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Hu\u1ebf, Th\u1eeba Thi\u00ean Hu\u1ebf, Vietnam", "16.45955500", "107.59285650", "edu", "", "Vietnam", "2011"], ["Integrating Perception and Cognition for AGI", "", "Carnegie Mellon University", "Carnegie Mellon University", "Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA", "37.41021930", "-122.05965487", "edu", "", "United States", "2011"], ["Pedestrian detection and direction estimation by cascade detector with multi-classifiers utilizing feature interaction descriptor", "Toyota Central R&D Labs., Inc., Nagakute, Aichi 480-1192, Japan", "Toyota Central R&D Labs, Japan", "Toyota Central R&D Labs., Inc., Nagakute, Aichi 480-1192, Japan", "41\u756a\uff11 Yokomichi, Nagakute, Aichi Prefecture 480-1192, Japan", "35.16898430", "137.05429210", "company", "", "Japan", "2011"], ["Integrated Pedestrian and Direction Classification Using a Random Decision Forest", "", "University of Auckland", "University of Auckland", "Auckland 1010, New Zealand", "-36.85233780", "174.76910730", "edu", "", "", "2013"], ["Co-occurrence flow for pedestrian detection", "", "University of Cambridge", "University of Cambridge", "Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK", "52.17638955", "0.14308882", "edu", "", "United Kingdom", "2011"], ["Enabling Pedestrian Safety using Computer Vision Techniques: A Case Study of the 2018 Uber Inc. 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"University of Texas at San Antonio", "UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA", "29.58333105", "-98.61944505", "edu", "", "United States", "2015"], ["Dynamic management of a partial reconfigurable hardware architecture for pedestrian detection in regions of interest", "LE2I Laboratory. Univ. Bourgogne Franche Comté, F21000, Dijon, France", "LE2I Laboratory. Univ. Bourgogne Franche Comt\u00e9, Dijon, France", "LE2I Laboratory. Univ. Bourgogne Franche Comté, F21000, Dijon, France", "UFR Sciences et Techniques, all\u00e9e Alain Savary, 21000 Dijon, France", "47.31256900", "5.07361200", "edu", "", "France", "2017"], ["Approximation of feature pyramids in the DCT domain and its application to pedestrian detection", "Department of Electrical and Computer Engineering, Concordia University, Montreal, Quebec, Canada H3G 1M8", "Concordia University", "Concordia University", "Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA", "45.57022705", "-122.63709346", "edu", "", "United States", "2016"], ["UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking", "", "Hanyang University", "Hanyang University", "\ud55c\uc591\ub300, 206, \uc655\uc2ed\ub9ac\ub85c, \uc0ac\uadfc\ub3d9, \uc131\ub3d9\uad6c, \uc11c\uc6b8\ud2b9\ubcc4\uc2dc, 04763, \ub300\ud55c\ubbfc\uad6d", "37.55572710", "127.04366420", "edu", "", "South Korea", "2015"], ["Visual People Detection \u2013 Different Models , Comparison and Discussion", "", "TU Darmstadt", "TU Darmstadt", "Karolinenpl. 5, 64289 Darmstadt, Germany", "49.87482770", "8.65632810", "edu", "", "Germany", "2009"], ["Variant SemiBoost for Improving Human Detection in Application Scenes", "School of Computer Science and Engineering, South China University of Technology, Guangzhou, China", "South China University of Technology", "South China University of Technology", "\u534e\u5357\u7406\u5de5\u5927\u5b66, \u5927\u5b66\u57ce\u4e2d\u73af\u4e1c\u8def, \u5e7f\u5dde\u5927\u5b66\u57ce, \u65b0\u9020, \u756a\u79ba\u533a (Panyu), \u5e7f\u5dde\u5e02, \u5e7f\u4e1c\u7701, 510006, \u4e2d\u56fd", "23.05020420", "113.39880323", "edu", "", "China", "2018"], ["Fast moving pedestrian detection based on motion segmentation and new motion features", "Institute of Computer Science III, University of Bonn, Bonn, Germany", "University of Bonn", "University of Bonn", "Rheinische Friedrich-Wilhelms-Universit\u00e4t Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk K\u00f6ln, Nordrhein-Westfalen, 53113, Deutschland", "50.73381240", "7.10224650", "edu", "", "Germany", "2015"], ["Single-Pedestrian Detection Aided by Multi-pedestrian Detection", "", "Chinese University of Hong Kong", "Chinese University of Hong Kong", "Hong Kong, \u99ac\u6599\u6c34\u6c60\u65c1\u8def", "22.41626320", "114.21093180", "edu", "", "China", "2013"], ["Vehicle Detection Method Based on Edge Information and Local Transform Histogram", "", "Hanyang University", "Hanyang University", "\ud55c\uc591\ub300, 206, \uc655\uc2ed\ub9ac\ub85c, \uc0ac\uadfc\ub3d9, \uc131\ub3d9\uad6c, \uc11c\uc6b8\ud2b9\ubcc4\uc2dc, 04763, \ub300\ud55c\ubbfc\uad6d", "37.55572710", "127.04366420", "edu", "", "South Korea", "2013"], ["Quality-adaptive deep learning for pedestrian detection", "", "Purdue University", "Purdue University", "Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA", "40.43197220", "-86.92389368", "edu", "", "United States", "2017"], ["Pedestrian detection and tracking using HOG and oriented-LBP features", "", "Shenzhen Institutes of Advanced Technology", "Shenzhen Institutes of Advanced Technology", "\u4e2d\u56fd\u79d1\u5b66\u9662\u6df1\u5733\u5148\u8fdb\u6280\u672f\u7814\u7a76\u9662, 1068, \u79d1\u7814\u8def, \u6df1\u5733\u5927\u5b66\u57ce, \u4e09\u5751\u6751, \u5357\u5c71\u533a, \u6df1\u5733\u5e02, \u5e7f\u4e1c\u7701, 518000, \u4e2d\u56fd", "22.59805605", "113.98533784", "edu", "", "China", "2011"], ["A two-stage training deep neural network for small pedestrian detection", "Graduate School of Science and Engineering, Teikyo University", "Teikyo University", "Teikyo University", "Japan, \u3012173-8605 Tokyo, \u677f\u6a4b\u533a\u52a0\u8cc0\uff12\u4e01\u76ee\uff11\uff11\u2212\uff11", "35.75927460", "139.71450290", "edu", "", "Japan", "2017"], ["Adapting an object detector by considering the worst case: A conservative approach", "Electrical and Computer Engineering Dept., University of Missouri, Columbia, MO, USA", "University of Missouri", "University of Missouri", "L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA", "38.92676100", "-92.29193783", "edu", "", "United States", "2011"], ["Partial Occlusion Handling in Pedestrian Detection With a Deep Model", "Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong", "Chinese University of Hong Kong", "Chinese University of Hong Kong", "Hong Kong, \u99ac\u6599\u6c34\u6c60\u65c1\u8def", "22.41626320", "114.21093180", "edu", "", "China", "2016"], ["Learning and Exploiting Camera Geometry for Computer Vision", "", "Duke University", "Duke University", "Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA", "35.99905220", "-78.92906290", "edu", "", "United States", "2016"], ["Robust Multi-resolution Pedestrian Detection in Traffic Scenes", "", "Chinese Academy of Sciences", "Chinese Academy of Sciences", "\u4e2d\u56fd\u79d1\u5b66\u9662\u5fc3\u7406\u7814\u7a76\u6240, 16, \u6797\u8403\u8def, \u671d\u9633\u533a / Chaoyang, \u5317\u4eac\u5e02, 100101, \u4e2d\u56fd", "40.00447950", "116.37023800", "edu", "", "China", "2013"], ["Local Co-Occurrence Selection via Partial Least Squares for Pedestrian Detection", "University at Buffalo, The State University of New York, Buffalo, NY, USA", "State University of New York, Buffalo", "University at Buffalo, The State University of New York, Buffalo, NY, USA", "Buffalo, NY 14260, USA", "43.00080930", "-78.78896970", "edu", "", "United States", "2017"], ["Visualization of object image database by using logistic discriminant analysis", "National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568, Japan", "National Institute of Advanced Industrial Science and Technology", "National Institute of Advanced Industrial Science and Technology", "\u7523\u696d\u6280\u8853\u7dcf\u5408\u7814\u7a76\u6240\uff1b\u897f\u4e8b\u696d\u6240, \u5b66\u5712\u897f\u5927\u901a\u308a, Onogawa housing complex, \u3064\u304f\u3070\u5e02, \u8328\u57ce\u770c, \u95a2\u6771\u5730\u65b9, 305-0051, \u65e5\u672c", "36.05238585", "140.11852361", "edu", "", "Japan", "2016"], ["Pedestrian detection with geometric context from a single image", "Beijing University of Posts and Telecommunications, Beijing, China", "Beijing University of Posts and Telecommunications", "Beijing University of Posts and Telecommunications", "\u5317\u4eac\u90ae\u7535\u5927\u5b66, \u897f\u571f\u57ce\u8def, \u6d77\u6dc0\u533a, \u5317\u4eac\u5e02, 100082, \u4e2d\u56fd", "39.96014880", "116.35193921", "edu", "", "China", "2011"], ["People perception from RGB-D cameras for mobile robots", "School of Electrical and Automation Engineering, Shanghai University, Shanghai, 200072 China", "Shanghai University", "Shanghai University", "\u4e0a\u6d77\u5927\u5b66, \u9526\u79cb\u8def, \u5927\u573a\u9547, \u5b9d\u5c71\u533a (Baoshan), \u4e0a\u6d77\u5e02, 201906, \u4e2d\u56fd", "31.32235655", "121.38400941", "edu", "", "China", "2015"], ["Recognition in-the-Tail: Training Detectors for Unusual Pedestrians with Synthetic Imposters", "", "Carnegie Mellon University Silicon Valley", "CARNEGIE MELLON UNIVERSITY", "Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA", "37.41021930", "-122.05965487", "edu", "", "United States", "2017"], ["Out of sight: a toolkit for tracking occluded human joint positions", "University of St Andrews, St Andrews, UK", "University of St Andrews", "University of St Andrews", "University of St Andrews, North Street, Albany Park Student accommodation, Carngour, St Andrews, Fife, Scotland, KY16 9AJ, UK", "56.34119840", "-2.79309380", "edu", "", "United Kingdom", "2016"], ["Fast Pedestrian Detection Based on the Selective Window Differential Filter", "School of Electronic and Informatics Engineering, Jiangsu University, Zhenjiang, China", "Jiangsu University", "Jiangsu University", "\u6c5f\u82cf\u5927\u5b66, 301, \u5b66\u5e9c\u8def, \u4eac\u53e3\u533a, \u8c61\u5c71\u8857\u9053, \u4eac\u53e3\u533a (Jingkou), \u9547\u6c5f\u5e02 / Zhenjiang, \u6c5f\u82cf\u7701, 212013, \u4e2d\u56fd", "32.20302965", "119.50968362", "edu", "", "China", "2017"], ["On experimenting with pedestrian classification using neural network", "TDC, Network Systems and Technologies (NeST) Technopark, Thiruvananthapuram - 695581, India", "TDC, Network Systems and Technologies (NeST) Technopark, Thiruvananthapuram, India", "TDC, Network Systems and Technologies (NeST) Technopark, Thiruvananthapuram - 695581, India", "Park Centre, Technopark Campus, Thiruvananthapuram, Kerala 695581, India", "8.55809670", "76.88156050", "edu", "", "India", "2011"], ["Spatiotemporal Stacked Sequential Learning for Pedestrian Detection", "", "Computer Vision Center, Barcelona", "Computer Vision Center, Barcelona", "Campus UAB, Edifici O, s/n, 08193 Cerdanyola del Vall\u00e8s, Barcelona, Spain", "41.50089570", "2.11155300", "edu", "", "Spain", "2015"], ["Synthesizing a Scene-Specific Pedestrian Detector and Pose Estimator for Static Video Surveillance", "Volvo Construction Equipment, G\u00f6thenburg, Sweden", "Volvo Construction Equipment, G\u00f6thenburg, Sweden", "Volvo Construction Equipment, G\u00f6thenburg, Sweden", "Gropeg\u00e5rdsgatan 11, 417 15 G\u00f6teborg, Sweden", "57.71720040", "11.92185580", "company", "", "Sweden", "2018"], ["Leveraging RGB-D Data: Adaptive fusion and domain adaptation for object detection", "", "University of Freiburg", "Social Robotics Lab, University of Freiburg, Germany", "Fahnenbergplatz, 79085 Freiburg im Breisgau, Germany", "47.99354410", "7.84594960", "edu", "", "Germany", "2012"], ["A Diverse Dataset for Pedestrian Detection", "", "Max Planck Institute for Informatics", "Max Planck Institute for Informatics", "MPII, E1 4, Campus, Universit\u00e4t, Sankt Johann, Bezirk Mitte, Saarbr\u00fccken, Regionalverband Saarbr\u00fccken, Saarland, 66123, Deutschland", "49.25795660", "7.04577417", "edu", "", "Germany", ""], ["Exploiting Target Data to Learn Deep Convolutional Networks for Scene-Adapted Human Detection", "VIVA Research Laboratory, School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada", "University of Ottawa", "University of Ottawa", "University of Ottawa, 1, Stewart Street, Byward Market, Lowertown, Rideau-Vanier, Ottawa, Ontario, K1N 6N5, Canada", "45.42580475", "-75.68740118", "edu", "", "Canada", "2018"], ["Integrating Orientation Cue With EOH-OLBP-Based Multilevel Features for Human Detection", "Research and Development Department, AnKe Smart City Technology Company Ltd., Shenzhen, China", "Shenzhen Institutes of Advanced Technology", "Shenzhen Institutes of Advanced Technology", "\u4e2d\u56fd\u79d1\u5b66\u9662\u6df1\u5733\u5148\u8fdb\u6280\u672f\u7814\u7a76\u9662, 1068, \u79d1\u7814\u8def, \u6df1\u5733\u5927\u5b66\u57ce, \u4e09\u5751\u6751, \u5357\u5c71\u533a, \u6df1\u5733\u5e02, \u5e7f\u4e1c\u7701, 518000, \u4e2d\u56fd", "22.59805605", "113.98533784", "edu", "", "China", "2013"], ["Is pedestrian detection robust for surveillance?", "Nanyang Technological University, Singapore", "Nanyang Technological University", "Nanyang Technological University", "NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore", "1.34841040", "103.68297965", "edu", "", "Singapore", "2015"], ["MuseumVisitors: A dataset for pedestrian and group detection, gaze estimation and behavior understanding", "", "Columbia University", "Columbia University", "Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA", "40.84198360", "-73.94368971", "edu", "", "United States", "2015"], ["Pedestrian Detection in Video Images via Error Correcting Output Code Classification of Manifold Subclasses", "College of Engineering, Graduate University of Chinese Academy of Sciences, Beijing, China", "Graduate University of Chinese Academy of Sciences", "Graduate University of Chinese Academy of Sciences", "China, Beijing, Haidian, Zhongguancun South 1st Alley, \u4e2d\u5173\u6751\u5357\u4e00\u6761", "39.98177000", "116.33008600", "edu", "", "", "2012"], ["A discriminative deep model for pedestrian detection with occlusion handling", "Department of Electronic Engineering, The Chinese University of Hong Kong", "Chinese University of Hong Kong", "Chinese University of Hong Kong", "Hong Kong, \u99ac\u6599\u6c34\u6c60\u65c1\u8def", "22.41626320", "114.21093180", "edu", "", "China", "2012"], ["Pedestrian Detection: An Evaluation of the State of the Art", "MPI Informatics, Saabrucken", "MPI Informatics, Saabrucken", "MPI Informatics, Saabrucken", "Campus E1 4, 66123, Stuhlsatzenhausweg, 66123 Saarbr\u00fccken, Germany", "49.25786570", "7.04579560", "edu", "", "Germany", "2012"], ["The WILDTRACK Multi-Camera Person Dataset", "", "ETH Zurich", "ETH Zurich", "R\u00e4mistrasse 101, 8092 Z\u00fcrich, Switzerland", "47.37631300", "8.54766990", "edu", "", "Switzerland", "2017"], ["Vision-based pedestrian monitoring at intersections including behavior & crossing count", "Electrical and Computer Engineering Department, University of Nevada, Las Vegas, 89154, USA", "University of Nevada", "University of Nevada", "Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA", "39.54694490", "-119.81346566", "edu", "", "United States", "2016"], ["Gradient Response Maps for Real-Time Detection of Textureless Objects", "Technische Universitat Muenchen, Garching bie Muenchen", "Technische Universitat Muenchen", "Technische Universitat Muenchen, Garching bie Muenchen", "Boltzmannstra\u00dfe 15, 85748 Garching bei M\u00fcnchen, Germany", "48.26480530", "11.66886010", "edu", "", "Germany", "2012"], ["Pedestrian Detection Based on Sparse and Low-Rank Matrix Decomposition", "", "Jiangsu University", "Jiangsu University", "\u6c5f\u82cf\u5927\u5b66, 301, \u5b66\u5e9c\u8def, \u4eac\u53e3\u533a, \u8c61\u5c71\u8857\u9053, \u4eac\u53e3\u533a (Jingkou), \u9547\u6c5f\u5e02 / Zhenjiang, \u6c5f\u82cf\u7701, 212013, \u4e2d\u56fd", "32.20302965", "119.50968362", "edu", "", "China", "2014"], ["Pedestrian detection in digital videos using committee of motion feature extractors", "Universidade de Pernambuco(UPE), Recife, Brazil, Instituto Federal de Pernambuco (IFPE), Palmares, Brazil", "Universidad Nacional de Mar del Plata, Argentina", "Laboratorio de Comunicaciones e ICYTE y Departamento Informática, Facultad de Ingeniería, Universidad Nacional de Mar del Plata (UNMDP), Mar del Plata, Argentina", "De\u00e1n Funes 3350, B7602AYL Mar del Plata, Buenos Aires, Argentina", "-38.00537090", "-57.57090000", "edu", "", "Argentina", "2017"], ["Fusion of Depth and Vision Information for Human Detection \u22c6", "", "Wayne State University", "Wayne State University", "Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA", "42.35775700", "-83.06286711", "edu", "", "United States", "2013"], ["Spatial-Temporal Granularity-Tunable Gradients Partition (STGGP) Descriptors for Human Detection", "", "University of Oulu", "University of Oulu", "Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi", "65.05921570", "25.46632601", "edu", "", "Finland", "2010"], ["Context-aware pedestrian detection especially for small-sized instances with Deconvolution Integrated Faster RCNN (DIF R-CNN)", "Division of Electronical Engineering, Hanyang University, Ansan, Republic of Korea", "Hanyang University", "Hanyang University", "\ud55c\uc591\ub300, 206, \uc655\uc2ed\ub9ac\ub85c, \uc0ac\uadfc\ub3d9, \uc131\ub3d9\uad6c, \uc11c\uc6b8\ud2b9\ubcc4\uc2dc, 04763, \ub300\ud55c\ubbfc\uad6d", "37.55572710", "127.04366420", "edu", "", "South Korea", "2018"], ["Multiresolution models for object detection", "", "University of California, Irvine", "University of California, Irvine", "Irvine, CA 92697, USA", "33.64049520", "-117.84429620", "edu", "", "", "2010"], ["Gradient-based region of interest selection for faster pedestrian detection", "Technical University of Cluj Napoca", "Technical University of Cluj Napoca", "Technical University of Cluj Napoca", "Strada Memorandumului 28, Cluj-Napoca 400114, Romania", "46.76929900", "23.58561300", "edu", "", "Romania", "2013"], ["Scan window based pedestrian recognition methods improvement by search space and scale reduction", "Image Processing and Pattern Recognition Group, Computer Science Department, Technical University of Cluj-Napoca, Romania", "Technical University of Cluj-Napoca", "Technical University of Cluj-Napoca", "Strada Memorandumului 28, Cluj-Napoca 400114, Romania", "46.76929900", "23.58561300", "edu", "", "Romania", "2014"], ["Long term carefully learning for person detection application to intelligent surveillance system", "Hue University of Sciences, Vietnam", "Hue University of Sciences", "Hue University of Sciences, Vietnam", "77 Nguy\u1ec5n Hu\u1ec7, Ph\u00fa Nhu\u1eadn, Tp. Hu\u1ebf, Th\u1eeba Thi\u00ean Hu\u1ebf, Vietnam", "16.45955500", "107.59285650", "edu", "", "Vietnam", "2011"], ["Integrating Perception and Cognition for AGI", "", "Carnegie Mellon University Silicon Valley", "CARNEGIE MELLON UNIVERSITY", "Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA", "37.41021930", "-122.05965487", "edu", "", "United States", "2011"], ["Pedestrian detection and direction estimation by cascade detector with multi-classifiers utilizing feature interaction descriptor", "Toyota Central R&D Labs., Inc., Nagakute, Aichi 480-1192, Japan", "Toyota Central R&D Labs, Japan", "Toyota Central R&D Labs., Inc., Nagakute, Aichi 480-1192, Japan", "41\u756a\uff11 Yokomichi, Nagakute, Aichi Prefecture 480-1192, Japan", "35.16898430", "137.05429210", "company", "", "Japan", "2011"], ["Integrated Pedestrian and Direction Classification Using a Random Decision Forest", "", "University of Auckland", "University of Auckland", "Auckland 1010, New Zealand", "-36.85233780", "174.76910730", "edu", "", "", "2013"], ["Co-occurrence flow for pedestrian detection", "", "University of Cambridge", "University of Cambridge", "Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK", "52.17638955", "0.14308882", "edu", "", "United Kingdom", "2011"], ["Enabling Pedestrian Safety using Computer Vision Techniques: A Case Study of the 2018 Uber Inc. Self-driving Car Crash", "", "Texas A&M University", "Texas A&M University", "Texas A&M University, Horticulture Street, Park West, College Station, Brazos County, Texas, 77841, USA", "30.61083650", "-96.35212800", "edu", "", "United States", "2018"], ["Joint Attention in Driver-Pedestrian Interaction: from Theory to Practice", "", "York University", "York University", "York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada", "43.77439110", "-79.50481085", "edu", "", "Canada", "2018"], ["Adaptation for Person Detection", "", "Duke University", "Duke University", "Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA", "35.99905220", "-78.92906290", "edu", "", "United States", "2016"], ["Pedestrian Detection with Semantic Regions of Interest", "", "University of Chinese Academy of Sciences", "University of Chinese Academy of Sciences", "University of Chinese Academy of Sciences, UCAS, Yuquanlu, \u7389\u6cc9\u8def, \u7530\u6751, \u6d77\u6dc0\u533a, 100049, \u4e2d\u56fd", "39.90828040", "116.24585270", "edu", "", "China", "2017"], ["Human head detection using Histograms of Oriented optical flow in low quality videos with occlusion", "ISSNIP, Department of Electrical and Electronic Engineering, The University of Melbourne, Victoria - 3010, Australia", "University of Melbourne", "ISSNIP, The University of Melbourne, Victoria - 3010, Australia", "Parkville VIC 3010, Australia", "-37.79636890", "144.96117380", "edu", "", "Australia", "2013"], ["Human Detection by Quadratic Classification on Subspace of Extended Histogram of Gradients", "School of Electrical and Electronics Engineering, Nanyang Technological University, Singapore", "Nanyang Technological University", "Nanyang Technological University", "NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore", "1.34841040", "103.68297965", "edu", "", "Singapore", "2014"], ["Intensity self similarity features for pedestrian detection in Far-Infrared images", "Laboratoire d'Informatique, de Traitement de l'Information et des Systemes, INSA Rouen, Avenue de l'Universite, 76800, Saint-Etienne-du-Rouvray, France", "INSA Rouen, France", "Laboratoire d'Informatique, de Traitement de l'Information et des Systemes, INSA Rouen, Avenue de l'Universite, 76800, Saint-Etienne-du-Rouvray, France", "685 Avenue de l'Universit\u00e9, 76800 Saint-\u00c9tienne-du-Rouvray, France", "49.38497570", "1.06832570", "edu", "", "France", "2012"]]}
\ No newline at end of file