEE, Dao-Qing Dai, Member, IEEE, and Stan Z. Li, Fellow, IEEE
+role in robust face recognition [5]. Many algorithms have
+een proposed to deal with the effectiveness of feature design
+nd extraction [6], [7]; however, the performance of many
+existing methods is still highly sensitive to variations of
+imaging conditions, such as outdoor illumination, exaggerated
+expression, and continuous occlusion. These complex varia-
+tions are signiﬁcantly affecting the recognition accuracy in
+recent years [8]–[10].
+Appearance-based subspace learning is one of the sim-
+plest approach for feature extraction, and many methods
+re usually based on linear correlation of pixel intensities.
+For example, Eigenface [11] uses eigen system of pixel
+intensities to estimate the lower rank linear subspace of
+set of training face images by minimizing the (cid:2)2 dis-
+tance metric. The solution enjoys optimality properties when
+noise is independent
+identically distributed Gaussian only."
+2322ec2f3571e0ddc593c4e2237a6a794c61251d,Four not six: Revealing culturally common facial expressions of emotion.,"Jack, R. E. , Sun, W., Delis, I., Garrod, O. G. B. and Schyns, P. G. (2016)
+Four not six: revealing culturally common facial expressions of
+emotion.Journal of Experimental Psychology: General, 145(6), pp. 708-
+730.  (doi:10.1037/xge0000162)
+This is the author’s final accepted version.
+There may be differences between this version and the published version.
+You are advised to consult the publisher’s version if you wish to cite from
+http://eprints.gla.ac.uk/116592/
+Deposited on: 20 April 2016
+Enlighten – Research publications by members of the University of Glasgow
+http://eprints.gla.ac.uk"
+23120f9b39e59bbac4438bf4a8a7889431ae8adb,Improved RGB-D-T based face recognition,"Aalborg Universitet
+Improved RGB-D-T based Face Recognition
+Oliu Simon, Marc;   Corneanu, Ciprian; Nasrollahi, Kamal; Guerrero, Sergio Escalera;
+Nikisins, Olegs; Sun, Yunlian; Li, Haiqing; Sun, Zhenan; Moeslund, Thomas B.; Greitans,
+Modris
+Published in:
+DOI (link to publication from Publisher):
+0.1049/iet-bmt.2015.0057
+Publication date:
+Document Version
+Accepted manuscript, peer reviewed version
+Link to publication from Aalborg University
+Citation for published version (APA):
+Oliu Simon, M.,   Corneanu, C., Nasrollahi, K., Guerrero, S. E., Nikisins, O., Sun, Y., ... Greitans, M. (2016).
+General rights
+Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners
+nd it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.
+? Users may download and print one copy of any publication from the public portal for the purpose of private study or research.
+? You may not further distribute the material or use it for any profit-making activity or commercial gain
+? You may freely distribute the URL identifying the publication in the public portal ?"
+23d55061f7baf2ffa1c847d356d8f76d78ebc8c1,Generic and attribute-specific deep representations for maritime vessels,"Solmaz et al. IPSJ Transactions on Computer Vision and
+Applications  (2017) 9:22
+DOI 10.1186/s41074-017-0033-4
+IPSJ Transactions on Computer
+Vision and Applications
+RESEARCH PAPER
+Open Access
+Generic and attribute-specific deep
+representations for maritime vessels
+Berkan Solmaz*†
+, Erhan Gundogdu†, Veysel Yucesoy and Aykut Koc"
+23a8d02389805854cf41c9e5fa56c66ee4160ce3,Influence of low resolution of images on reliability of face detection and recognition,"Multimed Tools Appl
+DOI 10.1007/s11042-013-1568-8
+Influence of low resolution of images on reliability
+of face detection and recognition
+Tomasz Marciniak· Agata Chmielewska·
+Radoslaw Weychan· Marianna Parzych·
+Adam Dabrowski
+© The Author(s) 2013. This article is published with open access at SpringerLink.com"
+23b37c2f803a2d4b701e2f39c5f623b2f3e14d8e,Modified Approaches on Face Recognition By using Multisensory Image,"Available Online at www.ijcsmc.com
+International Journal of Computer Science and Mobile Computing
+A Monthly Journal of Computer Science and Information Technology
+ISSN 2320–088X
+IJCSMC, Vol. 2, Issue. 4, April 2013, pg.646 – 649
+RESEARCH ARTICLE
+Modified Approaches on Face Recognition
+By using Multisensory Image
+S. Dhanarajan1, G. Michael2
+Computer Science Department, Bharath University, India
+Computer Science Department, Bharath University, India"
+4f051022de100241e5a4ba8a7514db9167eabf6e,Face Parsing via a Fully-Convolutional Continuous CRF Neural Network,"Face Parsing via a Fully-Convolutional Continuous
+CRF Neural Network
+Lei Zhou, Zhi Liu, Senior Member, IEEE, Xiangjian He, Senior Member, IEEE"
+4faded442b506ad0f200a608a69c039e92eaff11,İstanbul Technical University Institute of Science and Technology Face Recognition under Varying Illumination,"İSTANBUL TECHNICAL UNIVERSITY  INSTITUTE OF SCIENCE AND TECHNOLOGY
+FACE RECOGNITION UNDER VARYING
+ILLUMINATION
+Master Thesis by
+Erald VUÇINI, B.Sc.
+Department :  Computer Engineering
+Programme:  Computer Engineering
+Supervisor: Prof. Dr. Muhittin GÖKMEN
+JUNE 2006"
+4fc936102e2b5247473ea2dd94c514e320375abb,Guess Where? Actor-Supervision for Spatiotemporal Action Localization,"Guess Where? Actor-Supervision for Spatiotemporal Action Localization
+Victor Escorcia1∗
+Cuong D. Dao1
+Mihir Jain3
+KAUST1, University of Amsterdam2, Qualcomm Technologies, Inc.3
+Bernard Ghanem1
+Cees Snoek2∗"
+4f6adc53798d9da26369bea5a0d91ed5e1314df2,Online Nonnegative Matrix Factorization with General Divergences,"IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. , NO. , 2016
+Online Nonnegative Matrix Factorization with
+General Divergences
+Renbo Zhao, Member, IEEE, Vincent Y. F. Tan, Senior Member, IEEE, Huan Xu"
+4f591e243a8f38ee3152300bbf42899ac5aae0a5,Understanding Higher-Order Shape via 3D Shape Attributes,"SUBMITTED TO TPAMI
+Understanding Higher-Order Shape
+via 3D Shape Attributes
+David F. Fouhey, Abhinav Gupta, Andrew Zisserman"
+4f9958946ad9fc71c2299847e9ff16741401c591,Facial Expression Recognition with Recurrent Neural Networks,"Facial Expression Recognition with Recurrent Neural Networks
+Alex Graves, J¨urgen Schmidhuber
+Robotics and Embedded Systems Lab, Department of Computer Science
+Image Understanding and Knowledge-Based Systems, Department of Computer Science
+Christoph Mayer, Matthias Wimmer, Bernd Radig
+Technische Universit¨at M¨unchen, Germany"
+4f4f920eb43399d8d05b42808e45b56bdd36a929,A Novel Method for 3 D Image Segmentation with Fusion of Two Images using Color K-means Algorithm,"International Journal of Computer Applications (0975 – 8887)
+Volume 123 – No.4, August 2015
+A Novel Method for 3D Image Segmentation with Fusion
+of Two Images using Color K-means Algorithm
+Neelam Kushwah
+Dept. of CSE
+ITM Universe
+Gwalior
+Priusha Narwariya
+Dept. of CSE
+ITM Universe
+Gwalior"
+4f77a37753c03886ca9c9349723ec3bbfe4ee967,"Localizing Facial Keypoints with Global Descriptor Search, Neighbour Alignment and Locally Linear Models","Localizing Facial Keypoints with Global Descriptor Search,
+Neighbour Alignment and Locally Linear Models
+Md. Kamrul Hasan1, Christopher Pal1 and Sharon Moalem2
+´Ecole Polytechnique de Montr´eal, Universit´e de Montr´eal
+University of Toronto and Recognyz Systems Technologies
+lso focused on emotion recognition in the wild [9]."
+8de06a584955f04f399c10f09f2eed77722f6b1c,Facial Landmarks Localization Estimation by Cascaded Boosted Regression,"Author manuscript, published in ""International Conference on Computer Vision Theory and Applications (VISAPP 2013) (2013)"""
+8d4f0517eae232913bf27f516101a75da3249d15,Event-based Dynamic Face Detection and Tracking Based on Activity,"ARXIV SUBMISSION, MARCH 2018
+Event-based Dynamic Face Detection and
+Tracking Based on Activity
+Gregor Lenz, Sio-Hoi Ieng and Ryad Benosman"
+8de2dbe2b03be8a99628ffa000ac78f8b66a1028,Action Recognition in Videos,"´Ecole Nationale Sup´erieure dInformatique et de Math´ematiques Appliqu´ees de Grenoble
+INP Grenoble – ENSIMAG
+UFR Informatique et Math´ematiques Appliqu´ees de Grenoble
+Rapport de stage de Master 2 et de projet de ﬁn d’´etudes
+Effectu´e au sein de l’´equipe LEAR, I.N.R.I.A., Grenoble
+Action Recognition in Videos
+Gaidon Adrien
+e ann´ee ENSIMAG – Option I.I.I.
+M2R Informatique – sp´ecialit´e I.A.
+04 f´evrier 2008 – 04 juillet 2008
+LEAR,
+I.N.R.I.A., Grenoble
+655 avenue de l’Europe
+8 334 Montbonnot
+France
+Responsable de stage
+Mme. Cordelia Schmid
+Tuteur ´ecole
+M. Augustin Lux
+M. Roger Mohr"
+8d3fbdb9783716c1832a0b7ab1da6390c2869c14,Discriminant Subspace Analysis for Uncertain Situation in Facial Recognition,"Discriminant Subspace Analysis for Uncertain
+Situation in Facial Recognition
+Pohsiang Tsai, Tich Phuoc Tran, Tom Hintz and Tony Jan
+School of Computing and Communications – University of Technology, Sydney
+Australia
+. Introduction
+Facial    analysis  and  recognition  have  received  substential  attention  from  researchers  in
+iometrics,  pattern  recognition,  and  computer  vision  communities.  They  have  a  large
+number  of  applications,  such  as  security,  communication,  and  entertainment.  Although  a
+great deal of efforts has been devoted to automated face recognition systems, it still remains
+challenging uncertainty problem. This is because human facial appearance has potentially
+of very large intra-subject variations of head pose, illumination, facial expression, occlusion
+due to other objects or accessories, facial hair and aging. These misleading variations may
+ause classifiers to degrade generalization performance.
+It is important for face recognition systems to employ an effective feature extraction scheme
+to  enhance  separability  between  pattern  classes  which  should  maintain  and  enhance
+features of the input data that make distinct pattern classes separable (Jan, 2004). In general,
+there  exist  a  number  of  different  feature  extraction  methods.  The  most  common  feature
+extraction  methods  are  subspace  analysis  methods  such  as  principle  component  analysis
+(PCA)  (Kirby  &  Sirovich,  1990)  (Jolliffe,  1986)  (Turk  &  Pentland,  1991b),  kernel  principle"
+8d42a24d570ad8f1e869a665da855628fcb1378f,An Empirical Study of Context in Object Detection,"CVPR 2009 Submission #987. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.
+An Empirical Study of Context in Object Detection
+Anonymous CVPR submission
+Paper ID 987"
+8d8461ed57b81e05cc46be8e83260cd68a2ebb4d,Age identification of Facial Images using Neural Network,"Age identification of Facial Images using Neural
+Network
+Sneha Thakur, Ligendra Verma
+CSE Department,CSVTU
+RIT, Raipur, Chhattisgarh , INDIA"
+8d384e8c45a429f5c5f6628e8ba0d73c60a51a89,Temporal Dynamic Graph LSTM for Action-Driven Video Object Detection,"Temporal Dynamic Graph LSTM for Action-driven Video Object Detection
+Yuan Yuan1 Xiaodan Liang2 Xiaolong Wang2 Dit-Yan Yeung1 Abhinav Gupta2
+The Hong Kong University of Science and Technology 2 Carneige Mellon University"
+8d1adf0ac74e901a94f05eca2f684528129a630a,Facial Expression Recognition Using Facial Movement Features,"Facial Expression Recognition Using Facial
+Movement Features"
+8d646ac6e5473398d668c1e35e3daa964d9eb0f6,Memory-Efficient Global Refinement of Decision-Tree Ensembles and its Application to Face Alignment,"MEMORY-EFFICIENT GLOBAL REFINEMENT OF DECISION-TREE ENSEMBLES AND
+ITS APPLICATION TO FACE ALIGNMENT
+Nenad Markuˇs†
+Ivan Gogi´c†
+Igor S. Pandˇzi´c†
+J¨orgen Ahlberg‡
+University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, 10000 Zagreb, Croatia
+Computer Vision Laboratory, Dept. of Electrical Engineering, Link¨oping University, SE-581 83 Link¨oping, Sweden"
+8dffbb6d75877d7d9b4dcde7665888b5675deee1,Emotion Recognition with Deep-Belief Networks,"Emotion Recognition with Deep-Belief
+Networks
+Tom McLaughlin, Mai Le, Naran Bayanbat
+Introduction
+For  our  CS229  project,  we  studied  the  problem  of
+reliable  computerized  emotion  recognition  in  images  of
+human
+faces.  First,  we  performed  a  preliminary
+exploration using SVM classifiers, and then developed an
+pproach based on Deep Belief Nets. Deep Belief Nets, or
+DBNs,  are  probabilistic  generative  models  composed  of
+multiple  layers  of  stochastic  latent  variables,  where  each
+“building block” layer is a Restricted Boltzmann Machine
+(RBM).  DBNs  have  a  greedy  layer-wise  unsupervised
+learning algorithm as well as a discriminative fine-tuning
+procedure  for  optimizing  performance  on  classification
+tasks. [1].
+We  trained  our  classifier  on  three  databases:  the
+Cohn-Kanade Extended Database (CK+) [2], the Japanese
+Female  Facial Expression  Database (JAFFE) [3], and the"
+8d5998cd984e7cce307da7d46f155f9db99c6590,ChaLearn looking at people: A review of events and resources,"ChaLearn Looking at People:
+A Review of Events and Resources
+Sergio Escalera1,2, Xavier Bar´o2,3, Hugo Jair Escalante4,5, Isabelle Guyon4,6,
+Dept. Mathematics and Computer Science, UB, Spain,
+Computer Vision Center, UAB, Barcelona, Spain,
+EIMT, Open University of Catalonia, Barcelona, Spain,
+ChaLearn, California, USA, 5 INAOE, Puebla, Mexico,
+6 Universit´e Paris-Saclay, Paris, France,
+http://chalearnlap.cvc.uab.es"
+8dce38840e6cf5ab3e0d1b26e401f8143d2a6bff,Towards large scale multimedia indexing: A case study on person discovery in broadcast news,"Towards large scale multimedia indexing:
+A case study on person discovery in broadcast news
+Nam Le1, Hervé Bredin2, Gabriel Sargent3, Miquel India5, Paula Lopez-Otero6,
+Claude Barras2, Camille Guinaudeau2, Guillaume Gravier3, Gabriel Barbosa da Fonseca4,
+Izabela Lyon Freire4, Zenilton Patrocínio Jr4, Silvio Jamil F. Guimarães4, Gerard Martí5,
+Josep Ramon Morros5, Javier Hernando5, Laura Docio-Fernandez6, Carmen Garcia-Mateo6,
+Sylvain Meignier7, Jean-Marc Odobez1
+Idiap Research Institute & EPFL, 2 LIMSI, CNRS, Univ. Paris-Sud, Université Paris-Saclay,
+CNRS, Irisa & Inria Rennes, 4 PUC de Minas Gerais, Belo Horizonte,
+5 Universitat Politècnica de Catalunya, 6 University of Vigo, 7 LIUM, University of Maine"
+153f5ad54dd101f7f9c2ae17e96c69fe84aa9de4,Overview of algorithms for face detection and tracking,"Overview of algorithms for face detection and
+tracking
+Nenad Markuˇs"
+15cd05baa849ab058b99a966c54d2f0bf82e7885,Structured Sparse Subspace Clustering: A unified optimization framework,"Structured Sparse Subspace Clustering: A Uniﬁed Optimization Framework
+Chun-Guang Li1, René Vidal2
+SICE, Beijing University of Posts and Telecommunications. 2Center for Imaging Science, Johns Hopkins University.
+In many real-world applications, we need to deal with high-dimensional
+datasets, such as images, videos, text, and more. In practice, such high-
+dimensional datasets can be well approximated by multiple low-dimensional
+subspaces corresponding to multiple classes or categories. For example, the
+feature point trajectories associated with a rigidly moving object in a video
+lie in an afﬁne subspace (of dimension up to 4), and face images of a subject
+under varying illumination lie in a linear subspace (of dimension up to 9).
+Therefore, the task, known in the literature as subspace clustering [6], is
+to segment the data into the corresponding subspaces and ﬁnds multiple
+pplications in computer vision.
+State of the art approaches [1, 2, 3, 4, 5, 7] for solving this problem fol-
+low a two-stage approach: a) Construct an afﬁnity matrix between points by
+exploiting the ‘self-expressiveness’ property of the data, which allows any
+data point to be represented as a linear (or afﬁne) combination of the other
+data points; b) Apply spectral clustering on the afﬁnity matrix to recover
+the data segmentation. Dividing the problem in two steps is, on the one
+hand, appealing because the ﬁrst step can be solved using convex optimiza-"
+15136c2f94fd29fc1cb6bedc8c1831b7002930a6,Deep Learning Architectures for Face Recognition in Video Surveillance,"Deep Learning Architectures for Face
+Recognition in Video Surveillance
+Saman Bashbaghi, Eric Granger, Robert Sabourin and Mostafa Parchami"
+153e5cddb79ac31154737b3e025b4fb639b3c9e7,Active Dictionary Learning in Sparse Representation Based Classification,"PREPRINT SUBMITTED TO IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
+Active Dictionary Learning in Sparse
+Representation Based Classiﬁcation
+Jin Xu, Haibo He, Senior Member, IEEE, and Hong Man, Senior Member, IEEE"
+157eb982da8fe1da4c9e07b4d89f2e806ae4ceb6,Connecting the dots in multi-class classification: From nearest subspace to collaborative representation,"MITSUBISHI ELECTRIC RESEARCH LABORATORIES
+http://www.merl.com
+Connecting the Dots in Multi-Class Classiﬁcation: From
+Nearest Subspace to Collaborative Representation
+Chi, Y.; Porikli, F.
+TR2012-043
+June 2012"
+15e0b9ba3389a7394c6a1d267b6e06f8758ab82b,The OU-ISIR Gait Database comprising the Large Population Dataset with Age and performance evaluation of age estimation,"Xu et al. IPSJ Transactions on Computer Vision and
+Applications  (2017) 9:24
+DOI 10.1186/s41074-017-0035-2
+IPSJ Transactions on Computer
+Vision and Applications
+TECHNICAL NOTE
+Open Access
+The OU-ISIR Gait Database comprising the
+Large Population Dataset with Age and
+performance evaluation of age estimation
+Chi Xu1,2, Yasushi Makihara2*, Gakuto Ogi2, Xiang Li1,2, Yasushi Yagi2 and Jianfeng Lu1"
+15aa6c457678e25f6bc0e818e5fc39e42dd8e533,Conditional Image Generation for Learning the Structure of Visual Objects,
+15cf1f17aeba62cd834116b770f173b0aa614bf4,Facial Expression Recognition using Neural Network with Regularized Backpropagation Algorithm,"International Journal of Computer Applications (0975 – 8887)
+Volume 77 – No.5, September 2013
+Facial Expression Recognition using Neural Network with
+Regularized Back-propagation Algorithm
+Ashish Kumar Dogra
+Research Scholar
+Department of ECE,
+Lovely Professional University,
+Phagwara, India
+Nikesh Bajaj
+Assistant Professor
+Department of ECE,
+Lovely Professional University,
+Phagwara, India
+Harish Kumar Dogra
+Research Scholar
+Department of ECE,
+Gyan Ganga Institute of
+Technology & Sciences,
+Jabalpur, India"
+15f3d47b48a7bcbe877f596cb2cfa76e798c6452,Automatic face analysis tools for interactive digital games,"Automatic face analysis tools for interactive digital games
+Anonymised for blind review
+Anonymous
+Anonymous
+Anonymous"
+15728d6fd5c9fc20b40364b733228caf63558c31,Expanding the Breadth and Detail of Object Recognition By,(cid:13) 2013 Ian N. Endres
+153c8715f491272b06dc93add038fae62846f498,On Clustering Images of Objects,"(cid:13) Copyright by Jongwoo Lim, 2005"
+122ee00cc25c0137cab2c510494cee98bd504e9f,The Application of Active Appearance Models to Comprehensive Face Analysis Technical Report,"The Application of
+Active Appearance Models to
+Comprehensive Face Analysis
+Technical Report
+Simon Kriegel
+TU M¨unchen
+April 5, 2007"
+12cb3bf6abf63d190f849880b1703ccc183692fe,Guess Who?: A game to crowdsource the labeling of affective facial expressions is comparable to expert ratings,"Guess Who?: A game to crowdsource the labeling of affective facial
+expressions is comparable to expert ratings.
+Barry Borsboom
+Graduation research project, june 2012
+Supervised by: Dr. Joost Broekens
+Leiden University Media Technology Department,"
+12cd96a419b1bd14cc40942b94d9c4dffe5094d2,Leveraging Captions in the Wild to Improve Object Detection,"Proceedings of the 5th Workshop on Vision and Language, pages 29–38,
+Berlin, Germany, August 12 2016. c(cid:13)2016 Association for Computational Linguistics"
+1275852f2e78ed9afd189e8b845fdb5393413614,A Transfer Learning based Feature-Weak-Relevant Method for Image Clustering,"A Transfer Learning based Feature-Weak-Relevant Method for
+Image Clustering
+Bo Dong, Xinnian Wang
+Dalian Maritime University
+Dalian, China"
+12055b8f82d5411f9ad196b60698d76fbd07ac1e,Multiview Facial Landmark Localization in RGB-D Images via Hierarchical Regression With Binary Patterns,"Multiview Facial Landmark Localization in RGB-D
+Images via Hierarchical Regression
+With Binary Patterns
+Zhanpeng Zhang, Student Member, IEEE, Wei Zhang, Member, IEEE, Jianzhuang Liu, Senior Member, IEEE,
+nd Xiaoou Tang, Fellow, IEEE"
+120785f9b4952734818245cc305148676563a99b,Diagnostic automatique de l'état dépressif(Classification of depressive moods),"Diagnostic automatique de l’état dépressif
+S. Cholet
+H. Paugam-Moisy
+Laboratoire de Mathématiques Informatique et Applications (LAMIA - EA 4540)
+Université des Antilles, Campus de Fouillole - Guadeloupe
+Résumé
+Les troubles psychosociaux sont un problème de santé pu-
+lique majeur, pouvant avoir des conséquences graves sur
+le court ou le long terme, tant sur le plan professionnel que
+personnel ou familial. Le diagnostic de ces troubles doit
+être établi par un professionnel. Toutefois, l’IA (l’Intelli-
+gence Artiﬁcielle) peut apporter une contribution en four-
+nissant au praticien une aide au diagnostic, et au patient
+un suivi permanent rapide et peu coûteux. Nous proposons
+une approche vers une méthode de diagnostic automatique
+de l’état dépressif à partir d’observations du visage en
+temps réel, au moyen d’une simple webcam. A partir de
+vidéos du challenge AVEC’2014, nous avons entraîné un
+lassiﬁeur neuronal à extraire des prototypes de visages
+selon différentes valeurs du score de dépression de Beck"
+12ebeb2176a5043ad57bc5f3218e48a96254e3e9,Traffic Road Sign Detection and Recognition for Automotive Vehicles,"International Journal of Computer Applications (0975 – 8887)
+Volume 120 – No.24, June 2015
+Traffic Road Sign Detection and Recognition for
+Automotive Vehicles
+Md. Safaet Hossain
+Zakir Hyder
+Department of Electrical Engineering and
+Department of Electrical Engineering and
+Computer Science North South University, Dhaka
+Computer Science North South University, Dhaka
+Bangladesh
+Bangladesh"
+12150d8b51a2158e574e006d4fbdd3f3d01edc93,Deep End2End Voxel2Voxel Prediction,"Deep End2End Voxel2Voxel Prediction
+Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo
+Torresani, Manohar Paluri
+Presented by: Ahmed Osman
+Ahmed Osman"
+12d8730da5aab242795bdff17b30b6e0bac82998,Persistent Evidence of Local Image Properties in Generic ConvNets,"Persistent Evidence of Local Image Properties in Generic ConvNets
+Ali Sharif Razavian, Hossein Azizpour,
+Atsuto Maki, Josephine Sullivan, Carl Henrik Ek, and Stefan Carlsson
+CVAP, KTH (Royal Institute of Technology), Stockholm, SE-10044"
+8c13f2900264b5cf65591e65f11e3f4a35408b48,A Generic Face Representation Approach for Local Appearance Based Face Verification,"A GENERIC FACE REPRESENTATION APPROACH FOR
+LOCAL APPEARANCE BASED FACE VERIFICATION
+Hazim Kemal Ekenel, Rainer Stiefelhagen
+Interactive Systems Labs, Universität Karlsruhe (TH)
+76131 Karlsruhe, Germany
+{ekenel,
+web: http://isl.ira.uka.de/face_recognition/"
+8c955f3827a27e92b6858497284a9559d2d0623a,Facial Expression Recognition under Noisy Environment Using Gabor Filters,"Buletinul Ştiinţific al Universităţii ""Politehnica"" din Timişoara
+Seria ELECTRONICĂ şi TELECOMUNICAŢII
+TRANSACTIONS on ELECTRONICS and COMMUNICATIONS
+Tom 53(67), Fascicola 1-2, 2008
+Facial Expression Recognition under Noisy Environment
+Using Gabor Filters
+Ioan Buciu1, I. Nafornita2, I. Pitas3"
+8c7f4c11b0c9e8edf62a0f5e6cf0dd9d2da431fa,Dataset Augmentation for Pose and Lighting Invariant Face Recognition,"Dataset Augmentation for Pose and Lighting
+Invariant Face Recognition
+Daniel Crispell∗, Octavian Biris∗, Nate Crosswhite†, Jeffrey Byrne†, Joseph L. Mundy∗
+Vision Systems, Inc.
+Systems and Technology Research"
+8ce9b7b52d05701d5ef4a573095db66ce60a7e1c,Structured Sparse Subspace Clustering: A Joint Affinity Learning and Subspace Clustering Framework,"Structured Sparse Subspace Clustering: A Joint
+Afﬁnity Learning and Subspace Clustering
+Framework
+Chun-Guang Li, Chong You, and Ren´e Vidal"
+8cb6daba2cb1e208e809633133adfee0183b8dd2,Know Before You Do: Anticipating Maneuvers via Learning Temporal Driving Models,"Know Before You Do: Anticipating Maneuvers
+via Learning Temporal Driving Models
+Ashesh Jain, Hema S Koppula, Bharad Raghavan, Shane Soh, Ashutosh Saxena
+Cornell University and Stanford University"
+8c6c0783d90e4591a407a239bf6684960b72f34e,SESSION KNOWLEDGE ENGINEERING AND MANAGEMENT + KNOWLEDGE ACQUISITION Chair(s),"SESSION
+KNOWLEDGE ENGINEERING AND
+MANAGEMENT + KNOWLEDGE ACQUISITION
+Chair(s)
+Int'l Conf. Information and Knowledge Engineering | IKE'13 |1"
+8cc07ae9510854ec6e79190cc150f9f1fe98a238,Using Deep Learning to Challenge Safety Standard for Highly Autonomous Machines in Agriculture,"Article
+Using Deep Learning to Challenge Safety Standard
+for Highly Autonomous Machines in Agriculture
+Kim Arild Steen *,†, Peter Christiansen †, Henrik Karstoft and Rasmus Nyholm Jørgensen
+Department of Engineering, Aarhus University, Finlandsgade 22 8200 Aarhus N, Denmark;
+(P.C.); (H.K.); (R.N.J.)
+* Correspondence: Tel.: +45-3116-8628
+These authors contributed equally to this work.
+Academic Editors: Francisco Rovira-Más and Gonzalo Pajares Martinsanz
+Received: 18 December 2015; Accepted: 2 February 2016; Published: 15 February 2016"
+8509abbde2f4b42dc26a45cafddcccb2d370712f,A way to improve precision of face recognition in SIPP without retrain of the deep neural network model,"Improving precision and recall of face recognition in SIPP with combination of
+modiﬁed mean search and LSH
+Xihua.Li"
+858ddff549ae0a3094c747fb1f26aa72821374ec,"Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications","Survey on RGB, 3D, Thermal, and Multimodal
+Approaches for Facial Expression Recognition:
+History, Trends, and Affect-related Applications
+Ciprian A. Corneanu, Marc Oliu, Jeffrey F. Cohn, and Sergio Escalera"
+858901405086056361f8f1839c2f3d65fc86a748,On Tensor Tucker Decomposition: the Case for an Adjustable Core Size,"ON TENSOR TUCKER DECOMPOSITION: THE CASE FOR AN
+ADJUSTABLE CORE SIZE
+BILIAN CHEN ∗, ZHENING LI † , AND SHUZHONG ZHANG ‡"
+85188c77f3b2de3a45f7d4f709b6ea79e36bd0d9,"Combined model for detecting, localizing, interpreting and recognizing faces","Author manuscript, published in ""Workshop on Faces in 'Real-Life' Images: Detection, Alignment, and Recognition, Marseille :
+France (2008)"""
+8518b501425f2975ea6dcbf1e693d41e73d0b0af,Relative Hidden Markov Models for Evaluating Motion Skill,"Relative Hidden Markov Models for Evaluating Motion Skills
+Qiang Zhang and Baoxin Li
+Computer Science and Engineering
+Arizona State Univerisity, Tempe, AZ 85281"
+854dbb4a0048007a49df84e3f56124d387588d99,Spatial-Temporal Recurrent Neural Network for Emotion Recognition,"JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014
+Spatial-Temporal Recurrent Neural Network for
+Emotion Recognition
+Tong Zhang, Wenming Zheng*, Member, IEEE, Zhen Cui*, Yuan Zong and Yang Li"
+1d7ecdcb63b20efb68bcc6fd99b1c24aa6508de9,The Hidden Sides of Names&#x2014;Face Modeling with First Name Attributes,"The Hidden Sides of Names—Face Modeling
+with First Name Attributes
+Huizhong Chen, Student Member, IEEE, Andrew C. Gallagher, Senior Member, IEEE, and
+Bernd Girod, Fellow, IEEE"
+1d1a7ef193b958f9074f4f236060a5f5e7642fc1,Ensemble of Patterns of Oriented Edge Magnitudes Descriptors For Face Recognition,"Int'l Conf. IP, Comp.  Vision, and Pattern Recognition |  IPCV'13  \
+Ensemble of Patterns of Oriented Edge Magnitudes
+Descriptors For Face Recognition
+Loris Nanni,1 Alessandra Lumini,2 Sheryl Brahnam,3 Mauro M igliardi1
+*DEI, University o f Padua, viale Gradenigo 6, Padua, Italy,  {loris.nanni,
+DEI, Universita di Bologna, Via Venezia 52, 47521  Cesena, Italy, unibo.it;
+Computer Information Systems, Missouri State University, 901  S. National, Springfield, MO 65804, USA.
+faces; and 3) face tagging, which is a particular case of face
+identification."
+1d0dd20b9220d5c2e697888e23a8d9163c7c814b,Boosted Metric Learning for Efficient Identity-Based Face Retrieval,"NEGREL ET AL.: BOOSTED METRIC LEARNING FOR FACE RETRIEVAL
+Boosted Metric Learning for Efﬁcient
+Identity-Based Face Retrieval
+Romain Negrel
+Alexis Lechervy
+Frederic Jurie
+GREYC, CNRS UMR 6072, ENSICAEN
+Université de Caen Basse-Normandie
+France"
+1d776bfe627f1a051099997114ba04678c45f0f5,Deployment of Customized Deep Learning based Video Analytics On Surveillance Cameras,"Deployment of Customized Deep Learning based
+Video Analytics On Surveillance Cameras
+Pratik Dubal(cid:63), Rohan Mahadev(cid:63), Suraj Kothawade(cid:63),
+Kunal Dargan, and Rishabh Iyer
+AitoeLabs (www.aitoelabs.com)"
+1dff919e51c262c22630955972968f38ba385d8a,Toward an Affect-Sensitive Multimodal Human–Computer Interaction,"Toward an Affect-Sensitive Multimodal
+Human–Computer Interaction
+MAJA PANTIC, MEMBER, IEEE, AND LEON J. M. ROTHKRANTZ
+Invited Paper
+The ability to recognize affective states of a person we are com-
+municating with is the core of emotional intelligence. Emotional
+intelligenceisa facet of human intelligence thathas been argued to be
+indispensable and perhaps the most important for successful inter-
+personal social interaction. This paper argues that next-generation
+human–computer interaction (HCI) designs need to include the
+essence of emotional intelligence—the ability to recognize a user’s
+ffective states—in order to become more human-like, more effec-
+tive, and more efficient. Affective arousal modulates all nonverbal
+ommunicative cues (facial expressions, body movements, and vocal
+nd physiological reactions). In a face-to-face interaction, humans
+detect and interpret those interactive signals of their communicator
+with little or no effort. Yet design and development of an automated
+system that accomplishes these tasks is rather difficult. This paper
+surveys the past work in solving these problems by a computer
+nd provides a set of recommendations for developing the first"
+1de8f38c35f14a27831130060810cf9471a62b45,A Branch-and-Bound Framework for Unsupervised Common Event Discovery,"Int J Comput Vis
+DOI 10.1007/s11263-017-0989-7
+A Branch-and-Bound Framework for Unsupervised Common
+Event Discovery
+Wen-Sheng Chu1
+Jeffrey F. Cohn1,2 · Daniel S. Messinger3
+· Fernando De la Torre1 ·
+Received: 3 June 2016 / Accepted: 12 January 2017
+© Springer Science+Business Media New York 2017"
+1da83903c8d476c64c14d6851c85060411830129,Iterated Support Vector Machines for Distance Metric Learning,"Iterated Support Vector Machines for Distance
+Metric Learning
+Wangmeng Zuo, Member, IEEE, Faqiang Wang, David Zhang, Fellow, IEEE, Liang Lin, Member, IEEE,
+Yuchi Huang, Member, IEEE, Deyu Meng, and Lei Zhang, Senior Member, IEEE"
+1d58d83ee4f57351b6f3624ac7e727c944c0eb8d,Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions,"Enhanced Local Texture
+Feature Sets for Face
+Recognition under Difficult
+Lighting Conditions
+Xiaoyang Tan and Bill Triggs
+INRIA & Laboratoire Jean
+Kuntzmann,
+655 avenue de l'Europe, Montbonnot 38330, France"
+1d729693a888a460ee855040f62bdde39ae273af,Photorealistic Face De-Identification by Aggregating Donors' Face Components,"Photorealistic Face de-Identiﬁcation by Aggregating
+Donors’ Face Components
+Saleh Mosaddegh, Lo¨ıc Simon, Fr´ed´eric Jurie
+To cite this version:
+Saleh Mosaddegh, Lo¨ıc Simon, Fr´ed´eric Jurie. Photorealistic Face de-Identiﬁcation by Aggre-
+gating Donors’ Face Components. Asian Conference on Computer Vision, Nov 2014, Singapore.
+pp.1-16, 2014. <hal-01070658>
+HAL Id: hal-01070658
+https://hal.archives-ouvertes.fr/hal-01070658
+Submitted on 2 Oct 2014
+HAL is a multi-disciplinary open access
+rchive for the deposit and dissemination of sci-
+entiﬁc research documents, whether they are pub-
+lished or not. The documents may come from
+teaching and research institutions in France or
+broad, or from public or private research centers.
+L’archive ouverte pluridisciplinaire HAL, est
+destin´ee au d´epˆot et `a la diffusion de documents
+scientiﬁques de niveau recherche, publi´es ou non,
+´emanant des ´etablissements d’enseignement et de"
+1d4c25f9f8f08f5a756d6f472778ab54a7e6129d,An Innovative Mean Approach for Plastic Surgery Face Recognition,"International Journal of Science and Research (IJSR)
+ISSN (Online): 2319-7064
+Index Copernicus Value (2014): 6.14 | Impact Factor (2014): 4.438
+An Innovative Mean Approach for Plastic Surgery
+Face Recognition
+Mahendra P. Randive1, Umesh W. Hore2
+Student of M.E., Department of Electronics & Telecommunication Engineering,
+P. R. Patil College of Engineering, Amravati Maharashtra – India
+Assistant Professor, Department of Electronics & Telecommunication Engineering,
+P. R. Patil College of Engineering, Amravati Maharashtra – India"
+71b376dbfa43a62d19ae614c87dd0b5f1312c966,The temporal connection between smiles and blinks,"The Temporal Connection Between Smiles and Blinks
+Laura C. Trutoiu, Jessica K. Hodgins, and Jeffrey F. Cohn"
+718824256b4461d62d192ab9399cfc477d3660b4,Selecting Training Data for Cross-Corpus Speech Emotion Recognition: Prototypicality vs. Generalization,"Selecting Training Data for Cross-Corpus Speech Emotion Recognition:
+Prototypicality vs. Generalization
+Bj¨orn Schuller, Zixing Zhang, Felix Weninger, and Gerhard Rigoll
+Institute for Human-Machine Communication, Technische Universit¨at M¨unchen, Germany"
+714d487571ca0d676bad75c8fa622d6f50df953b,eBear: An expressive Bear-Like robot,"eBear: An Expressive Bear-Like Robot
+Xiao Zhang, Ali Mollahosseini, Amir H. Kargar B., Evan Boucher,
+Richard M. Voyles, Rodney Nielsen and Mohammd H. Mahoor"
+710011644006c18291ad512456b7580095d628a2,Learning Residual Images for Face Attribute Manipulation,"Learning Residual Images for Face Attribute Manipulation
+Wei Shen
+Rujie Liu
+Fujitsu Research & Development Center, Beijing, China.
+{shenwei,"
+711bb5f63139ee7a9b9aef21533f959671a7d80e,Objects extraction and recognition for camera-based interaction : heuristic and statistical approaches,"Helsinki University of Technology Laboratory of Computational Engineering Publications
+Teknillisen korkeakoulun Laskennallisen tekniikan laboratorion julkaisuja
+Espoo 2007
+REPORT B68
+OBJECTS EXTRACTION AND RECOGNITION FOR
+CAMERA-BASED INTERACTION: HEURISTIC AND
+STATISTICAL APPROACHES
+Hao Wang
+TEKNILLINEN KORKEAKOULU
+TEKNILLINEN KORKEAKOULU
+TEKNISKA HÖGSKOLAN
+TEKNISKA HÖGSKOLAN
+HELSINKI UNIVERSITY OF TECHNOLOGY
+HELSINKI UNIVERSITY OF TECHNOLOGY
+TECHNISCHE UNIVERSITÄT HELSINKI
+TECHNISCHE UNIVERSITÄT HELSINKI
+UNIVERSITE DE TECHNOLOGIE D'HELSINKI
+UNIVERSITE DE TECHNOLOGIE D'HELSINKI"
+76fd801981fd69ff1b18319c450cb80c4bc78959,Alignment of Eye Movements and Spoken Language for Semantic Image Understanding,"Proceedings of the 11th International Conference on Computational Semantics, pages 76–81,
+London, UK, April 15-17 2015. c(cid:13)2015 Association for Computational Linguistics"
+76dc11b2f141314343d1601635f721fdeef86fdb,Weighted Decoding ECOC for Facial Action Unit Classification,"Weighted Decoding ECOC for Facial
+Action Unit Classiﬁcation
+Terry Windeatt"
+76673de6d81bedd6b6be68953858c5f1aa467e61,Discovering a Lexicon of Parts and Attributes,"Discovering a Lexicon of Parts and Attributes
+Subhransu Maji
+Toyota Technological Institute at Chicago,
+Chicago, IL 60637, USA"
+76cd5e43df44e389483f23cb578a9015d1483d70,Face Verification from Depth using Privileged Information,"BORGHI ET AL.: FACE VERIFICATION FROM DEPTH
+Face Veriﬁcation from Depth using
+Privileged Information
+Department of Engineering
+""Enzo Ferrari""
+University of Modena and Reggio
+Emilia
+Modena, Italy
+Guido Borghi
+Stefano Pini
+Filippo Grazioli
+Roberto Vezzani
+Rita Cucchiara"
+76b11c281ac47fe6d95e124673a408ee9eb568e3,Real-time Multi View Face Detection and Pose Estimation Aishwarya,"International Journal of Latest Engineering and Management Research (IJLEMR)
+ISSN: 2455-4847
+www.ijlemr.com || Volume 02 - Issue 03 || March 2017 || PP. 59-71
+REAL-TIME MULTI VIEW FACE DETECTION AND POSE
+ESTIMATION
+AISHWARYA.S1 , RATHNAPRIYA.K1, SUKANYA SARGUNAR.V2
+U. G STUDENTS, DEPT OF CSE, ALPHA COLLEGE OF ENGINEERING, CHENNAI,
+ASST PROF.DEPARTMENT OF CSE, ALPHA COLLEGE OF ENGINEERING, CHENNAI"
+76d9f5623d3a478677d3f519c6e061813e58e833,Fast Algorithms for the Generalized Foley-Sammon Discriminant Analysis,"FAST ALGORITHMS FOR THE GENERALIZED FOLEY-SAMMON
+DISCRIMINANT ANALYSIS
+LEI-HONG ZHANG∗, LI-ZHI LIAO† , AND MICHAEL K. NG‡"
+76e2d7621019bd45a5851740bd2742afdcf62837,Real-Time Detection and Measurement of Eye Features from Color Images,"Article
+Real-Time Detection and Measurement of Eye
+Features from Color Images
+Diana Borza 1, Adrian Sergiu Darabant 2 and Radu Danescu 1,*
+Computer Science Department, Technical University of Cluj Napoca, 28 Memorandumului Street,
+Cluj Napoca 400114, Romania;
+Computer Science Department, Babes Bolyai University, 58-60 Teodor Mihali, C333, Cluj Napoca 400591,
+Romania;
+* Correspondence: Tel.: +40-740-502-223
+Academic Editors: Changzhi Li, Roberto Gómez-García and José-María Muñoz-Ferreras
+Received: 28 April 2016; Accepted: 14 July 2016; Published: 16 July 2016"
+765b2cb322646c52e20417c3b44b81f89860ff71,PoseShop: Human Image Database Construction and Personalized Content Synthesis,"PoseShop: Human Image Database
+Construction and Personalized
+Content Synthesis
+Tao Chen, Ping Tan, Member, IEEE, Li-Qian Ma, Ming-Ming Cheng, Member, IEEE,
+Ariel Shamir, and Shi-Min Hu, Member, IEEE"
+763158cef9d1e4041f24fce4cf9d6a3b7a7f08ff,Hierarchical Modeling and Applications to Recognition Tasks,"Hierarchical Modeling and
+Applications to Recognition Tasks
+Thesis submitted for the degree of
+”Doctor of Philosophy”
+Alon Zweig
+Submitted to the Senate of the Hebrew University
+August / 2013"
+760ba44792a383acd9ca8bef45765d11c55b48d4,Class-specific classifier: avoiding the curse of dimensionality,"INTRODUCTION AND BACKGROUND
+The purpose of this article is to introduce the
+reader to the basic principles of  classification with
+lass-specific features. It is written both for readers
+interested in only the basic concepts as well as those
+interested in getting started in applying the method.
+For in-depth coverage, the reader is referred to a more
+detailed article [l].
+Class-Specific Classifier:
+Avoiding the Curse of
+Dimensionality
+PAUL M. BAGGENSTOSS, Member. lEEE
+US. Naval Undersea Warfare Center
+This article describes a new probabilistic method called the
+“class-specific method” (CSM). CSM has the potential to avoid
+the “curse of dimensionality” which plagues most clmiiiers
+which attempt to determine the decision boundaries in a
+highdimensional featue space. In contrast, in CSM, it is possible
+to build classifiers without a ” n o n   feature space. Separate
+Law-dimensional features seta may be de6ned for each class, while"
+766728bac030b169fcbc2fbafe24c6e22a58ef3c,A survey of deep facial landmark detection,"A survey of deep facial landmark detection
+Yongzhe Yan1,2
+Xavier Naturel2
+Christophe Garcia3
+Thierry Chateau1
+Christophe Blanc1
+Stefan Duffner3
+Université Clermont Auvergne, France
+Wisimage, France
+Université de Lyon, CNRS, INSA Lyon, LIRIS, UMR5205, Lyon, France
+Résumé
+La détection de landmarks joue un rôle crucial dans de
+nombreuses applications d’analyse du visage comme la
+reconnaissance de l’identité, des expressions, l’animation
+d’avatar, la reconstruction 3D du visage, ainsi que pour
+les applications de réalité augmentée comme la pose de
+masque ou de maquillage virtuel. L’avènement de l’ap-
+prentissage profond a permis des progrès très importants
+dans ce domaine, y compris sur les corpus non contraints
+(in-the-wild). Nous présentons ici un état de l’art cen-"
+7697295ee6fc817296bed816ac5cae97644c2d5b,Detecting and Recognizing Human-Object Interactions,"Detecting and Recognizing Human-Object Interactions
+Georgia Gkioxari Ross Girshick
+Piotr Doll´ar Kaiming He
+Facebook AI Research (FAIR)"
+7636f94ddce79f3dea375c56fbdaaa0f4d9854aa,Robust Facial Expression Recognition Using a Smartphone Working against Illumination Variation,"Appl. Math. Inf. Sci. 6 No. 2S pp. 403S-408S (2012)
+An International Journal
+© 2012 NSP
+Applied Mathematics & Information Sciences
+Robust Facial Expression Recognition Using
+Smartphone Working against Illumination Variation
+2012 NSP
+Natural Sciences Publishing Cor.
+Kyoung-Sic Cho1, In-Ho Choi1 and Yong-Guk Kim1
+Department of Computer Engineering, Sejong University, 98 Kunja-Dong, Kwangjin-Gu, Seoul, Korea
+Corresponding author: Email:
+Received June 22, 2010; Revised March 21, 2011; Accepted 11 June 2011
+Published online: 1 January 2012"
+1c80bc91c74d4984e6422e7b0856cf3cf28df1fb,Hierarchical Adaptive Structural SVM for Domain Adaptation,"Noname manuscript No.
+(will be inserted by the editor)
+Hierarchical Adaptive Structural SVM for Domain Adaptation
+Jiaolong Xu · Sebastian Ramos · David V´azquez · Antonio M. L´opez
+Received: date / Accepted: date"
+1ce3a91214c94ed05f15343490981ec7cc810016,Exploring photobios,"Exploring Photobios
+Ira Kemelmacher-Shlizerman1
+Eli Shechtman2
+Rahul Garg1,3
+Steven M. Seitz1,3
+University of Washington∗
+Adobe Systems†
+Google Inc."
+1cfe3533759bf95be1fce8ce1d1aa2aeb5bfb4cc,Recognition of Facial Gestures Based on Support Vector Machines,"Recognition of Facial Gestures based on Support
+Vector Machines
+Attila Fazekas and Istv(cid:19)an S(cid:19)anta
+Faculty of Informatics, University of Debrecen, Hungary
+H-4010 Debrecen P.O.Box 12."
+1ce4587e27e2cf8ba5947d3be7a37b4d1317fbee,Deep fusion of visual signatures for client-server facial analysis,"Deep fusion of visual signatures
+for client-server facial analysis
+Binod Bhattarai
+Normandie Univ, UNICAEN,
+ENSICAEN, CNRS, GREYC
+Gaurav Sharma
+Computer Sc. & Engg.
+IIT Kanpur, India
+Frederic Jurie
+Normandie Univ, UNICAEN,
+ENSICAEN, CNRS, GREYC
+Facial analysis is a key technology for enabling human-
+machine interaction.
+In this context, we present a client-
+server framework, where a client transmits the signature of
+face to be analyzed to the server, and, in return, the server
+sends back various information describing the face e.g. is the
+person male or female, is she/he bald, does he have a mus-
+tache, etc. We assume that a client can compute one (or a
+ombination) of visual features; from very simple and ef‌f‌i-"
+1c30bb689a40a895bd089e55e0cad746e343d1e2,Learning Spatiotemporal Features with 3D Convolutional Networks,"Learning Spatiotemporal Features with 3D Convolutional Networks
+Du Tran1
+, Lubomir Bourdev1, Rob Fergus1, Lorenzo Torresani2, Manohar Paluri1
+Facebook AI Research, 2Dartmouth College"
+1c3073b57000f9b6dbf1c5681c52d17c55d60fd7,Direction de thèse:,"THÈSEprésentéepourl’obtentiondutitredeDOCTEURDEL’ÉCOLENATIONALEDESPONTSETCHAUSSÉESSpécialité:InformatiqueparCharlotteGHYSAnalyse,Reconstruction3D,&AnimationduVisageAnalysis,3DReconstruction,&AnimationofFacesSoutenancele19mai2010devantlejurycomposéde:Rapporteurs:MajaPANTICDimitrisSAMARASExaminateurs:MichelBARLAUDRenaudKERIVENDirectiondethèse:NikosPARAGIOSBénédicteBASCLE"
+1c93b48abdd3ef1021599095a1a5ab5e0e020dd5,A Compositional and Dynamic Model for Face Aging,"JOURNAL OF LATEX CLASS FILES, VOL. *, NO. *, JANUARY 2009
+A Compositional and Dynamic Model for Face Aging
+Jinli Suo , Song-Chun Zhu , Shiguang Shan and Xilin Chen"
+1c6e22516ceb5c97c3caf07a9bd5df357988ceda,Copycat CNN: Stealing Knowledge by Persuading Confession with Random Non-Labeled Data,"NetworkCNNimageslabelsFakeDatasetimages24132labelsTarget NetworkCNNimageslabelsOriginalDatasetFakeDatasetFig.1:Ontheleft,thetargetnetworkistrainedwithanoriginal(conﬁdential)datasetandisservedpubliclyasanAPI,receivingimagesasinputandprovidingclasslabelsasoutput.Ontheright,itispresentedtheprocesstogetstolenlabelsandtocreateafakedataset:randomnaturalimagesaresenttotheAPIandthelabelsareobtained.Afterthat,thecopycatnetworkistrainedusingthisfakedataset.cloud-basedservicestocustomersallowingthemtooffertheirownmodelsasanAPI.Becauseoftheresourcesandmoneyinvestedincreatingthesemodels,itisinthebestinterestofthesecompaniestoprotectthem,i.e.,toavoidthatsomeoneelsecopythem.Someworkshavealreadyinvestigatedthepossibilityofcopyingmodelsbyqueryingthemasablack-box.In[1],forexample,theauthorsshowedhowtoperformmodelextractionattackstocopyanequivalentornear-equivalentmachinelearningmodel(decisiontree,logisticregression,SVM,andmultilayerperceptron),i.e.,onethatachievescloseto100%agreementonaninputspaceofinterest.In[2],theauthorsevaluatedtheprocessofcopyingaNaiveBayesandSVMclassiﬁerinthecontextoftextclassiﬁcation.Bothworksfocusedongeneralclassiﬁersandnotondeepneuralnetworksthatrequirelargeamountsofdatatobetrainedleavingthequestionofwhetherdeepmodelscanbeeasilycopied.Althoughthesecondusesdeeplearningtostealtheclassiﬁers,itdoesnottrytouseDNNstostealfromdeepmodels.Additionally,theseworksfocusoncopyingbyqueryingwithproblemdomaindata.Inrecentyears,researchershavebeenexploringsomeintriguingpropertiesofdeepneuralnetworks[3],[4].More©2018IEEE.Personaluseofthismaterialispermitted.PermissionfromIEEEmustbeobtainedforallotheruses,inanycurrentorfuturemedia,includingreprinting/republishingthismaterialforadvertisingorpromotionalpurposes,creatingnewcollectiveworks,forresaleorredistributiontoserversorlists,orreuseofanycopyrightedcomponentofthisworkinotherworks."
+825f56ff489cdd3bcc41e76426d0070754eab1a8,Making Convolutional Networks Recurrent for Visual Sequence Learning,"Making Convolutional Networks Recurrent for Visual Sequence Learning
+Xiaodong Yang Pavlo Molchanov Jan Kautz
+NVIDIA"
+82d2af2ffa106160a183371946e466021876870d,A Novel Space-Time Representation on the Positive Semidefinite Con for Facial Expression Recognition,"A Novel Space-Time Representation on the Positive Semideﬁnite Cone
+for Facial Expression Recognition
+Anis Kacem1, Mohamed Daoudi1, Boulbaba Ben Amor1, and Juan Carlos Alvarez-Paiva2
+IMT Lille Douai, Univ. Lille, CNRS, UMR 9189 – CRIStAL –
+Centre de Recherche en Informatique Signal et Automatique de Lille, F-59000 Lille, France
+Univ. Lille, CNRS, UMR 8524, Laboratoire Paul Painlev´e, F-59000 Lille, France."
+82eff71af91df2ca18aebb7f1153a7aed16ae7cc,MSU-AVIS dataset : Fusing Face and Voice Modalities for Biometric Recognition in Indoor Surveillance Videos,"MSU-AVIS dataset:
+Fusing Face and Voice Modalities for Biometric
+Recognition in Indoor Surveillance Videos
+Anurag Chowdhury*, Yousef Atoum+, Luan Tran*, Xiaoming Liu*, Arun Ross*
+*Michigan State University, USA
++Yarmouk University, Jordan"
+82c303cf4852ad18116a2eea31e2291325bc19c3,Fusion Based FastICA Method: Facial Expression Recognition,"Journal of Image and Graphics, Volume 2, No.1, June, 2014
+Fusion Based FastICA Method: Facial Expression
+Recognition
+Humayra B. Ali and David M W Powers
+Computer Science, Engineering and Mathematics School, Flinders University, Australia
+Email: {ali0041,"
+8210fd10ef1de44265632589f8fc28bc439a57e6,Single Sample Face Recognition via Learning Deep Supervised Autoencoders,"Single Sample Face Recognition via Learning Deep
+Supervised Auto-Encoders
+Shenghua  Gao,  Yuting  Zhang,  Kui  Jia,  Jiwen  Lu,  Yingying  Zhang"
+82a4a35b2bae3e5c51f4d24ea5908c52973bd5be,Real-time emotion recognition for gaming using deep convolutional network features,"Real-time emotion recognition for gaming using
+deep convolutional network features
+S´ebastien Ouellet"
+829f390b3f8ad5856e7ba5ae8568f10cee0c7e6a,A Robust Rotation Invariant Multiview Face Detection in Erratic Illumination Condition,"International Journal of Computer Applications (0975 – 8887)
+Volume 57– No.20, November 2012
+A Robust Rotation Invariant Multiview Face Detection in
+Erratic Illumination Condition
+G.Nirmala Priya
+Associate Professor, Department of ECE
+Sona College of Technology
+Salem"
+82f4e8f053d20be64d9318529af9fadd2e3547ef,Technical Report: Multibiometric Cryptosystems,"Technical Report:
+Multibiometric Cryptosystems
+Abhishek Nagar, Student Member, IEEE, Karthik Nandakumar, Member, IEEE, and Anil K. Jain, Fellow, IEEE"
+82d781b7b6b7c8c992e0cb13f7ec3989c8eafb3d,Robust Facial Expression Recognition Using a State-based Model of Spatially-localized Facial,"REFERENCES
+Adler  A.,  Youmaran  R.  and  Loyka  S.,  “Towards  a  Measure  of
+Biometric  Information”,  Canadian  Conference  on  Electrical  and
+Computer Engineering, pp. 210-213, 2006.
+Ahmed A.A.E. and Traore I., “Anomaly  Intrusion Detection Based on
+Biometrics”, IEEE Workshop on Information Assurance, United States
+Military Academy, West Point, New York, pp. 452-458, 2005.
+Ahmed  A.A.E.  and  Traore  I.,  “Detecting  Computer  Intrusions  using
+Behavioural  Biometrics”,  Third  Annual  Conference  on  Privacy,
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+005.
+Al-Zubi  S.,  Bromme  A.  and  Tonnies  K.,  “Using  an  Active  Shape
+Structural  Model  for  Biometric  Sketch  Recognition”,  Proceedings  of
+DAGM, Magdeburg, Germany, Vol. 2781, pp. 187-195, 2003.
+Angle S., Bhagtani R. and Chheda H., “Biometrics: a Further Echelon
+of  Security”,  The  First  UAE  International  Conference  on  Biological
+nd Medical Physics, pp. 1-4, 2005.
+Avraam  Kasapis.,  “MLPs  and  Pose,  Expression  Classification”,
+Proceedings of UNiS Report, pp. 1-87, 2003.
+Banikazemi  M.,  Poff  D.  and  Abali  B.,  “Storage-based  Intrusion"
+82417d8ec8ac6406f2d55774a35af2a1b3f4b66e,Some Faces are More Equal than Others: Hierarchical Organization for Accurate and Efficient Large-Scale Identity-Based Face Retrieval,"Some faces are more equal than others:
+Hierarchical organization for accurate and
+ef‌f‌icient large-scale identity-based face retrieval
+Binod Bhattarai1, Gaurav Sharma2, Fr´ed´eric Jurie1, Patrick P´erez2
+GREYC, CNRS UMR 6072, Universit´e de Caen Basse-Normandie, France1
+Technicolor, Rennes, France2"
+826c66bd182b54fea3617192a242de1e4f16d020,Action-vectors: Unsupervised movement modeling for action recognition,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE
+ICASSP 2017"
+4919663c62174a9bc0cc7f60da8f96974b397ad2,Human age estimation using enhanced bio-inspired features (EBIF),"HUMAN AGE ESTIMATION USING ENHANCED BIO-INSPIRED FEATURES (EBIF)
+Mohamed Y.El Dib and Motaz El-Saban
+Faculty of Computers and Information, Cairo University, Cairo, Egypt"
+4967b0acc50995aa4b28e576c404dc85fefb0601,An Automatic Face Detection and Gender Classification from Color Images using Support Vector Machine,"Vol. 4, No. 1 Jan 2013                                                                                                 ISSN 2079-8407
+Journal of Emerging Trends in Computing and Information Sciences
+©2009-2013 CIS Journal. All rights reserved.
+An Automatic Face Detection and Gender Classification from
+http://www.cisjournal.org
+Color Images using Support Vector Machine
+Md. Hafizur Rahman, 2 Suman Chowdhury, 3 Md. Abul Bashar
+, 2, 3 Department of Electrical & Electronic Engineering, International
+University of Business Agriculture and Technology, Dhaka-1230, Bangladesh"
+4972aadcce369a8c0029e6dc2f288dfd0241e144,Multi-target Unsupervised Domain Adaptation without Exactly Shared Categories,"Multi-target Unsupervised Domain Adaptation
+without Exactly Shared Categories
+Huanhuan Yu, Menglei Hu and Songcan Chen"
+49e85869fa2cbb31e2fd761951d0cdfa741d95f3,Adaptive Manifold Learning,"Adaptive Manifold Learning
+Zhenyue Zhang, Jing Wang, and Hongyuan Zha"
+49a7949fabcdf01bbae1c2eb38946ee99f491857,A concatenating framework of shortcut convolutional neural networks,"A CONCATENATING FRAMEWORK OF SHORTCUT
+CONVOLUTIONAL NEURAL NETWORKS
+Yujian Li Ting Zhang, Zhaoying Liu, Haihe Hu"
+499343a2fd9421dca608d206e25e53be84489f44,Face Recognition with Name Using Local Weber‟s Law Descriptor,"Anil Kumar.C, et.al, International Journal of Technology and Engineering Science [IJTES]TM
+Volume 1[9], pp: 1371-1375, December 2013
+Face Recognition with Name Using Local Weber‟s
+Law Descriptor
+C.Anil kumar,2A.Rajani,3I.Suneetha
+M.Tech Student,2Assistant Professor,3Associate Professor
+Department of ECE, Annamacharya Institute of Technology and Sciences, Tirupati, India-517520
+on  FERET"
+498fd231d7983433dac37f3c97fb1eafcf065268,Linear Disentangled Representation Learning for Facial Actions,"LINEAR DISENTANGLED REPRESENTATION LEARNING FOR FACIAL ACTIONS
+Xiang Xiang1 and Trac D. Tran2
+Dept. of Computer Science
+Dept. of Electrical & Computer Engineering
+Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA
+Fig. 1. The separability of the neutral face yn and expression
+omponent ye. We ﬁnd yn is better for identity recognition
+than y and ye is better for expression recognition than y."
+49e1aa3ecda55465641b2c2acc6583b32f3f1fc6,Support Vector Machine for age classification,"International Journal of Emerging Technology and Advanced Engineering
+Website: www.ijetae.com (ISSN 2250-2459, Volume 2, Issue 5, May 2012)
+Support Vector Machine for age classification
+Sangeeta Agrawal1, Rohit Raja2, Sonu Agrawal3
+Assistant Professor, CSE, RSR RCET, Kohka Bhilai
+,3 Sr. Assistant Professor, CSE, SSCET, Junwani Bhilai"
+49df381ea2a1e7f4059346311f1f9f45dd997164,Client-Specific Anomaly Detection for Face Presentation Attack Detection,"On the Use of Client-Speciﬁc Information for Face
+Presentation Attack Detection Based on Anomaly
+Detection
+Shervin Rahimzadeh Arashloo and Josef Kittler,"
+496074fcbeefd88664b7bd945012ca22615d812e,Driver Distraction Using Visual-Based Sensors and Algorithms,"Review
+Driver Distraction Using Visual-Based Sensors
+nd Algorithms
+Alberto Fernández 1,*, Rubén Usamentiaga 2, Juan Luis Carús 1 and Rubén Casado 2
+Grupo TSK, Technological Scientiﬁc Park of Gijón, 33203 Gijón, Asturias, Spain;
+Department of Computer Science and Engineering, University of Oviedo, Campus de Viesques, 33204 Gijón,
+Asturias, Spain; (R.U.); (R.C.)
+* Corrospondence: Tel.: +34-984-29-12-12; Fax: +34-984-39-06-12
+Academic Editor: Gonzalo Pajares Martinsanz
+Received: 14 July 2016; Accepted: 24 October 2016; Published: 28 October 2016"
+40205181ed1406a6f101c5e38c5b4b9b583d06bc,Using Context to Recognize People in Consumer Images,"Using Context to Recognize People in Consumer Images
+Andrew C. Gallagher and Tsuhan Chen"
+40dab43abef32deaf875c2652133ea1e2c089223,Facial Communicative Signals: valence recognition in task-oriented human-robot Interaction,"Noname manuscript No.
+(will be inserted by the editor)
+Facial Communicative Signals
+Valence Recognition in Task-Oriented Human-Robot Interaction
+Christian Lang · Sven Wachsmuth · Marc Hanheide · Heiko Wersing
+Received: date / Accepted: date"
+40b0fced8bc45f548ca7f79922e62478d2043220,Do Convnets Learn Correspondence?,"Do Convnets Learn Correspondence?
+Trevor Darrell
+Jonathan Long
+{jonlong, nzhang,
+University of California – Berkeley
+Ning Zhang"
+405b43f4a52f70336ac1db36d5fa654600e9e643,What can we learn about CNNs from a large scale controlled object dataset?,"What can we learn about CNNs from a large scale controlled object dataset?
+Ali Borji
+Saeed Izadi
+Laurent Itti"
+40b86ce698be51e36884edcc8937998979cd02ec,Finding Faces in News Photos Using Both Face and Name Information,"Yüz ve İsim İlişkisi kullanarak Haberlerdeki Kişilerin Bulunması
+Finding Faces in News Photos Using Both Face and Name Information
+Derya Ozkan, Pınar Duygulu
+Bilgisayar Mühendisliği Bölümü, Bilkent Üniversitesi, 06800, Ankara
+Özetçe
+Bu  çalışmada,  haber  fotoğraflarından  oluşan  geniş  veri
+kümelerinde  kişilerin  sorgulanmasını  sağlayan  bir  yöntem
+sunulmuştur.  Yöntem  isim  ve  yüzlerin  ilişkilendirilmesine
+dayanmaktadır.  Haber  başlığında  kişinin  ismi  geçiyor  ise
+fotoğrafta da o kişinin yüzünün bulunacağı  varsayımıyla, ilk
+olarak  sorgulanan  isim  ile  ilişkilendirilmiş,  fotoğraflardaki
+tüm yüzler seçilir. Bu yüzler arasında sorgu kişisine ait farklı
+koşul,  poz  ve  zamanlarda  çekilmiş  pek  çok  resmin  yanında,
+haberde ismi geçen başka kişilere ait yüzler ya da kullanılan
+yüz  bulma  yönteminin  hatasından  kaynaklanan  yüz  olmayan
+resimler de bulunabilir. Yine de, çoğu  zaman, sorgu kişisine
+it resimler daha çok olup, bu resimler birbirine diğerlerine
+olduğundan  daha  çok  benzeyeceklerdir.  Bu  nedenle,  yüzler
+rasındaki  benzerlikler  çizgesel  olarak  betimlendiğinde  ,
+irbirine en çok benzeyen yüzler bu çizgede en yoğun bileşen"
+402f6db00251a15d1d92507887b17e1c50feebca,3D Facial Action Units Recognition for Emotional Expression,"D Facial Action Units Recognition for Emotional
+Expression
+Norhaida Hussain1, Hamimah Ujir, Irwandi Hipiny and Jacey-Lynn Minoi2
+Department of Information Technology and Communication, Politeknik Kuching, Sarawak, Malaysia
+Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Kota Samarahan, Sarawak, Malaysia
+The  muscular  activities  caused  the  activation  of  certain  AUs  for  every  facial  expression  at  the  certain  duration  of  time
+throughout the facial expression. This paper presents the methods to recognise facial Action Unit (AU) using facial distance
+of the facial features which activates the muscles. The seven facial action units involved are AU1, AU4, AU6, AU12, AU15,
+AU17 and AU25 that characterises happy and sad expression. The recognition is performed on each AU according to rules
+defined based on the distance of each facial points. The facial distances chosen are extracted from twelve facial features.
+Then the facial distances are trained using Support Vector Machine (SVM) and Neural Network (NN). Classification result
+using SVM is presented with several different SVM kernels while result using NN is presented for each training, validation
+nd testing phase.
+Keywords: Facial action units recognition, 3D AU recognition, facial expression"
+40fb4e8932fb6a8fef0dddfdda57a3e142c3e823,A mixed generative-discriminative framework for pedestrian classification,"A Mixed Generative-Discriminative Framework for Pedestrian Classiﬁcation
+Markus Enzweiler1
+Dariu M. Gavrila2,3
+Image & Pattern Analysis Group, Dept. of Math. and Comp. Sc., Univ. of Heidelberg, Germany
+Environment Perception, Group Research, Daimler AG, Ulm, Germany
+Intelligent Systems Lab, Faculty of Science, Univ. of Amsterdam, The Netherlands"
+40dd2b9aace337467c6e1e269d0cb813442313d7,Localizing spatially and temporally objects and actions in videos. (Localiser spatio-temporallement des objets et des actions dans des vidéos),"This thesis has been submitted in fulfilment of the requirements for a postgraduate degree
+(e.g. PhD, MPhil, DClinPsychol) at the University of Edinburgh. Please note the following
+terms and conditions of use:
+This work is protected by copyright and other intellectual property rights, which are
+retained by the thesis author, unless otherwise stated.
+A copy can be downloaded for personal non-commercial research or study, without
+prior permission or charge.
+This thesis cannot be reproduced or quoted extensively from without first obtaining
+permission in writing from the author.
+The content must not be changed in any way or sold commercially in any format or
+medium without the formal permission of the author.
+When referring to this work, full bibliographic details including the author, title,
+warding institution and date of the thesis must be given."
+40a34d4eea5e32dfbcef420ffe2ce7c1ee0f23cd,Bridging Heterogeneous Domains With Parallel Transport For Vision and Multimedia Applications,"Bridging Heterogeneous Domains With Parallel Transport For Vision and
+Multimedia Applications
+Raghuraman Gopalan
+Dept. of Video and Multimedia Technologies Research
+AT&T Labs-Research
+San Francisco, CA 94108"
+40389b941a6901c190fb74e95dc170166fd7639d,Automatic Facial Expression Recognition,"Automatic Facial Expression Recognition
+Jacob Whitehill, Marian Stewart Bartlett, and Javier R. Movellan
+Emotient
+http://emotient.com
+February 12, 2014
+Imago animi vultus est, indices oculi. (Cicero)
+Introduction
+The face is innervated by two different brain systems that compete for control of its muscles:
+cortical brain system related to voluntary and controllable behavior, and a sub-cortical
+system responsible for involuntary expressions. The interplay between these two systems
+generates a wealth of information that humans constantly use to read the emotions, inten-
+tions, and interests [25] of others.
+Given the critical role that facial expressions play in our daily life, technologies that can
+interpret and respond to facial expressions automatically are likely to ﬁnd a wide range of
+pplications. For example, in pharmacology, the effect of new anti-depression drugs could
+e assessed more accurately based on daily records of the patients’ facial expressions than
+sking the patients to ﬁll out a questionnaire, as it is currently done [7]. Facial expression
+recognition may enable a new generation of teaching systems to adapt to the expression
+of their students in the way good teachers do [61]. Expression recognition could be used
+to assess the fatigue of drivers and air-pilots [58, 59]. Daily-life robots with automatic"
+40273657e6919455373455bd9a5355bb46a7d614,Anonymizing k Facial Attributes via Adversarial Perturbations,"Anonymizing k-Facial Attributes via Adversarial Perturbations
+Saheb Chhabra1, Richa Singh1, Mayank Vatsa1 and Gaurav Gupta2
+IIIT Delhi, New Delhi, India
+Ministry of Electronics and Information Technology, New Delhi, India
+{sahebc, rsingh,"
+40b10e330a5511a6a45f42c8b86da222504c717f,Implementing the Viola-Jones Face Detection Algorithm,"Implementing the Viola-Jones
+Face Detection Algorithm
+Ole Helvig Jensen
+Kongens Lyngby 2008
+IMM-M.Sc.-2008-93"
+40ca925befa1f7e039f0cd40d57dbef6007b4416,Sampling Matters in Deep Embedding Learning,"Sampling Matters in Deep Embedding Learning
+Chao-Yuan Wu∗
+UT Austin
+R. Manmatha
+A9/Amazon
+Alexander J. Smola
+Amazon
+Philipp Kr¨ahenb¨uhl
+UT Austin"
+4026dc62475d2ff2876557fc2b0445be898cd380,An Affective User Interface Based on Facial Expression Recognition and Eye-Gaze Tracking,"An Affective User Interface Based on Facial Expression
+Recognition and Eye-Gaze Tracking
+Soo-Mi Choi and Yong-Guk Kim
+School of Computer Engineering, Sejong University, Seoul, Korea"
+40f127fa4459a69a9a21884ee93d286e99b54c5f,Optimizing Apparent Display Resolution Enhancement for Arbitrary Videos,"Optimizing Apparent Display Resolution
+Enhancement for Arbitrary Videos
+Michael Stengel*, Member, IEEE, Martin Eisemann, Stephan Wenger,
+Benjamin Hell, Marcus Magnor, Member, IEEE"
+401e6b9ada571603b67377b336786801f5b54eee,Active Image Clustering: Seeking Constraints from Humans to Complement Algorithms,"Active Image Clustering: Seeking Constraints from
+Humans to Complement Algorithms
+November 22, 2011"
+2e8e6b835e5a8f55f3b0bdd7a1ff765a0b7e1b87,Pointly-Supervised Action Localization,"International Journal of Computer Vision manuscript No.
+(will be inserted by the editor)
+Pointly-Supervised Action Localization
+Pascal Mettes · Cees G. M. Snoek
+Received: date / Accepted: date"
+2eb37a3f362cffdcf5882a94a20a1212dfed25d9,Local Feature Based Face Recognition,"Local Feature Based Face Recognition
+Sanjay A. Pardeshi and Sanjay N. Talbar
+R.I.T., Rajaramnagar and S.G.G.S. COE &T, Nanded
+India
+. Introduction
+A  reliable  automatic  face  recognition  (AFR)  system  is  a  need  of  time  because  in  today's
+networked  world,  maintaining  the  security  of  private  information  or  physical  property  is
+ecoming increasingly important and difficult as well. Most of the time criminals have been
+taking  the  advantage  of  fundamental  flaws  in  the  conventional  access  control  systems  i.e.
+the systems operating on credit card, ATM etc. do not grant access by ""who we are"", but by
+""what  we  have”.  The  biometric  based  access  control systems  have  a  potential  to  overcome
+most  of  the  deficiencies  of  conventional  access  control  systems  and  has  been  gaining  the
+importance  in  recent  years.  These  systems  can  be  designed  with  biometric  traits  such  as
+fingerprint,  face,  iris,  signature,  hand  geometry  etc.  But  comparison  of  different  biometric
+traits shows that face is very attractive biometric because of its non-intrusiveness and social
+cceptability.  It  provides  automated  methods  of  verifying  or  recognizing  the  identity  of  a
+living person based on its facial characteristics.
+In last decade, major advances occurred in face recognition, with many systems capable of
+chieving  recognition  rates  greater  than  90%.  However  real-world  scenarios  remain  a
+hallenge, because face acquisition process can undergo to a wide range of variations. Hence"
+2e5cfa97f3ecc10ae8f54c1862433285281e6a7c,Generative Adversarial Networks for Improving Face Classification,"Generative Adversarial Networks for Improving Face Classification  JONAS NATTEN SUPERVISOR Morten Goodwin, PhD University of Agder, 2017 Faculty of Engineering and Science Department of ICT"
+2e091b311ac48c18aaedbb5117e94213f1dbb529,Collaborative Facial Landmark Localization for Transferring Annotations Across Datasets,"Collaborative Facial Landmark Localization
+for Transferring Annotations Across Datasets
+Brandon M. Smith and Li Zhang
+University of Wisconsin – Madison
+http://www.cs.wisc.edu/~lizhang/projects/collab-face-landmarks/"
+2e1415a814ae9abace5550e4893e13bd988c7ba1,Dictionary Based Face Recognition in Video Using Fuzzy Clustering and Fusion,"International Journal of Engineering Trends and Technology (IJETT) – Volume 21 Number 3 – March 2015
+Dictionary Based Face Recognition in Video Using
+Fuzzy Clustering and Fusion
+Neeraja K.C.#1, RameshMarivendan E.#2,
+#1IInd year M.E. Student, #2Assistant Professor
+#1#2ECE Department, Dhanalakshmi Srinivasan College of Engineering,
+Coimbatore,Tamilnadu,India.
+Anna University."
+2e68190ebda2db8fb690e378fa213319ca915cf8,Generating Videos with Scene Dynamics,"Generating Videos with Scene Dynamics
+Carl Vondrick
+Hamed Pirsiavash
+Antonio Torralba"
+2e0d56794379c436b2d1be63e71a215dd67eb2ca,Improving precision and recall of face recognition in SIPP with combination of modified mean search and LSH,"Improving precision and recall of face recognition in SIPP with combination of
+modiﬁed mean search and LSH
+Xihua.Li"
+2e475f1d496456831599ce86d8bbbdada8ee57ed,Groupsourcing: Team Competition Designs for Crowdsourcing,"Groupsourcing: Team Competition Designs for
+Crowdsourcing
+Markus Rokicki, Sergej Zerr, Stefan Siersdorfer
+L3S Research Center, Hannover, Germany"
+2ef51b57c4a3743ac33e47e0dc6a40b0afcdd522,Leveraging Billions of Faces to Overcome Performance Barriers in Unconstrained Face Recognition,"Leveraging Billions of Faces to Overcome
+Performance Barriers in Unconstrained Face
+Recognition
+Yaniv Taigman and Lior Wolf
+face.com
+{yaniv,"
+2ed4973984b254be5cba3129371506275fe8a8eb,Victoria Ovsyannikova THE EFFECTS OF MOOD ON EMOTION RECOGNITION AND ITS RELATIONSHIP WITH THE GLOBAL VS LOCAL INFORMATION PROCESSING,"Victoria Ovsyannikova
+THE EFFECTS OF MOOD ON
+EMOTION RECOGNITION AND
+ITS RELATIONSHIP WITH THE
+GLOBAL VS LOCAL
+INFORMATION PROCESSING
+STYLES
+BASIC RESEARCH PROGRAM
+WORKING PAPERS
+SERIES: PSYCHOLOGY
+WP BRP 60/PSY/2016
+This Working Paper is an output of a research project implemented at the National Research
+University Higher School of Economics (HSE). Any opinions or claims contained in this
+Working Paper do not necessarily reflect the views of HSE"
+2e9c780ee8145f29bd1a000585dd99b14d1f5894,Simultaneous Adversarial Training - Learn from Others Mistakes,"Simultaneous Adversarial Training - Learn from
+Others’ Mistakes
+Zukang Liao
+Lite-On Singapore Pte. Ltd, 2Imperial College London"
+2ebc35d196cd975e1ccbc8e98694f20d7f52faf3,Towards Wide-angle Micro Vision Sensors,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.
+IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
+Towards Wide-angle Micro Vision Sensors
+Sanjeev J. Koppal*
+Ioannis Gkioulekas* Travis Young+ Hyunsung Park*
+Kenneth B. Crozier* Geoffrey L. Barrows+ Todd Zickler*"
+2ea78e128bec30fb1a623c55ad5d55bb99190bd2,Residual vs. Inception vs. Classical Networks for Low-Resolution Face Recognition,"Residual vs. Inception vs. Classical Networks for
+Low-Resolution Face Recognition
+Christian Herrmann1,2, Dieter Willersinn2, and J¨urgen Beyerer1,2
+Vision and Fusion Lab, Karlsruhe Institute of Technology KIT, Karlsruhe, Germany
+Fraunhofer IOSB, Karlsruhe, Germany
+{christian.herrmann,dieter.willersinn,"
+2e0f5e72ad893b049f971bc99b67ebf254e194f7,Apparel Classification with Style,"Apparel Classiﬁcation with Style
+Lukas Bossard1, Matthias Dantone1, Christian Leistner1,2,
+Christian Wengert1,3, Till Quack3, Luc Van Gool1,4
+ETH Z¨urich, Switzerland 2Microsoft, Austria 3Kooaba AG, Switzerland
+KU Leuven, Belgium"
+2ec7d6a04c8c72cc194d7eab7456f73dfa501c8c,A R Eview on T Exture B Ased E Motion R Ecognition from F Acial E Xpression,"International Journal of Scientific Research and Management Studies (IJSRMS)
+ISSN: 2349-3771
+Volume 3 Issue 4, pg: 164-169
+A REVIEW ON TEXTURE BASED EMOTION RECOGNITION
+FROM FACIAL EXPRESSION
+Rishabh Bhardwaj, 2Amit Kumar Chanchal, 3 Shubham Kashyap,
+3 Pankaj Pandey, 3Prashant Kumar
+U.G. Scholars, 2Assistant Professor,
+Dept. of E & C Engg., MIT Moradabad, Ram Ganga Vihar, Phase II, Moradabad, India."
+2e832d5657bf9e5678fd45b118fc74db07dac9da,"Recognition of Facial Expressions of Emotion: The Effects of Anxiety, Depression, and Fear of Negative Evaluation","Running head: RECOGNITION OF FACIAL EXPRESSIONS OF EMOTION
+Recognition of Facial Expressions of Emotion: The Effects of Anxiety, Depression, and Fear of Negative
+Evaluation
+Rachel Merchak
+Wittenberg University
+Rachel Merchak, Psychology Department, Wittenberg University.
+Author Note
+This research was conducted in collaboration with Dr. Stephanie Little, Psychology Department,
+Wittenberg University, and Dr. Michael Anes, Psychology Department, Wittenberg University.
+Correspondence concerning this article should be addressed to Rachel Merchak, 10063 Fox
+Chase Drive, Loveland, OH 45140.
+E‐mail:"
+2b4d092d70efc13790d0c737c916b89952d4d8c7,Robust Facial Expression Recognition using Local Haar Mean Binary Pattern,"JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 32, XXXX-XXXX (2016)
+Robust Facial Expression Recognition using Local Haar
+Mean Binary Pattern
+MAHESH GOYANI1, NARENDRA PATEL2
+,2 Department of Computer Engineering
+Charotar University of Science and Technology, Changa, India
+Gujarat Technological University, V.V.Nagar, India
+E-mail:
+In this paper, we propose a hybrid statistical feature extractor, Local Haar Mean Bina-
+ry Pattern (LHMBP). It extracts level-1 haar approximation coefficients and computes Local
+Mean  Binary  Pattern  (LMBP)  of  it.  LMBP  code  of  pixel  is  obtained  by  weighting  the
+thresholded neighbor value of 3  3 patch on its mean. LHMBP produces highly discrimina-
+tive code compared to other state of the art methods. To localize appearance features, ap-
+proximation subband is divided into M  N regions. LHMBP feature descriptor is derived
+y  concatenating  LMBP  distribution  of  each  region.  We  also  propose  a  novel  template
+matching strategy called Histogram Normalized Absolute Difference (HNAD) for histogram
+ased  feature  comparison.  Experiments  prove  the  superiority  of  HNAD  over  well-known
+template  matching  techniques  such  as  L2  norm  and  Chi-Square.  We  also  investigated
+LHMBP for expression recognition in low resolution. The performance of the proposed ap-
+proach is tested on well-known CK, JAFFE, and SFEW facial expression datasets in diverse"
+2b0ff4b82bac85c4f980c40b3dc4fde05d3cc23f,An Effective Approach for Facial Expression Recognition with Local Binary Pattern and Support Vector Machine,"An Effective Approach for Facial Expression Recognition with Local Binary
+Pattern and Support Vector Machine
+Cao Thi Nhan, 2Ton That Hoa An, 3Hyung Il Choi
+*1School of Media, Soongsil University,
+School of Media, Soongsil University,
+School of Media, Soongsil University,"
+2bab44d3a4c5ca79fb8f87abfef4456d326a0445,Player identification in soccer videos,"Player Identiﬁcation in Soccer Videos
+Marco Bertini, Alberto Del Bimbo, and Walter Nunziati
+Dipartimento di Sistemi e Informatica, University of Florence
+Via S. Marta, 3 - 50139 Florence, Italy"
+2b1327a51412646fcf96aa16329f6f74b42aba89,Improving performance of recurrent neural network with relu nonlinearity,"Under review as a conference paper at ICLR 2016
+IMPROVING PERFORMANCE OF RECURRENT NEURAL
+NETWORK WITH RELU NONLINEARITY
+Sachin S. Talathi & Aniket Vartak
+Qualcomm Research
+San Diego, CA 92121, USA"
+2b5cb5466eecb131f06a8100dcaf0c7a0e30d391,A comparative study of active appearance model annotation schemes for the face,"A Comparative Study of Active Appearance Model
+Annotation Schemes for the Face
+Amrutha Sethuram
+Face Aging Group
+UNCW, USA
+Karl Ricanek
+Face Aging Group
+UNCW, USA
+Eric Patterson
+Face Aging Group
+UNCW, USA"
+2b632f090c09435d089ff76220fd31fd314838ae,Early Adaptation of Deep Priors in Age Prediction from Face Images,"Early Adaptation of Deep Priors in Age Prediction from Face Images
+Mahdi Hajibabaei
+Computer Vision Lab
+D-ITET, ETH Zurich
+Anna Volokitin
+Computer Vision Lab
+D-ITET, ETH Zurich
+Radu Timofte
+CVL, D-ITET, ETH Zurich
+Merantix GmbH"
+2b507f659b341ed0f23106446de8e4322f4a3f7e,Deep Identity-aware Transfer of Facial Attributes,"Deep Identity-aware Transfer of Facial Attributes
+Mu Li1, Wangmeng Zuo2, David Zhang1
+The Hong Kong Polytechnic University 2Harbin Institute of Technology"
+2b8dfbd7cae8f412c6c943ab48c795514d53c4a7,Polynomial based texture representation for facial expression recognition,"014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP)
+978-1-4799-2893-4/14/$31.00 ©2014 IEEE
+e-mail:
+e-mail:
+RECOGNITION
+. INTRODUCTION
+(d1,d2)∈[0;d]2
+d1+d2≤d"
+2bae810500388dd595f4ebe992c36e1443b048d2,Analysis of Facial Expression Recognition by Event-related Potentials,"International Journal of Bioelectromagnetism
+Vol. 18, No. 1, pp. 13 - 18, 2016
+www.ijbem.org
+Analysis of Facial Expression Recognition
+y Event-related Potentials
+Taichi Hayasaka and Ayumi Miyachi
+Department of Information and Computer Engineering,
+National Institute of Technology, Toyota College, Japan
+Correspondence: Taichi Hayasaka, Department of Information and Computer Engineering, National Institute of Technology,
+Toyota College, 2-1 Eisei, Toyota-shi, Aichi, 471-8525 Japan,
+E-mail: phone +81 565 36 5861, fax +81 565 36 5926"
+2bbbbe1873ad2800954058c749a00f30fe61ab17,Face Verification across Ages Using Self Organizing Map,"ISSN(Online): 2320-9801
+ISSN (Print):  2320-9798
+International Journal of Innovative Research in Computer and Communication Engineering
+(An ISO 3297: 2007 Certified Organization)
+Vol.2, Special Issue 1, March 2014
+Proceedings of International Conference On Global Innovations In Computing Technology (ICGICT’14)
+Organized by
+Department of CSE, JayShriram Group of Institutions, Tirupur, Tamilnadu, India on 6th & 7th March 2014
+Face Verification across Ages Using Self
+Organizing Map
+B.Mahalakshmi1, K.Duraiswamy2, P.Gnanasuganya3, P.Aruldhevi4, R.Sundarapandiyan5
+Associate Professor, Department of CSE, K.S.Rangasamy College of Technology, Namakkal, TamilNadu, India1
+Dean, K.S.Rangasamy College of Technology, Namakkal, TamilNadu, India2
+B.E, Department of CSE, K.S.Rangasamy College of Technology, Namakkal, TamilNadu, India3, 4, 5"
+477236563c6a6c6db922045453b74d3f9535bfa1,Attribute Based Image Search Re-Ranking Snehal,"International Journal of Science and Research (IJSR)
+ISSN (Online): 2319-7064
+Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611
+Attribute Based Image Search Re-Ranking
+Snehal S Patil1, Ajay Dani2
+Master of Computer Engg, Savitribai Phule Pune University, G. H. Raisoni Collage of Engg and Technology, Wagholi, Pune
+2Professor, Computer and Science Dept, Savitribai Phule Pune University, G. H .Raisoni Collage of Engg and Technology, Wagholi, Pune
+integrating
+images  by"
+4793f11fbca4a7dba898b9fff68f70d868e2497c,Kinship Verification through Transfer Learning,"Kinship Veriﬁcation through Transfer Learning
+Siyu Xia∗
+CSE, SUNY at Buffalo, USA
+nd Southeast University, China
+Ming Shao∗
+Yun Fu
+SUNY at Buffalo, USA
+SUNY at Buffalo, USA"
+470dbd3238b857f349ebf0efab0d2d6e9779073a,Unsupervised Simultaneous Orthogonal basis Clustering Feature Selection,"Unsupervised Simultaneous Orthogonal Basis Clustering Feature Selection
+Dongyoon Han and Junmo Kim
+School of Electrical Engineering, KAIST, South Korea
+In this paper, we propose a novel unsupervised feature selection method: Si-
+multaneous Orthogonal basis Clustering Feature Selection (SOCFS). To per-
+form feature selection on unlabeled data effectively, a regularized regression-
+ased formulation with a new type of target matrix is designed. The target
+matrix captures latent cluster centers of the projected data points by per-
+forming the orthogonal basis clustering, and then guides the projection ma-
+trix to select discriminative features. Unlike the recent unsupervised feature
+selection methods, SOCFS does not explicitly use the pre-computed local
+structure information for data points represented as additional terms of their
+objective functions, but directly computes latent cluster information by the
+target matrix conducting orthogonal basis clustering in a single uniﬁed term
+of the proposed objective function.
+Since the target matrix is put in a single uniﬁed term for regression of
+the proposed objective function, feature selection and clustering are simul-
+taneously performed. In this way, the projection matrix for feature selection
+is more properly computed by the estimated latent cluster centers of the
+projected data points. To the best of our knowledge, this is the ﬁrst valid"
+47541d04ec24662c0be438531527323d983e958e,British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Control Number: 2008xxxxxx,Affective Information Processing
+474b461cd12c6d1a2fbd67184362631681defa9e,Multi-resolution fusion of DTCWT and DCT for shift invariant face recognition,"014 IEEE International
+Conference on Systems, Man
+nd Cybernetics
+(SMC 2014)
+San Diego, California, USA
+5-8 October 2014
+Pages 1-789
+IEEE Catalog Number:
+ISBN:
+CFP14SMC-POD
+978-1-4799-3841-4"
+47d4838087a7ac2b995f3c5eba02ecdd2c28ba14,Automatic Recognition of Deceptive Facial Expressions of Emotion,"JOURNAL OF IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, VOL. XX, NO. X, XXX 2017
+Automatic Recognition of Facial Displays of
+Unfelt Emotions
+Kaustubh Kulkarni*, Ciprian Adrian Corneanu*, Ikechukwu Ofodile*, Student Member, IEEE, Sergio
+Escalera, Xavier Bar´o, Sylwia Hyniewska, Member, IEEE, J¨uri Allik,
+nd Gholamreza Anbarjafari, Senior Member, IEEE"
+47a2727bd60e43f3253247b6d6f63faf2b67c54b,Semi-supervised Vocabulary-Informed Learning,"Semi-supervised Vocabulary-informed Learning
+Yanwei Fu and Leonid Sigal
+Disney Research"
+47d3b923730746bfaabaab29a35634c5f72c3f04,Real-Time Facial Expression Recognition App Development on Smart Phones,"Humaid Alshamsi.et.al. Int. Journal of Engineering Research and Application              www.ijera.com
+ISSN : 2248-9622, Vol. 7, Issue 7, ( Part -3) July 2017, pp.30-38
+RESEARCH ARTICLE
+OPEN ACCESS
+Real-Time Facial Expression Recognition App Development on
+Smart Phones
+Humaid Alshamsi, Veton Kupuska
+Electrical And Computer Engineering Department, Florida Institute Of Technology, Melbourne Fl,"
+47e3029a3d4cf0a9b0e96252c3dc1f646e750b14,Facial expression recognition in still pictures and videos using active appearance models: a comparison approach,"International Conference on Computer Systems and Technologies - CompSysTech’07
+Facial Expression Recognition in still pictures and videos using Active
+Appearance Models. A comparison approach.
+Drago(cid:1) Datcu
+Léon Rothkrantz"
+475e16577be1bfc0dd1f74f67bb651abd6d63524,DAiSEE: Towards User Engagement Recognition in the Wild,"DAiSEE: Towards User Engagement Recognition in the Wild
+Abhay Gupta
+Microsoft
+Vineeth N Balasubramanian
+Indian Institution of Technology Hyderabad"
+471befc1b5167fcfbf5280aa7f908eff0489c72b,Class-Specific Kernel-Discriminant Analysis for Face Verification,"Class-Speciﬁc Kernel-Discriminant
+Analysis for Face Veriﬁcation
+Georgios Goudelis, Stefanos Zafeiriou, Anastasios Tefas, Member, IEEE, and Ioannis Pitas, Fellow, IEEE
+lass problems ("
+47e8db3d9adb79a87c8c02b88f432f911eb45dc5,MAGMA: Multilevel Accelerated Gradient Mirror Descent Algorithm for Large-Scale Convex Composite Minimization,"MAGMA: Multi-level accelerated gradient mirror descent algorithm for
+large-scale convex composite minimization
+Vahan Hovhannisyan
+Panos Parpas
+Stefanos Zafeiriou
+July 15, 2016"
+47bf7a8779c68009ea56a7c20e455ccdf0e3a8fa,Automatic Face Recognition System using Pattern Recognition Techniques: A Survey,"International Journal of Computer Applications (0975 – 8887)
+Volume 83 – No 5, December 2013
+Automatic Face Recognition System using Pattern
+Recognition Techniques: A Survey
+Ningthoujam Sunita Devi                                                                              Prof.K.Hemachandran
+Department of Computer Science                                                                Department of Computer Science
+Assam University, Silchar-788011                                                               Assam University, Silchar-788011"
+47b508abdaa5661fe14c13e8eb21935b8940126b,An Efficient Method for Feature Extraction of Face Recognition Using PCA,"Volume 4, Issue 12, December 2014                                  ISSN: 2277 128X
+International Journal of Advanced Research in
+Computer Science and Software Engineering
+Research Paper
+Available online at: www.ijarcsse.com
+An Efficient Method for Feature Extraction of Face
+Recognition Using PCA
+Tara Prasad Singh
+(M.Tech. Student)
+Computer Science & Engineering
+Iftm University,Moradabad-244001 U.P."
+782188821963304fb78791e01665590f0cd869e8,Automatic Spatially-Aware Fashion Concept Discovery,"sleevelengthincreasing dress length+ mini =(b) Structured product browsing(c) Attribute-feedback product retrieval(a) Concept discoveryminimidimaxisleevelessshort-sleevelong-sleeveblueblackredyellowFigure1.(a)Weproposeaconceptdiscoveryapproachtoauto-maticallyclusterspatially-awareattributesintomeaningfulcon-cepts.Thediscoveredspatially-awareconceptsarefurtherutilizedfor(b)structuredproductbrowsing(visualizingimagesaccordingtoselectedconcepts)and(c)attribute-feedbackproductretrieval(reﬁningsearchresultsbyprovidingadesiredattribute).variousfeedback,includingtherelevanceofdisplayedim-ages[20,4],ortuningparameterslikecolorandtexture,andthenresultsareupdatedcorrespondingly.However,rel-evancefeedbackislimitedduetoitsslowconvergencetomeetthecustomerrequirements.Inadditiontocolorandtexture,customersoftenwishtoexploithigher-levelfea-tures,suchasneckline,sleevelength,dresslength,etc.Semanticattributes[13],whichhavebeenappliedef-fectivelytoobjectcategorization[15,27]andﬁne-grainedrecognition[12]couldpotentiallyaddresssuchchallenges.Theyaremid-levelrepresentationsthatdescribesemanticproperties.Recently,researchershaveannotatedclotheswithsemanticattributes[9,2,8,16,11](e.g.,material,pat-tern)asintermediaterepresentationsorsupervisorysignalstobridgethesemanticgap.However,annotatingsemanticattributesiscostly.Further,attributesconditionedonob-jectpartshaveachievedgoodperformanceinﬁne-grainedrecognition[3,33],conﬁrmingthatspatialinformationiscriticalforattributes.Thisalsoholdsforclothingimages.Forexample,thenecklineattributeusuallycorrespondstothetoppartinimageswhilethesleeveattributeordinarily1"
+78f08cc9f845dc112f892a67e279a8366663e26d,Semi-Autonomous Data Enrichment and Optimisation for Intelligent Speech Analysis,"TECHNISCHE UNIVERSIT ¨AT M ¨UNCHEN
+Lehrstuhl f¨ur Mensch-Maschine-Kommunikation
+Semi-Autonomous Data Enrichment and
+Optimisation for Intelligent Speech Analysis
+Zixing Zhang
+Vollst¨andiger Abdruck der von der Fakult¨at f¨ur Elektrotechnik und Informationstechnik
+der Technischen Universit¨at M¨unchen zur Erlangung des akademischen Grades eines
+Doktor-Ingenieurs (Dr.-Ing.)
+genehmigten Dissertation.
+Vorsitzender:
+Univ.-Prof. Dr.-Ing. habil. Dr. h.c. Alexander W. Koch
+Pr¨ufer der Dissertation:
+Univ.-Prof. Dr.-Ing. habil. Bj¨orn W. Schuller,
+Universit¨at Passau
+. Univ.-Prof. Gordon Cheng, Ph.D.
+Die Dissertation wurde am 30.09.2014 bei der Technischen Universit¨at M¨unchen einge-
+reicht und durch die Fakult¨at f¨ur Elektrotechnik und Informationstechnik am 07.04.2015
+ngenommen."
+783f3fccde99931bb900dce91357a6268afecc52,Adapted Active Appearance Models,"Hindawi Publishing Corporation
+EURASIP Journal on Image and Video Processing
+Volume 2009, Article ID 945717, 14 pages
+doi:10.1155/2009/945717
+Research Article
+Adapted Active Appearance Models
+Renaud S´eguier,1 Sylvain Le Gallou,2 Gaspard Breton,2 and Christophe Garcia2
+SUP ´ELEC/IETR, Avenue de la Boulaie, 35511 Cesson-S´evign´e, France
+Orange Labs—TECH/IRIS, 4 rue du clos courtel, 35 512 Cesson S´evign´e, France
+Correspondence should be addressed to Renaud S´eguier,
+Received 5 January 2009; Revised 2 September 2009; Accepted 20 October 2009
+Recommended by Kenneth M. Lam
+Active Appearance Models (AAMs) are able to align ef‌f‌iciently known faces under duress, when face pose and illumination are
+ontrolled. We propose Adapted Active Appearance Models to align unknown faces in unknown poses and illuminations. Our
+proposal is based on the one hand on a speciﬁc transformation of the active model texture in an oriented map, which changes the
+AAM normalization process; on the other hand on the research made in a set of different precomputed models related to the most
+dapted AAM for an unknown face. Tests on public and private databases show the interest of our approach. It becomes possible
+to align unknown faces in real-time situations, in which light and pose are not controlled.
+Copyright © 2009 Renaud S´eguier et al. This is an open access article distributed under the Creative Commons Attribution
+License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly"
+78f438ed17f08bfe71dfb205ac447ce0561250c6,Bridging the Semantic Gap : Image and video Understanding by Exploiting Attributes,
+781c2553c4ed2a3147bbf78ad57ef9d0aeb6c7ed,Tubelets: Unsupervised Action Proposals from Spatiotemporal Super-Voxels,"Int J Comput Vis
+DOI 10.1007/s11263-017-1023-9
+Tubelets: Unsupervised Action Proposals from Spatiotemporal
+Super-Voxels
+Mihir Jain1
+Cees G. M. Snoek1
+· Jan van Gemert2 · Hervé Jégou3 · Patrick Bouthemy3 ·
+Received: 25 June 2016 / Accepted: 18 May 2017
+© The Author(s) 2017. This article is an open access publication"
+78df7d3fdd5c32f037fb5cc2a7c104ac1743d74e,Temporal Pyramid Pooling-Based Convolutional Neural Network for Action Recognition,"TEMPORAL PYRAMID POOLING CNN FOR ACTION RECOGNITION
+Temporal Pyramid Pooling Based Convolutional
+Neural Network for Action Recognition
+Peng Wang, Yuanzhouhan Cao, Chunhua Shen, Lingqiao Liu, and Heng Tao Shen"
+78fdf2b98cf6380623b0e20b0005a452e736181e,Dense Wide-Baseline Stereo with Varying Illumination and its Application to Face Recognition,
+787c1bb6d1f2341c5909a0d6d7314bced96f4681,"Face Detection and Verification in Unconstrained Videos: Challenges, Detection, and Benchmark Evaluation","Face Detection and Veriﬁcation in Unconstrained
+Videos: Challenges, Detection, and Benchmark
+Evaluation
+Mahek Shah
+IIIT-D-MTech-CS-GEN-13-106
+July 16, 2015
+Indraprastha Institute of Information Technology, Delhi
+Thesis Advisors
+Dr. Mayank Vatsa
+Dr. Richa Singh
+Submitted in partial fulﬁllment of the requirements
+for the Degree of M.Tech. in Computer Science
+(cid:13) Shah, 2015
+Keywords: face recognition, face detection, face veriﬁcation"
+7808937b46acad36e43c30ae4e9f3fd57462853d,Describing people: A poselet-based approach to attribute classification,"Describing People: A Poselet-Based Approach to Attribute Classiﬁcation ∗
+Lubomir Bourdev1,2, Subhransu Maji1 and Jitendra Malik1
+EECS, U.C. Berkeley, Berkeley, CA 94720
+Adobe Systems, Inc., 345 Park Ave, San Jose, CA 95110"
+8b2c090d9007e147b8c660f9282f357336358061,Emotion Classification based on Expressions and Body Language using Convolutional Neural Networks,"Lake Forest College
+Lake Forest College Publications
+Senior Theses
+-23-2018
+Student Publications
+Emotion Classification based on Expressions and
+Body Language using Convolutional Neural
+Networks
+Aasimah S. Tanveer
+Lake Forest College,
+Follow this and additional works at: https://publications.lakeforest.edu/seniortheses
+Part of the Neuroscience and Neurobiology Commons
+Recommended Citation
+Tanveer, Aasimah S., ""Emotion Classification based on Expressions and Body Language using Convolutional Neural Networks""
+(2018). Senior Theses.
+This Thesis is brought to you for free and open access by the Student Publications at Lake Forest College Publications. It has been accepted for
+inclusion in Senior Theses by an authorized administrator of Lake Forest College Publications. For more information, please contact"
+8bed7ff2f75d956652320270eaf331e1f73efb35,Emotion Recognition in the Wild using Deep Neural Networks and Bayesian Classifiers,"Emotion Recognition in the Wild using
+Deep Neural Networks and Bayesian Classifiers
+Luca Surace
+Elena Ba(cid:138)ini S¨onmez
+University of Calabria - DeMACS
+Via Pietro Bucci
+Rende (CS), Italy
+Massimiliano Patacchiola
+Plymouth University - CRNS
+Portland Square PL4 8AA
+Plymouth, United Kingdom
+c.uk
+Istanbul Bilgi University - DCE
+Eski Silahtaraa Elektrik Santral Kazm
+Karabekir Cad. No: 2/13 34060 Eyp
+Istanbul, Turkey
+William Spataro
+University of Calabria - DeMACS
+Via Pietro Bucci
+Rende (CS), Italy"
+8b7191a2b8ab3ba97423b979da6ffc39cb53f46b,Search pruning in video surveillance systems: Efficiency-reliability tradeoff,"Search Pruning in Video Surveillance Systems: Efﬁciency-Reliability Tradeoff
+Antitza Dantcheva, Arun Singh, Petros Elia, Jean-Luc Dugelay
+EURECOM
+Sophia Antipolis, France
+{Antitza.Dantcheva, Arun.Singh, Petros.Elia,"
+8bf57dc0dd45ed969ad9690033d44af24fd18e05,Subject-Independent Emotion Recognition from Facial Expressions using a Gabor Feature RBF Neural Classifier Trained with Virtual Samples Generated by Concurrent Self-Organizing Maps,"Subject-Independent Emotion Recognition from Facial Expressions
+using a Gabor Feature RBF Neural Classifier Trained with Virtual
+Samples Generated by Concurrent Self-Organizing Maps
+VICTOR-EMIL NEAGOE, ADRIAN-DUMITRU CIOTEC
+Depart. Electronics, Telecommunications & Information Technology
+Polytechnic University of Bucharest
+Splaiul Independentei No. 313, Sector 6, Bucharest,
+ROMANIA"
+8b744786137cf6be766778344d9f13abf4ec0683,And Summarization by Sub-modular Inference,"978-1-4799-9988-0/16/$31.00 ©2016 IEEE
+ICASSP 2016"
+8bf647fed40bdc9e35560021636dfb892a46720e,Learning to hash-tag videos with Tag2Vec,"Learning to Hash-tag Videos with Tag2Vec
+Aditya Singh
+Saurabh Saini
+Rajvi Shah
+CVIT, KCIS, IIIT Hyderabad, India
+P J Narayanan
+http://cvit.iiit.ac.in/research/projects/tag2vec
+Figure 1. Learning a direct mapping from videos to hash-tags : sample frames from short video clips with user-given hash-tags
+(left); a sample frame from a query video and hash-tags suggested by our system for this query (right)."
+8bb21b1f8d6952d77cae95b4e0b8964c9e0201b0,Multimodal Interaction on a Social Robotic Platform,"Methoden
+t 11/2013
+(cid:2)(cid:2)(cid:2)
+Multimodale Interaktion
+uf einer sozialen Roboterplattform
+Multimodal Interaction on a Social Robotic Platform
+Jürgen Blume
+Korrespondenzautor:
+, Tobias Rehrl, Gerhard Rigoll, Technische Universität München
+Zusammenfassung Dieser Beitrag beschreibt die multimo-
+dalen Interaktionsmöglichkeiten mit der Forschungsroboter-
+plattform ELIAS. Zunächst wird ein Überblick über die Ro-
+oterplattform sowie die entwickelten Verarbeitungskompo-
+nenten gegeben, die Einteilung dieser Komponenten erfolgt
+nach dem Konzept von wahrnehmenden und agierenden Mo-
+dalitäten. Anschließend wird das Zusammenspiel der Kom-
+ponenten in einem multimodalen Spieleszenario näher be-
+trachtet. (cid:2)(cid:2)(cid:2) Summary
+This paper presents the mul-
+timodal"
+8b1db0894a23c4d6535b5adf28692f795559be90,How Reliable are Your Visual Attributes?,"Biometric and Surveillance Technology for Human and Activity Identification X, edited by Ioannis Kakadiaris,
+Walter J. Scheirer, Laurence G. Hassebrook, Proc. of SPIE Vol. 8712, 87120Q · © 2013 SPIE
+CCC code: 0277-786X/13/$18 · doi: 10.1117/12.2018974
+Proc. of SPIE Vol. 8712  87120Q-1
+From: http://proceedings.spiedigitallibrary.org/ on 06/07/2013 Terms of Use: http://spiedl.org/terms"
+134db6ca13f808a848321d3998e4fe4cdc52fbc2,Dynamics of facial expression: recognition of facial actions and their temporal segments from face profile image sequences,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 36, NO. 2, APRIL 2006
+Dynamics of Facial Expression: Recognition of
+Facial Actions and Their Temporal Segments
+From Face Proﬁle Image Sequences
+Maja Pantic, Member, IEEE, and Ioannis Patras, Member, IEEE"
+133dd0f23e52c4e7bf254e8849ac6f8b17fcd22d,Active Clustering with Model-Based Uncertainty Reduction,"This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
+Active Clustering with Model-Based
+Uncertainty Reduction
+Caiming Xiong, David M. Johnson, and Jason J. Corso Senior Member, IEEE"
+1369e9f174760ea592a94177dbcab9ed29be1649,Geometrical facial modeling for emotion recognition,"Geometrical Facial Modeling for Emotion Recognition
+Giampaolo L. Libralon and Roseli A. F. Romero"
+133900a0e7450979c9491951a5f1c2a403a180f0,Social Grouping for Multi-Target Tracking and Head Pose Estimation in Video,"JOURNAL OF LATEX CLASS FILES
+Social Grouping for Multi-target Tracking and
+Head Pose Estimation in Video
+Zhen Qin and Christian R. Shelton"
+13db9466d2ddf3c30b0fd66db8bfe6289e880802,Transfer Subspace Learning Model for Face Recognition at a Distance,"I.J. Image, Graphics and Signal Processing, 2017, 1, 27-32
+Published Online January 2017 in MECS (http://www.mecs-press.org/)
+DOI: 10.5815/ijigsp.2017.01.04
+Transfer Subspace Learning Model for Face
+Recognition at a Distance
+Alwin Anuse
+MIT, Pune ,India
+Email:
+Nilima Deshmukh
+AISSM’S IOT,India
+Email:
+Vibha Vyas
+College of Engineering Pune,India
+Email:
+learning  algorithms  work"
+13141284f1a7e1fe255f5c2b22c09e32f0a4d465,Object Tracking by Oversampling Local Features,"Object Tracking by
+Oversampling Local Features
+Federico Pernici and Alberto Del Bimbo"
+1394ca71fc52db972366602a6643dc3e65ee8726,EmoReact: a multimodal approach and dataset for recognizing emotional responses in children,"See	discussions,	stats,	and	author	profiles	for	this	publication	at:	https://www.researchgate.net/publication/308407783
+EmoReact:	A	Multimodal	Approach	and	Dataset
+for	Recognizing	Emotional	Responses	in	Children
+Conference	Paper	·	November	2016
+DOI:	10.1145/2993148.2993168
+CITATIONS
+READS
+authors,	including:
+Behnaz	Nojavanasghari
+University	of	Central	Florida
+PUBLICATIONS			20	CITATIONS
+Tadas	Baltrusaitis
+Carnegie	Mellon	University
+0	PUBLICATIONS			247	CITATIONS
+SEE	PROFILE
+SEE	PROFILE
+Charles	E.	Hughes
+University	of	Central	Florida
+85	PUBLICATIONS			1,248	CITATIONS
+SEE	PROFILE"
+133da0d8c7719a219537f4a11c915bf74c320da7,A Novel Method for 3D Image Segmentation with Fusion of Two Images using Color K-means Algorithm,"International Journal of Computer Applications (0975 – 8887)
+Volume 123 – No.4, August 2015
+A Novel Method for 3D Image Segmentation with Fusion
+of Two Images using Color K-means Algorithm
+Neelam Kushwah
+Dept. of CSE
+ITM Universe
+Gwalior
+Priusha Narwariya
+Dept. of CSE
+ITM Universe
+Gwalior"
+133f01aec1534604d184d56de866a4bd531dac87,Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics,"Effective Unconstrained Face Recognition by
+Combining Multiple Descriptors and Learned
+Background Statistics
+Lior Wolf, Member, IEEE, Tal Hassner, and Yaniv Taigman"
+13841d54c55bd74964d877b4b517fa94650d9b65,Generalised ambient reflection models for Lambertian and Phong surfaces,"Generalised Ambient Reflection Models for Lambertian and
+Phong Surfaces
+Author
+Zhang, Paul, Gao, Yongsheng
+Published
+Conference Title
+Proceedings of the 2009 IEEE International Conference on Image Processing (ICIP 2009)
+https://doi.org/10.1109/ICIP.2009.5413812
+Copyright Statement
+© 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/
+republish this material for advertising or promotional purposes or for creating new collective
+works for resale or redistribution to servers or lists, or to reuse any copyrighted component of
+this work in other works must be obtained from the IEEE.
+Downloaded from
+http://hdl.handle.net/10072/30001
+Griffith Research Online
+https://research-repository.griffith.edu.au"
+13f6ab2f245b4a871720b95045c41a4204626814,Cortex commands the performance of skilled movement,"RESEARCH ARTICLE
+Cortex commands the performance of
+skilled movement
+Jian-Zhong Guo, Austin R Graves, Wendy W Guo, Jihong Zheng, Allen Lee,
+Juan Rodrı´guez-Gonza´ lez, Nuo Li, John J Macklin, James W Phillips,
+Brett D Mensh, Kristin Branson, Adam W Hantman*
+Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United
+States"
+13afc4f8d08f766479577db2083f9632544c7ea6,Multiple kernel learning for emotion recognition in the wild,"Multiple Kernel Learning for
+Emotion Recognition in the Wild
+Karan Sikka, Karmen Dykstra, Suchitra Sathyanarayana,
+Gwen Littlewort and Marian S. Bartlett
+Machine Perception Laboratory
+EmotiW Challenge, ICMI, 2013"
+13188a88bbf83a18dd4964e3f89d0bc0a4d3a0bd,Image Normalization Robust using Histogram Equalization and Logarithm Transform Frequency DCT Coefficients for Illumination in Facial Images,"Dr. V. S. Manjula
+HOD, Department of Computer Science, St. Joseph College of Information Technology, Songea, Tanzania"
+13d9da779138af990d761ef84556e3e5c1e0eb94,Learning to Locate Informative Features for Visual Identification,"Int J Comput Vis (2008) 77: 3–24
+DOI 10.1007/s11263-007-0093-5
+Learning to Locate Informative Features for Visual Identiﬁcation
+Andras Ferencz · Erik G. Learned-Miller ·
+Jitendra Malik
+Received: 18 August 2005 / Accepted: 11 September 2007 / Published online: 9 November 2007
+© Springer Science+Business Media, LLC 2007"
+7f511a6a2b38a26f077a5aec4baf5dffc981d881,Low-Latency Human Action Recognition with Weighted Multi-Region Convolutional Neural Network,"LOW-LATENCY HUMAN ACTION RECOGNITION WITH WEIGHTED MULTI-REGION
+CONVOLUTIONAL NEURAL NETWORK
+Yunfeng Wang(cid:63), Wengang Zhou(cid:63), Qilin Zhang†, Xiaotian Zhu(cid:63), Houqiang Li(cid:63)
+(cid:63)University of Science and Technology of China, Hefei, Anhui, China
+HERE Technologies, Chicago, Illinois, USA"
+7ff42ee09c9b1a508080837a3dc2ea780a1a839b,Data Fusion for Real-time Multimodal Emotion Recognition through Webcams and Microphones in E-Learning,"Data Fusion for Real-time Multimodal Emotion Recognition through Webcams
+nd Microphones in E-Learning
+Kiavash Bahreini*, Rob Nadolski*, Wim Westera*
+*Welten Institute, Research Centre for Learning, Teaching and Technology, Faculty of
+Psychology and Educational Sciences, Open University of the Netherlands, Valkenburgerweg
+77, 6419 AT Heerlen, The Netherlands
+{kiavash.bahreini, rob.nadolski,"
+7f533bd8f32525e2934a66a5b57d9143d7a89ee1,Audio-Visual Identity Grounding for Enabling Cross Media Search,"Audio-Visual Identity Grounding for Enabling Cross Media Search
+Kevin Brady, MIT Lincoln Laboratory
+Paper ID 22"
+7f44f8a5fd48b2d70cc2f344b4d1e7095f4f1fe5,Sparse Output Coding for Scalable Visual Recognition,"Int J Comput Vis (2016) 119:60–75
+DOI 10.1007/s11263-015-0839-4
+Sparse Output Coding for Scalable Visual Recognition
+Bin Zhao1 · Eric P. Xing1
+Received: 15 May 2013 / Accepted: 16 June 2015 / Published online: 26 June 2015
+© Springer Science+Business Media New York 2015"
+7f4bc8883c3b9872408cc391bcd294017848d0cf,The Multimodal Focused Attribute Model : A Nonparametric Bayesian Approach to Simultaneous Object Classification and Attribute Discovery,"Computer
+Sciences
+Department
+The Multimodal Focused Attribute Model:  A Nonparametric
+Bayesian Approach to Simultaneous Object Classification and
+Attribute Discovery
+Jake Rosin
+Charles R. Dyer
+Xiaojin Zhu
+Technical Report #1697
+January 2012"
+7f6061c83dc36633911e4d726a497cdc1f31e58a,YouTube-8M: A Large-Scale Video Classification Benchmark,"YouTube-8M: A Large-Scale Video Classiﬁcation
+Benchmark
+Sami Abu-El-Haija
+George Toderici
+Nisarg Kothari
+Joonseok Lee
+Paul Natsev
+Balakrishnan Varadarajan
+Sudheendra Vijayanarasimhan
+Google Research"
+7f36dd9ead29649ed389306790faf3b390dc0aa2,Movement Differences between Deliberate and Spontaneous Facial Expressions: Zygomaticus Major Action in Smiling.,"MOVEMENT DIFFERENCES BETWEEN DELIBERATE
+AND SPONTANEOUS FACIAL EXPRESSIONS:
+ZYGOMATICUS MAJOR ACTION IN SMILING
+Karen L. Schmidt, Zara Ambadar, Jeffrey F. Cohn, and L. Ian Reed"
+7f6cd03e3b7b63fca7170e317b3bb072ec9889e0,A Face Recognition Signature Combining Patch-based Features with Soft Facial Attributes,"A Face Recognition Signature Combining Patch-based
+Features with Soft Facial Attributes
+L. Zhang, P. Dou, I.A. Kakadiaris
+Computational Biomedicine Lab, 4849 Calhoun Rd, Rm 373, Houston, TX 77204"
+7f97a36a5a634c30de5a8e8b2d1c812ca9f971ae,Incremental Classifier Learning with Generative Adversarial Networks,"Incremental Classiﬁer Learning with Generative Adversarial Networks
+Yue Wu1 Yinpeng Chen2 Lijuan Wang2 Yuancheng Ye3
+Zicheng Liu2 Yandong Guo2 Zhengyou Zhang2 Yun Fu1
+Northeastern University 2Microsoft Research 3City University of New York"
+7f268f29d2c8f58cea4946536f5e2325777fa8fa,Facial Emotion Recognition in Curvelet Domain,"Facial Emotion Recognition in Curvelet Domain
+Gyanendra K Verma and Bhupesh Kumar Singh
+Indian Institute of Informaiton Technology, Allahabad, India
+Allahabad, India - 211012"
+7f3a73babe733520112c0199ff8d26ddfc7038a0,Robust Face Identification with Small Sample Sizes using Bag of Words and Histogram of Oriented Gradients,
+7af38f6dcfbe1cd89f2307776bcaa09c54c30a8b,Learning in Computer Vision and Beyond: Development,"eaig i C	e Vii ad Beyd:
+Deve
+h . Weg
+Deae f C	e Sciece
+ichiga Sae Uiveiy
+Ea aig  48824
+Abac
+Thi chae id	ce wha i ca
+aic	
+ve
+y h	a cgiive deve
+ih i deeied befe he \bih"" f he ye. Afe he \bih"" i eab
+ 
+ach i  ea
+deve
+way aia
+	 ea whi
+de deve
+7a81967598c2c0b3b3771c1af943efb1defd4482,Do We Need More Training Data?,"Do We Need More Training Data?
+Xiangxin Zhu · Carl Vondrick · Charless C. Fowlkes · Deva Ramanan"
+7ae0212d6bf8a067b468f2a78054c64ea6a577ce,Human Face Processing Techniques With Application To Large Scale Video Indexing,"Human Face Processing Techniques
+With Application To
+Large Scale Video Indexing
+LE DINH DUY
+DOCTOR OF
+PHILOSOPHY
+Department of Informatics,
+School of Multidisciplinary Sciences,
+The Graduate University for Advanced Studies (SOKENDAI)
+006 (School Ｙear)
+September 2006"
+7a0fb972e524cb9115cae655e24f2ae0cfe448e0,Facial Expression Classification Using RBF AND Back-Propagation Neural Networks,"Facial Expression Classification Using RBF AND Back-Propagation Neural Networks
+R.Q.Feitosa1,2,
+M.M.B.Vellasco1,2,
+D.T.Oliveira1,
+D.V.Andrade1,
+S.A.R.S.Maffra1
+– Catholic University of Rio de Janeiro, Brazil
+Department of Electric Engineering
+– State University of Rio de Janeiro, Brazil
+Department of Computer Engineering
+e-mail: [raul, -rio.br, [diogo,"
+7ad77b6e727795a12fdacd1f328f4f904471233f,Supervised Local Descriptor Learning for Human Action Recognition,"Supervised Local Descriptor Learning
+for Human Action Recognition
+Xiantong Zhen, Feng Zheng, Ling Shao, Senior Member, IEEE, Xianbin Cao, Senior Member, IEEE, and Dan Xu"
+7a97de9460d679efa5a5b4c6f0b0a5ef68b56b3b,Constrained Joint Cascade Regression Framework for Simultaneous Facial Action Unit Recognition and Facial Landmark Detection,"nd Face shape relationship2)AU relationship3)Face shape patternUpdate facial landmark locationsUpdate AU activation probabilitiesAU activation probabilitiesCurrent landmark locationsFigure1.Constrainedjointcascaderegressionframeworkforsi-multaneousfacialactionunitrecognitionandlandmarkdetection.wouldenablethemachineunderstandingofhumanfacialbehavior,intent,emotionetc.Facialactionunitrecognitionandfaciallandmarkdetec-tionarerelatedtasks,buttheyareseldomlyexploitedjointlyintheliteratures.Forexample,thefaceshapedeﬁnedbythelandmarklocationsareconsideredaseffectivefeaturesforAUrecognition.But,thelandmarklocationinforma-tionisusuallyextractedbeforehandwithfaciallandmarkdetectionalgorithms.Ontheotherhand,theActionUnitinformationisrarelyutilizedintheliteraturetohelpfaciallandmarkdetection,eventhoughthefacialmusclemove-mentsandtheactivationofspeciﬁcfacialactionunitcancausetheappearanceandshapechangesofthefacewhichsigniﬁcantlyaffectfaciallandmarkdetection.Themutualinformationandintertwinedrelationshipamongfacialac-tionunitrecognitionandfaciallandmarkdetectionshouldbeutilizedtoboosttheperformancesofbothtasks.Cascaderegressionframeworkhasbeenshowntobeaneffectivemethodforfacealignmentrecently[19][13].Itstartsfromaninitialfaceshape(e.g.meanface)anditit-erativelyupdatesthefaciallandmarklocationsbasedonthelocalappearancefeaturesuntilconvergence.Severalregres-sionmodelshavebeenappliedtolearnthemappingfromthelocalappearancefeaturestothefaceshapeupdate.Toleveragethesuccessofthecascaderegressionframe-workandtoachievethegoalofjointfacialactionunit13400"
+7aa4c16a8e1481629f16167dea313fe9256abb42,Multi-task learning for face identification and attribute estimation,"978-1-5090-4117-6/17/$31.00 ©2017 IEEE
+ICASSP 2017"
+7ad7897740e701eae455457ea74ac10f8b307bed,Random Subspace Two-dimensional LDA for Face Recognition,"Random Subspace Two-dimensional LDA for Face Recognition*
+Garrett Bingham1"
+7a7b1352d97913ba7b5d9318d4c3d0d53d6fb697,Attend and Rectify: a Gated Attention Mechanism for Fine-Grained Recovery,"Attend and Rectify: a Gated Attention
+Mechanism for Fine-Grained Recovery
+Pau Rodr´ıguez†, Josep M. Gonfaus‡, Guillem Cucurull†,
+F. Xavier Roca†, Jordi Gonz`alez†
+Computer Vision Center and Universitat Aut`onoma de Barcelona (UAB),
+Campus UAB, 08193 Bellaterra, Catalonia Spain
+Visual Tagging Services, Parc de Recerca, Campus UAB"
+7aa062c6c90dba866273f5edd413075b90077b51,Minimizing Separability : A Comparative Analysis of Illumination Compensation Techniques in Face Recognition,"I.J. Information Technology and Computer Science, 2017, 5, 40-51
+Published Online May 2017 in MECS (http://www.mecs-press.org/)
+DOI: 10.5815/ijitcs.2017.05.06
+Minimizing Separability: A Comparative Analysis
+of Illumination Compensation Techniques in Face
+Recognition
+Chollette C. Olisah
+Department of Computer Science and IT, Baze University, Abuja, Nigeria
+E-mail:"
+1451e7b11e66c86104f9391b80d9fb422fb11c01,Image privacy protection with secure JPEG transmorphing,"IET Signal Processing
+Research Article
+Image privacy protection with secure JPEG
+transmorphing
+ISSN 1751-9675
+Received on 30th December 2016
+Revised 13th July 2017
+Accepted on 11th August 2017
+doi: 10.1049/iet-spr.2016.0756
+www.ietdl.org
+Lin Yuan1  , Touradj Ebrahimi1
+Multimedia Signal Processing Group, Electrical Engineering Department, EPFL, Station 11, Lausanne, Switzerland
+E-mail:"
+14761b89152aa1fc280a33ea4d77b723df4e3864,Zero-Shot Learning via Visual Abstraction,
+14fdec563788af3202ce71c021dd8b300ae33051,Social Influence Analysis based on Facial Emotions,"Social Influence Analysis based on Facial Emotions
+Pankaj Mishra, Raﬁk Hadﬁ, and Takayuki Ito
+Department of Computer Science and Engineering
+Nagoya Institute of Technology, Gokiso, Showa-ku, Nagoya, 466-8555 Japan
+{pankaj.mishra,"
+1459d4d16088379c3748322ab0835f50300d9a38,Cross-Domain Visual Matching via Generalized Similarity Measure and Feature Learning,"Cross-Domain Visual Matching via Generalized
+Similarity Measure and Feature Learning
+Liang Lin, Guangrun Wang, Wangmeng Zuo, Xiangchu Feng, and Lei Zhang"
+1450296fb936d666f2f11454cc8f0108e2306741,Learning to Discover Cross-Domain Relations with Generative Adversarial Networks,"Learning to Discover Cross-Domain Relations
+with Generative Adversarial Networks
+Taeksoo Kim 1 Moonsu Cha 1 Hyunsoo Kim 1 Jung Kwon Lee 1 Jiwon Kim 1"
+1442319de86d171ce9595b20866ec865003e66fc,Vision-Based Fall Detection with Convolutional Neural Networks,"Vision-Based Fall Detection with Convolutional
+Neural Networks
+Adri´an Nu˜nez-Marcos1, Gorka Azkune1, Ignacio Arganda-Carreras234
+DeustoTech - University of Deusto
+Avenida de las Universidades, 24 - 48007, Bilbao, Spain
+Dept. of Computer Science and Artiﬁcial Intelligence, Basque
+Country University, San Sebastian, Spain
+P. Manuel Lardizabal, 1 - 20018, San Sebastian, Spain
+Ikerbasque, Basque Foundation for Science, Bilbao, Spain
+Maria Diaz de Haro, 3 - 48013 Bilbao, Spain
+Donostia International Physics Center (DIPC), San Sebastian, Spain
+P. Manuel Lardizabal, 4 - 20018, San Sebastian, Spain"
+1462bc73834e070201acd6e3eaddd23ce3c1a114,Face Authentication /recognition System for Forensic Application Using Sketch Based on the Sift Features Approach,"International Journal of Science, Engineering and Technology Research (IJSETR), Volume 3, Issue 4, April 2014
+FACE AUTHENTICATION /RECOGNITION
+SYSTEM FOR FORENSIC APPLICATION
+USING SKETCH BASED ON THE SIFT
+FEATURES APPROACH
+Poonam A. Katre
+Department of Electronics Engineering KITS,
+RTMNU Nagpur University, India"
+140c95e53c619eac594d70f6369f518adfea12ef,Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A,"Pushing the Frontiers of Unconstrained Face Detection and Recognition: IARPA Janus Benchmark A
+Brendan F. Klare, Emma Taborsky , Austin Blanton , Jordan Cheney , Kristen Allen , Patrick Grother , Alan Mah , Anil K. Jain
+The development of accurate and scalable unconstrained face recogni-
+tion algorithms is a long term goal of the biometrics and computer vision
+ommunities. The term “unconstrained” implies a system can perform suc-
+essful identiﬁcations regardless of face image capture presentation (illumi-
+nation, sensor, compression) or subject conditions (facial pose, expression,
+occlusion). While automatic, as well as human, face identiﬁcation in certain
+scenarios may forever be elusive, such as when a face is heavily occluded or
+aptured at very low resolutions, there still remains a large gap between au-
+tomated systems and human performance on familiar faces. In order to close
+this gap, large annotated sets of imagery are needed that are representative
+of the end goals of unconstrained face recognition. This will help continue
+to push the frontiers of unconstrained face detection and recognition, which
+re the primary goals of the IARPA Janus program.
+The current state of the art in unconstrained face recognition is high
+ccuracy (roughly 99% true accept rate at a false accept rate of 1.0%) on
+faces that can be detected with a commodity face detectors, but unknown
+ccuracy on other faces. Despite the fact that face detection and recognition
+research generally has advanced somewhat independently, the frontal face"
+1467c4ab821c3b340abe05a1b13a19318ebbce98,Multitask and transfer learning for multi-aspect data,"Multitask and Transfer Learning for
+Multi-Aspect Data
+Bernardino Romera Paredes
+A dissertation submitted in partial fulﬁllment
+of the requirements for the degree of
+Doctor of Philosophy of University College London."
+142dcfc3c62b1f30a13f1f49c608be3e62033042,Adaptive region pooling for object detection,"Adaptive Region Pooling for Object Detection
+Yi-Hsuan Tsai
+UC Merced
+Onur C. Hamsici
+Qualcomm Research, San Diego
+Ming-Hsuan Yang
+UC Merced"
+14e428f2ff3dc5cf96e5742eedb156c1ea12ece1,Facial Expression Recognition Using Neural Network Trained with Zernike Moments,"Facial Expression Recognition Using Neural Network Trained with Zernike
+Moments
+Mohammed Saaidia
+Dept. Génie-Electrique
+Université M.C.M Souk-Ahras
+Souk-Ahras, Algeria"
+14a5feadd4209d21fa308e7a942967ea7c13b7b6,Content-based vehicle retrieval using 3D model and part information,"978-1-4673-0046-9/12/$26.00 ©2012 IEEE
+ICASSP 2012"
+14fee990a372bcc4cb6dc024ab7fc4ecf09dba2b,Modeling Spatio-Temporal Human Track Structure for Action Localization,"Modeling Spatio-Temporal Human Track Structure for Action
+Localization
+Guilhem Ch´eron · Anton Osokin · Ivan Laptev · Cordelia Schmid"
+14ee4948be56caeb30aa3b94968ce663e7496ce4,SmileNet: Registration-Free Smiling Face Detection,"SmileNet: Registration-Free Smiling Face Detection In The Wild.
+Jang, Y; Gunes, H; Patras, I
+© Copyright 2018 IEEE
+For additional information about this publication click this link.
+http://qmro.qmul.ac.uk/xmlui/handle/123456789/36405
+Information about this research object was correct at the time of download; we occasionally
+make corrections to records, please therefore check the published record when citing. For
+more information contact"
+8ee62f7d59aa949b4a943453824e03f4ce19e500,Robust Head-Pose Estimation Based on Partially-Latent Mixture of Linear Regressions,"Robust Head-Pose Estimation Based on
+Partially-Latent Mixture of Linear Regression
+Vincent Drouard∗, Radu Horaud∗, Antoine Deleforge†, Sil`eye Ba∗ and Georgios Evangelidis∗
+INRIA Grenoble Rhˆone-Alpes, Montbonnot Saint-Martin, France
+INRIA Rennes Bretagne Atlantique, Rennes, France"
+8e33183a0ed7141aa4fa9d87ef3be334727c76c0,Robustness of Face Recognition to Image Manipulations,"– COS429 Written Report, Fall 2017 –
+Robustness of Face Recognition to Image Manipulations
+Cathy Chen (cc27), Zachary Liu (zsliu), and Lindy Zeng (lindy)
+. Motivation
+We can often recognize pictures of people we know even if the image has low resolution or obscures
+part of the face, if the camera angle resulted in a distorted image of the subject’s face, or if the
+subject has aged or put on makeup since we last saw them. Although this is a simple recognition task
+for a human, when we think about how we accomplish this task, it seems non-trivial for computer
+lgorithms to recognize faces despite visual changes.
+Computer facial recognition is relied upon for many application where accuracy is important.
+Facial recognition systems have applications ranging from airport security and suspect identiﬁcation
+to personal device authentication and face tagging [7]. In these real-world applications, the system
+must continue to recognize images of a person who looks slightly different due to the passage of
+time, a change in environment, or a difference in clothing.
+Therefore, we are interested in investigating face recognition algorithms and their robustness to
+image changes resulting from realistically plausible manipulations. Furthermore, we are curious
+bout whether the impact of image manipulations on computer algorithms’ face recognition ability
+mirrors related insights from neuroscience about humans’ face recognition abilities.
+. Goal
+In this project, we implement both face recognition algorithms and image manipulations. We then"
+8e3d0b401dec8818cd0245c540c6bc032f169a1d,McGan: Mean and Covariance Feature Matching GAN,"McGan: Mean and Covariance Feature Matching GAN
+Youssef Mroueh * 1 2 Tom Sercu * 1 2 Vaibhava Goel 2"
+8e94ed0d7606408a0833e69c3185d6dcbe22bbbe,For your eyes only,"© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE
+must  be  obtained  for  all  other  uses,  in  any  current  or  future  media,  including
+reprinting/republishing  this  material  for  advertising  or  promotional  purposes,
+reating  new  collective  works,  for  resale  or  redistribution  to  servers  or  lists,  or
+reuse of any copyrighted component of this work in other works.
+Pre-print of article that will appear at WACV 2012."
+8e461978359b056d1b4770508e7a567dbed49776,LOMo: Latent Ordinal Model for Facial Analysis in Videos,"LOMo: Latent Ordinal Model for Facial Analysis in Videos
+Karan Sikka1,∗
+Gaurav Sharma2,3,†
+Marian Bartlett1,∗,‡
+UCSD, USA
+MPI for Informatics, Germany
+IIT Kanpur, India"
+8ea30ade85880b94b74b56a9bac013585cb4c34b,From turbo hidden Markov models to turbo state-space models [face recognition applications],"FROM TURBO HIDDEN MARKOV MODELS TO TURBO STATE-SPACE MODELS
+Florent Perronnin and Jean-Luc Dugelay
+Institut Eur´ecom
+Multimedia Communications Department
+BP 193, 06904 Sophia Antipolis Cedex, France
+fflorent.perronnin,"
+8e8e3f2e66494b9b6782fb9e3f52aeb8e1b0d125,"Detecting and classifying scars, marks, and tattoos found in the wild","in  any  current  or
+future  media,
+for  all  other  uses,
+ 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be
+obtained
+including
+reprinting/republishing  this  material  for  advertising  or  promotional  purposes,  creating
+new  collective  works,  for  resale  or  redistribution  to  servers  or  lists,  or  reuse  of  any
+opyrighted component of this work in other works.
+Pre-print of article that will appear at BTAS 2012.!!"
+8e378ef01171b33c59c17ff5798f30293fe30686,A system for automatic face analysis based on statistical shape and texture models,"Lehrstuhl f¨ur Mensch-Maschine-Kommunikation
+der Technischen Universit¨at M¨unchen
+A System for Automatic Face Analysis
+Based on
+Statistical Shape and Texture Models
+Ronald M¨uller
+Vollst¨andiger Abdruck der von der Fakult¨at
+f¨ur Elektrotechnik und Informationstechnik
+der Technischen Universit¨at M¨unchen
+zur Erlangung des akademischen Grades eines
+Doktor-Ingenieurs
+genehmigten Dissertation
+Vorsitzender: Prof. Dr. rer. nat. Bernhard Wolf
+Pr¨ufer der Dissertation:
+. Prof. Dr.-Ing. habil. Gerhard Rigoll
+. Prof. Dr.-Ing. habil. Alexander W. Koch
+Die Dissertation wurde am 28.02.2008 bei der Technischen Universit¨at M¨unchen
+eingereicht und durch die Fakult¨at f¨ur Elektrotechnik und Informationstechnik
+m 18.09.2008 angenommen."
+8ed051be31309a71b75e584bc812b71a0344a019,Class-Based Feature Matching Across Unrestricted Transformations,"Class-based feature matching across unrestricted
+transformations
+Evgeniy Bart and Shimon Ullman"
+8e36100cb144685c26e46ad034c524b830b8b2f2,Modeling Facial Geometry using Compositional VAEs,"Modeling Facial Geometry using Compositional VAEs
+Timur Bagautdinov∗1, Chenglei Wu2, Jason Saragih2, Pascal Fua1, Yaser Sheikh2
+´Ecole Polytechnique F´ed´erale de Lausanne
+Facebook Reality Labs, Pittsburgh"
+8e0becfc5fe3ecdd2ac93fabe34634827b21ef2b,Learning from Longitudinal Face Demonstration - Where Tractable Deep Modeling Meets Inverse Reinforcement Learning,"International Journal of Computer Vision manuscript No.
+(will be inserted by the editor)
+Learning from Longitudinal Face Demonstration -
+Where Tractable Deep Modeling Meets Inverse Reinforcement Learning
+Chi Nhan Duong · Kha Gia Quach · Khoa Luu · T. Hoang Ngan Le · Marios
+Savvides · Tien D. Bui
+Received: date / Accepted: date"
+22043cbd2b70cb8195d8d0500460ddc00ddb1a62,Separability-Oriented Subclass Discriminant Analysis,"Separability-Oriented Subclass Discriminant
+Analysis
+Huan Wan, Hui Wang, Gongde Guo, Xin Wei"
+22137ce9c01a8fdebf92ef35407a5a5d18730dde,Recognition of Faces from single and Multi-View Videos,
+22264e60f1dfbc7d0b52549d1de560993dd96e46,UnitBox: An Advanced Object Detection Network,"UnitBox: An Advanced Object Detection Network
+Jiahui Yu1,2
+Yuning Jiang2
+Zhangyang Wang1
+Zhimin Cao2
+Thomas Huang1
+University of Illinois at Urbana−Champaign
+Megvii Inc
+{jyu79, zwang119, {jyn,"
+223ec77652c268b98c298327d42aacea8f3ce23f,Acted Facial Expressions In The Wild Database,"TR-CS-11-02
+Acted Facial Expressions In The Wild
+Database
+Abhinav Dhall, Roland Goecke, Simon
+Lucey, Tom Gedeon
+September 2011
+ANU Computer Science Technical Report Series"
+228558a2a38a6937e3c7b1775144fea290d65d6c,Nonparametric Context Modeling of Local Appearance for Pose- and Expression-Robust Facial Landmark Localization,"Nonparametric Context Modeling of Local Appearance
+for Pose- and Expression-Robust Facial Landmark Localization
+Brandon M. Smith1
+Jonathan Brandt2
+University of Wisconsin–Madison
+Zhe Lin2
+Adobe Research
+Li Zhang1
+http://www.cs.wisc.edu/~lizhang/projects/face-landmark-localization/"
+22fdd8d65463f520f054bf4f6d2d216b54fc5677,Efficient Small and Capital Handwritten Character Recognition with Noise Reduction,"International Journal of Emerging Technology and Advanced Engineering
+Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 3, Issue 8, August 2013)
+Efficient Small and Capital Handwritten Character
+Recognition with Noise Reduction
+Beerendra Kumar Pal, Prof. Shailendra Tiwari, Prof. Sandeep Kumar
+Department of Computer Science Engg., IES College of Technology, Bhopal"
+2251a88fbccb0228d6d846b60ac3eeabe468e0f1,Matrix-Based Kernel Subspace Methods,"Matrix-Based Kernel Subspace Methods
+S. Kevin Zhou
+Integrated Data Systems Department
+Siemens Corporate Research
+755 College Road East, Princeton, NJ 08540
+Email:"
+227b18fab568472bf14f9665cedfb95ed33e5fce,Compositional Dictionaries for Domain Adaptive Face Recognition,"Compositional Dictionaries for Domain Adaptive
+Face Recognition
+Qiang Qiu, and Rama Chellappa, Fellow, IEEE."
+227b1a09b942eaf130d1d84cdcabf98921780a22,Multi-feature shape regression for face alignment,"Yang et al. EURASIP Journal on Advances in Signal Processing  (2018) 2018:51
+https://doi.org/10.1186/s13634-018-0572-6
+EURASIP Journal on Advances
+in Signal Processing
+R ES EAR CH
+Multi-feature shape regression for face
+lignment
+Wei-Jong Yang, Yi-Chen Chen, Pau-Choo Chung and Jar-Ferr Yang*
+Open Access"
+22dabd4f092e7f3bdaf352edd925ecc59821e168,Exploiting side information in locality preserving projection,"Deakin Research Online
+This is the published version:
+An, Senjian, Liu, Wanquan and Venkatesh, Svetha 2008, Exploiting side information in
+locality preserving projection, in CVPR 2008 : Proceedings of the 26th IEEE Conference on
+Computer Vision and Pattern Recognition, IEEE, Washington, D. C., pp. 1-8.
+Available from Deakin Research Online:
+http://hdl.handle.net/10536/DRO/DU:30044576
+Reproduced with the kind permissions of the copyright owner.
+Personal use of this material is permitted. However, permission to reprint/republish this
+material for advertising or promotional purposes or for creating new collective works for
+resale or redistribution to servers or lists, or to reuse any copyrighted component of this work
+in other works must be obtained from the IEEE.
+Copyright : 2008, IEEE"
+2271d554787fdad561fafc6e9f742eea94d35518,Multimodale Mensch-Roboter-Interaktion für Ambient Assisted Living,"TECHNISCHE UNIVERSIT ¨AT M ¨UNCHEN
+Lehrstuhl f¨ur Mensch-Maschine-Kommunikation
+Multimodale Mensch-Roboter-Interaktion
+f¨ur Ambient Assisted Living
+Tobias F. Rehrl
+Vollst¨andiger Abdruck der von der Fakult¨at f¨ur Elektrotechnik und Informationstechnik
+der Technischen Universit¨at M¨unchen zur Erlangung des akademischen Grades eines
+Doktor-Ingenieurs (Dr.-Ing.)
+genehmigten Dissertation.
+Vorsitzende:
+Pr¨ufer der Dissertation: 1. Univ.-Prof. Dr.-Ing. habil. Gerhard Rigoll
+. Univ.-Prof. Dr.-Ing. Horst-Michael Groß
+Univ.-Prof. Dr.-Ing. Sandra Hirche
+(Technische Universit¨at Ilmenau)
+Die Dissertation wurde am 17. April 2013 bei der Technischen Universit¨at M¨unchen
+eingereicht und durch die Fakult¨at f¨ur Elektrotechnik und Informationstechnik am
+8. Oktober 2013 angenommen."
+22e189a813529a8f43ad76b318207d9a4b6de71a,What will Happen Next? Forecasting Player Moves in Sports Videos,"What will Happen Next?
+Forecasting Player Moves in Sports Videos
+Panna Felsen
+UC Berkeley, STATS
+Pulkit Agrawal
+UC Berkeley
+Jitendra Malik
+UC Berkeley"
+25c19d8c85462b3b0926820ee5a92fc55b81c35a,Pose-Invariant Facial Expression Recognition Using Variable-Intensity Templates,"Noname manuscript No.
+(will be inserted by the editor)
+Pose-Invariant Facial Expression Recognition
+Using Variable-Intensity Templates
+Shiro Kumano · Kazuhiro Otsuka · Junji Yamato ·
+Eisaku Maeda · Yoichi Sato
+Received: date / Accepted: date"
+258a8c6710a9b0c2dc3818333ec035730062b1a5,Benelearn 2005 Annual Machine Learning Conference of Belgium and the Netherlands CTIT P ROCEEDINGS OF THE FOURTEENTH,"Benelearn 2005
+Annual Machine Learning Conference of
+Belgium and the Netherlands
+CTIT PROCEEDINGS OF THE FOURTEENTH
+ANNUAL MACHINE LEARNING CONFERENCE
+OF BELGIUM AND THE NETHERLANDS
+Martijn van Otterlo, Mannes Poel and Anton Nijholt (eds.)"
+25695abfe51209798f3b68fb42cfad7a96356f1f,An Investigation into Combining Both Facial Detection and Landmark Localisation into a Unified Procedure Using Gpu Computing,"AN INVESTIGATION INTO COMBINING
+BOTH FACIAL DETECTION AND
+LANDMARK LOCALISATION INTO A
+UNIFIED PROCEDURE USING GPU
+COMPUTING
+J M McDonagh
+MSc by Research"
+250ebcd1a8da31f0071d07954eea4426bb80644c,DenseBox: Unifying Landmark Localization with End to End Object Detection,"DenseBox: Unifying Landmark Localization with
+End to End Object Detection
+Lichao Huang1
+Yi Yang2
+Yafeng Deng2
+Institute of Deep Learning
+Baidu Research
+Yinan Yu3"
+25337690fed69033ef1ce6944e5b78c4f06ffb81,Strategic Engagement Regulation: an Integration of Self-enhancement and Engagement,"STRATEGIC ENGAGEMENT REGULATION:
+AN INTEGRATION OF SELF-ENHANCEMENT AND ENGAGEMENT
+Jordan B. Leitner
+A dissertation submitted to the Faculty of the University of Delaware in partial
+fulfillment of the requirements for the degree of Doctor of Philosophy in Psychology
+Spring 2014
+© 2014 Jordan B. Leitner
+All Rights Reserved"
+25d3e122fec578a14226dc7c007fb1f05ddf97f7,The first facial expression recognition and analysis challenge,"The First Facial Expression Recognition and Analysis Challenge
+Michel F. Valstar, Bihan Jiang, Marc Mehu, Maja Pantic, and Klaus Scherer"
+2597b0dccdf3d89eaffd32e202570b1fbbedd1d6,Towards Predicting the Likeability of Fashion Images,"Towards predicting the likeability of fashion images
+Jinghua Wang, Abrar Abdul Nabi, Gang Wang, Member, IEEE, Chengde Wan, Tian-Tsong Ng, Member, IEEE,"
+25982e2bef817ebde7be5bb80b22a9864b979fb0,Facial Feature Tracking Under Varying Facial Expressions and Face Poses Based on Restricted Boltzmann Machines,"(a)26facialfeaturepointsthatwetrack(b)oneexamplesequenceFigure1.Facialfeaturepointtrackingunderexpressionvariationandocclusion.Inrecentyears,thesemodelshavebeenusedexplicitlytohandletheshapevariations[17][5].Thenonlinearityem-beddedinRBManditsvariantsmakesthemmoreeffectiveandefﬁcienttorepresentthenonrigiddeformationsofob-jectscomparedtothelinearmethods.Theirlargenumberofhiddennodesanddeeparchitecturesalsocanimposesufﬁ-cientconstraintsaswellasenoughdegreesoffreedomsintotherepresentationsofthetargetobjects.Inthispaper,wepresentaworkthatcaneffectivelytrackfacialfeaturepointsusingfaceshapepriormodelsthatareconstructedbasedonRBM.Thefacialfeaturetrackercantrack26facialfeaturepoints(Fig.1(a))eveniffaceshavedifferentfacialexpressions,varyingposes,orocclu-sion(Fig.1(b)).Unlikethepreviousworksthattrackfacialfeaturepointsindependentlyorbuildashapemodeltocap-turethevariationsoffaceshapeorappearanceregardlessofthefacialexpressionsandfaceposes,theproposedmodelcouldcapturethedistinctionsaswellasthevariationsoffaceshapesduetofacialexpressionandposechangeinauniﬁedframework.Speciﬁcally,weﬁrstconstructamodel1"
+25c108a56e4cb757b62911639a40e9caf07f1b4f,Recurrent Scale Approximation for Object Detection in CNN,"Recurrent Scale Approximation for Object Detection in CNN
+Yu Liu1,2, Hongyang Li2, Junjie Yan1, Fangyin Wei1, Xiaogang Wang2, Xiaoou Tang2
+Multimedia Laboratory at The Chinese University of Hong Kong
+SenseTime Group Limited"
+25e05a1ea19d5baf5e642c2a43cca19c5cbb60f8,Label Distribution Learning,"Label Distribution Learning
+Xin Geng*, Member, IEEE"
+2559b15f8d4a57694a0a33bdc4ac95c479a3c79a,Contextual Object Localization With Multiple Kernel Nearest Neighbor,"Contextual Object Localization With Multiple
+Kernel Nearest Neighbor
+Brian McFee, Student Member, IEEE, Carolina Galleguillos, Student Member, IEEE, and
+Gert Lanckriet, Member, IEEE"
+25f1f195c0efd84c221b62d1256a8625cb4b450c,Experiments with Facial Expression Recognition using Spatiotemporal Local Binary Patterns,"-4244-1017-7/07/$25.00 ©2007 IEEE
+ICME 2007"
+25885e9292957feb89dcb4a30e77218ffe7b9868,Analyzing the Affect of a Group of People Using Multi-modal Framework,"JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2016
+Analyzing the Affect of a Group of People Using
+Multi-modal Framework
+Xiaohua Huang, Abhinav Dhall, Xin Liu, Guoying Zhao, Jingang Shi, Roland Goecke and Matti Pietik¨ainen"
+259706f1fd85e2e900e757d2656ca289363e74aa,Improving People Search Using Query Expansions: How Friends Help To Find People,"Improving People Search Using Query Expansions
+How Friends Help To Find People
+Thomas Mensink and Jakob Verbeek
+LEAR - INRIA Rhˆone Alpes - Grenoble, France"
+258a2dad71cb47c71f408fa0611a4864532f5eba,Discriminative Optimization of Local Features for Face Recognition,"Discriminative Optimization
+of Local Features for Face Recognition
+H O S S E I N   A Z I Z P O U R
+Master of Science Thesis
+Stockholm, Sweden 2011"
+25127c2d9f14d36f03d200a65de8446f6a0e3bd6,Evaluating the Performance of Deep Supervised Auto Encoder in Single Sample Face Recognition Problem Using Kullback-leibler Divergence Sparsity Regularizer,"Journal of Theoretical and Applied Information Technology
+20th May 2016. Vol.87. No.2
+© 2005 - 2016 JATIT & LLS. All rights reserved.
+ISSN: 1992-8645                                                       www.jatit.org                                                          E-ISSN: 1817-3195
+EVALUATING THE PERFORMANCE OF DEEP SUPERVISED
+AUTO ENCODER IN SINGLE SAMPLE FACE RECOGNITION
+PROBLEM USING KULLBACK-LEIBLER DIVERGENCE
+SPARSITY REGULARIZER
+OTNIEL Y. VIKTORISA, 2ITO WASITO, 2ARIDA F. SYAFIANDINI
+Faculty of Computer  of Computer Science, Universitas Indonesia, Kampus UI Depok, Indonesia
+E-mail:  ,"