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50 People 1 Question

Dataset Citations

@@ -104,11 +98,10 @@

An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)

49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)

Additional Resources

The dataset author spoke about his research at the CVPR conference in 2016 https://www.youtube.com/watch?v=Nl2fBKxwusQ

TODO

49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)

TODO

include the images referenced in the chinese defence papers?
change supp images to 2x2 grid with bboxes
add bounding boxes to the header image
remake montage with randomized images, with bboxes
clean up intro text
verify quote citations

a
"readme.txt" https://exhibits.stanford.edu/data/catalog/sx925dc9385.
+
a
Stewart, Russel. Andriluka, Mykhaylo. "End-to-end people detection in crowded scenes". 2016.
a
Li, Y. and Dou, Y. and Liu, X. and Li, T. Localized Region Context and Object Feature Fusion for People Head Detection. ICIP16 Proceedings. 2016. Pages 594-598.
a
Zhao. X, Wang Y, Dou, Y. A Replacement Algorithm of Non-Maximum Suppression Base on Graph Clustering.

@@ -142,11 +129,10 @@

Dataset Citations

@@ -116,11 +110,10 @@

Who used COFW Dataset?

+ +

+ This bar chart presents a ranking of the top countries where dataset citations originated. Mouse over individual columns to see yearly totals. These charts show at most the top 10 countries. +

+ +

Biometric Trade Routes

+ +

+ To help understand how COFW Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Caltech Occluded Faces in the Wild was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal research projects at that location. +

+ +

Academic
Commercial
Military / Government

Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.

+ + +

+ +

Dataset Citations

+ The dataset citations used in the visualizations were collected from Semantic Scholar, a website which aggregates and indexes research papers. Each citation was geocoded using names of institutions found in the PDF front matter, or as listed on other resources. These papers have been manually verified to show that researchers downloaded and used the dataset to train or test machine learning algorithms. +

+ +

(ignore) research notes

Years

1993-1996

Images

14,126

Identities

1,199

Origin

Web Searches

Funded by

ODNI, IARPA, Microsoft

COFW is "is designed to benchmark face landmark algorithms in realistic conditions, which include heavy occlusions and large shape variations" [Robust face landmark estimation under occlusion].

We asked four people with different levels of computer vision knowledge to each collect 250 faces representative of typical real-world images, with the clear goal of challenging computer vision methods. The result is 1,007 images of faces obtained from a variety of sources.

@@ -56,25 +107,15 @@ To increase the number of training images, and since COFW has the exact same la

Biometric Trade Routes

- +

- To help understand how COFW Dataset has been used around the world for commercial, military and academic research; publicly available research citing Caltech Occluded Faces in the Wild is collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location. + To help understand how COFW Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Caltech Occluded Faces in the Wild was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the location markers to reveal research projects at that location.

@@ -82,23 +123,16 @@ To increase the number of training images, and since COFW has the exact same la

Academic

Commercial

Military / Government

Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.

- -

Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.

Supplementary Information

@@ -129,11 +163,10 @@ To increase the number of training images, and since COFW has the exact same la

Duke MTMC pixel-averaged image of camera #5 is shown with the bounding boxes for each student drawn in white. (c) Adam Harvey

According to the dataset authors,

Duke MTMC

[ page under development ]

The Duke Multi-Target, Multi-Camera Tracking Dataset (MTMC) is a dataset of video recorded on Duke University campus during for the purpose of training, evaluating, and improving multi-target multi-camera tracking for surveillance. The dataset includes over 14 hours of 1080p video from 8 cameras positioned around Duke's campus during February and March 2014. Over 2,700 unique people are included in the dataset, which has become of the most widely used person re-identification image datasets.

The 8 cameras deployed on Duke's campus were specifically setup to capture students "during periods between lectures, when pedestrian traffic is heavy".

Who used Duke MTMC Dataset?

+ +

+ This bar chart presents a ranking of the top countries where dataset citations originated. Mouse over individual columns to see yearly totals. These charts show at most the top 10 countries. +

+ +

Biometric Trade Routes

- +

- To help understand how Duke MTMC Dataset has been used around the world for commercial, military and academic research; publicly available research citing Duke Multi-Target, Multi-Camera Tracking Project is collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location. + To help understand how Duke MTMC Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Duke Multi-Target, Multi-Camera Tracking Project was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal research projects at that location.

@@ -81,30 +87,19 @@

Academic

Commercial

Military / Government

Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.

Who used Duke MTMC Dataset?

+ +

Dataset Citations

- This bar chart presents a ranking of the top countries where dataset citations originated. Mouse over individual columns to see yearly totals. These charts show at most the top 10 countries. + The dataset citations used in the visualizations were collected from Semantic Scholar, a website which aggregates and indexes research papers. Each citation was geocoded using names of institutions found in the PDF front matter, or as listed on other resources. These papers have been manually verified to show that researchers downloaded and used the dataset to train or test machine learning algorithms.

- -

@@ -112,93 +107,29 @@

Supplementary Information

- -

Dataset Citations

- The dataset citations used in the visualizations were collected from Semantic Scholar, a website which aggregates and indexes research papers. Each citation was geocoded using names of institutions found in the PDF front matter, or as listed on other resources. These papers have been manually verified to show that researchers downloaded and used the dataset to train or test machine learning algorithms. -

- -

Research Notes

Data Visualizations

Duke MTMC pixel-averaged image of camera #5 is shown with the bounding boxes for each student drawn in white. (c) Adam Harvey

TODO

"We make available a new data set that has more than 2 million frames and more than 2,700 identities. It consists of 8×85 minutes of 1080p video recorded at 60 frames per second from 8 static cameras deployed on the Duke University campus during periods between lectures, when pedestrian traffic is heavy." - 27a2fad58dd8727e280f97036e0d2bc55ef5424c
"This work was supported in part by the EPSRC Programme Grant (FACER2VM) EP/N007743/1, EPSRC/dstl/MURI project EP/R018456/1, the National Natural Science Foundation of China (61373055, 61672265, 61602390, 61532009, 61571313), Chinese Ministry of Education (Z2015101), Science and Technology Department of Sichuan Province (2017RZ0009 and 2017FZ0029), Education Department of Sichuan Province (15ZB0130), the Open Research Fund from Province Key Laboratory of Xihua University (szjj2015-056) and the NVIDIA GPU Grant Program." - ec9c20ed6cce15e9b63ac96bb5a6d55e69661e0b
"DukeMTMC aims to accelerate advances in multi-target multi-camera tracking. It provides a tracking system that works within and across cameras, a new large scale HD video data set recorded by 8 synchronized cameras with more than 7,000 single camera trajectories and over 2,000 unique identities, and a new performance evaluation method that measures how often a system is correct about who is where"
DukeMTMC is a new, manually annotated, calibrated, multi-camera data set recorded outdoors on the Duke University campus with 8 synchronized cameras. It consists of:
-
8 static cameras x 85 minutes of 1080p 60 fps video - More than 2,000,000 manually annotated frames - More than 2,000 identities - Manual annotation by 5 people over 1 year - More identities than all existing MTMC datasets combined - Unconstrained paths, diverse appearance
-
DukeMTMC Project -Ergys Ristani Ergys Ristani Ergys Ristani Ergys Ristani Ergys Ristani
change to heatmap overlay of each location
make fancy viz of foot trails with bbox and blurred persons
expand story
add google street view images of each camera location?
add actual head detections to header image with faces blurred
add 4 diverse example images with faces blurred
add map location of the brainwash cafe

People involved: -Ergys Ristani, Francesco Solera, Roger S. Zou, Rita Cucchiara, Carlo Tomasi.

Navigation:

Data Set - Downloads - Downloads - Dataset Extensions - Performance Measures - Tracking Systems - Publications - How to Cite - Contact

Welcome to the Duke Multi-Target, Multi-Camera Tracking Project.

DukeMTMC aims to accelerate advances in multi-target multi-camera tracking. It provides a tracking system that works within and across cameras, a new large scale HD video data set recorded by 8 synchronized cameras with more than 7,000 single camera trajectories and over 2,000 unique identities, and a new performance evaluation method that measures how often a system is correct about who is where. -DukeMTMC Data Set -Snapshot from the DukeMTMC data set.

DukeMTMC is a new, manually annotated, calibrated, multi-camera data set recorded outdoors on the Duke University campus with 8 synchronized cameras. It consists of:

8 static cameras x 85 minutes of 1080p 60 fps video - More than 2,000,000 manually annotated frames - More than 2,000 identities - Manual annotation by 5 people over 1 year - More identities than all existing MTMC datasets combined - Unconstrained paths, diverse appearance

News

05 Feb 2019 We are organizing the 2nd Workshop on MTMCT and ReID at CVPR 2019 - 25 Jul 2018: The code for DeepCC is available on github - 28 Feb 2018: OpenPose detections now available for download - 19 Feb 2018: Our DeepCC tracker has been accepted to CVPR 2018 - 04 Oct 2017: A new blog post describes ID measures of performance - 26 Jul 2017: Slides from the BMTT 2017 workshop are now available - 09 Dec 2016: DukeMTMC is now hosted on MOTChallenge

DukeMTMC Downloads

DukeMTMC dataset (tracking)

Dataset Extensions

Below is a list of dataset extensions provided by the community:

DukeMTMC-VideoReID (download) - DukeMTMC-reID (download) - DukeMTMC4REID - DukeMTMC-attribute

If you use or extend DukeMTMC, please refer to the license terms. -DukeMTMCT Benchmark

DukeMTMCT is a tracking benchmark hosted on motchallenge.net. Click here for the up-to-date rankings. Here you will find the official motchallenge-devkit used for evaluation by MOTChallenge. For detailed instructions how to submit on motchallenge you can refer to this link.

Trackers are ranked using our identity-based measures which compute how often the system is correct about who is where, regardless of how often a target is lost and reacquired. Our measures are useful in applications such as security, surveillance or sports. This short post describes our measures with illustrations, while for details you can refer to the original paper. -Tracking Systems

We provide code for the following tracking systems which are all based on Correlation Clustering optimization:

DeepCC for single- and multi-camera tracking [1] - Single-Camera Tracker (demo video) [2] - Multi-Camera Tracker (demo video, failure cases) [2] - People-Groups Tracker [3] - Original Single-Camera Tracker [4]

Who used HRT Transgender?

- -

- This bar chart presents a ranking of the top countries where dataset citations originated. Mouse over individual columns to see yearly totals. These charts show at most the top 10 countries. -

- -

Biometric Trade Routes

- -

- To help understand how HRT Transgender has been used around the world for commercial, military and academic research; publicly available research citing HRT Transgender Dataset is collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location. -

- -

Academic
Commercial
Military / Government
Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.

- -

Supplementary Information

- -

Dataset Citations

- -

HRT Transgender Dataset

[ page under development ]

{% include 'dashboard.html' }

All 5,379 people in the Labeled Faces in The Wild Dataset. Showing one face per person

The Names and Faces dataset was the first face recognition dataset created entire from online photos. However, Names and Faces and LFW are not the first face recognition dataset created entirely "in the wild". That title belongs to the UCD dataset. Images obtained "in the wild" means using an image without explicit consent or awareness from the subject or photographer.

Who used LFW?

+ +

+ This bar chart presents a ranking of the top countries where dataset citations originated. Mouse over individual columns to see yearly totals. These charts show at most the top 10 countries. +

+ +

Biometric Trade Routes

- +

- To help understand how LFW has been used around the world for commercial, military and academic research; publicly available research citing Labeled Faces in the Wild is collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location. + To help understand how LFW has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Labeled Faces in the Wild was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal research projects at that location.

@@ -88,30 +88,19 @@

Academic

Commercial

Military / Government

Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.

Who used LFW?

+ +

Dataset Citations

- -

@@ -119,33 +108,52 @@

Supplementary Information

- -

Dataset Citations

- -

Commercial Use

Add a paragraph about how usage extends far beyond academia into research centers for largest companies in the world. And even funnels into CIA funded research in the US and defense industry usage in China.

Research, text, and graphics ©Adam Harvey / megapixels.cc

Research

"In our experiments, we used 10000 images and associated captions from the Faces in the wilddata set [3]."
"This work was supported in part by the Center for Intelligent Information Retrieval, the Central Intelligence Agency, the National Security Agency and National Science Foundation under CAREER award IIS-0546666 and grant IIS-0326249."
From: "People-LDA: Anchoring Topics to People using Face Recognition" https://www.semanticscholar.org/paper/People-LDA%3A-Anchoring-Topics-to-People-using-Face-Jain-Learned-Miller/10f17534dba06af1ddab96c4188a9c98a020a459 and https://ieeexplore.ieee.org/document/4409055
This paper was presented at IEEE 11th ICCV conference Oct 14-21 and the main LFW paper "Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments" was also published that same year
10f17534dba06af1ddab96c4188a9c98a020a459
This research is based upon work supported in part by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via contract number 2014-14071600010.
From "Labeled Faces in the Wild: Updates and New Reporting Procedures"
70% of people in the dataset have only 1 image and 29% have 2 or more images
The LFW dataset is considered the "most popular benchmark for face recognition" 2
The LFW dataset is "the most widely used evaluation set in the field of facial recognition" 3
All images in LFW dataset were obtained "in the wild" meaning without any consent from the subject or from the photographer
The faces in the LFW dataset were detected using the Viola-Jones haarcascade face detector [^lfw_website] [^lfw-survey]
The LFW dataset is used by several of the largest tech companies in the world including "Google, Facebook, Microsoft Research Asia, Baidu, Tencent, SenseTime, Face++ and Chinese University of Hong Kong." 3
All images in the LFW dataset were copied from Yahoo News between 2002 - 2004
In 2014, two of the four original authors of the LFW dataset received funding from IARPA and ODNI for their followup paper Labeled Faces in the Wild: Updates and New Reporting Procedures via IARPA contract number 2014-14071600010
The dataset includes 2 images of George Tenet, the former Director of Central Intelligence (DCI) for the Central Intelligence Agency whose facial biometrics were eventually used to help train facial recognition software in China and Russia
./15/155205b8e288fd49bf203135871d66de879c8c04/paper.txt shows usage by DSTO Australia, supported parimal@iisc.ac.in

Created

2002 – 2004

Images

13,233

Identities

5,749

Origin

Yahoo! News Images

Used by

Facebook, Google, Microsoft, Baidu, Tencent, SenseTime, Face++, CIA, NSA, IARPA

Website

umass.edu

There are about 3 men for every 1 woman in the LFW dataset 1
The person with the most images is George W. Bush with 530
There are about 3 George W. Bush's for every 1 Tony Blair
The LFW dataset includes over 500 actors, 30 models, 10 presidents, 124 basketball players, 24 football players, 11 kings, 7 queens, and 1 Moby
In all 3 of the LFW publications [^lfw_original_paper], [^lfw_survey], [^lfw_tech_report] the words "ethics", "consent", and "privacy" appear 0 times
The word "future" appears 71 times
* denotes partial funding for related research

a b
http://vis-www.cs.umass.edu/lfw/results.html
-
Jingtuo Liu, Yafeng Deng, Tao Bai, Zhengping Wei, Chang Huang. Targeting Ultimate Accuracy: Face Recognition via Deep Embedding. https://arxiv.org/abs/1506.07310
-
a
Lee, Justin. "PING AN Tech facial recognition receives high score in latest LFW test results". BiometricUpdate.com. Feb 13, 2017. https://www.biometricupdate.com/201702/ping-an-tech-facial-recognition-receives-high-score-in-latest-lfw-test-results
+
a
Jingtuo Liu, Yafeng Deng, Tao Bai, Zhengping Wei, Chang Huang. Targeting Ultimate Accuracy: Face Recognition via Deep Embedding. https://arxiv.org/abs/1506.07310
+
a b c
Lee, Justin. "PING AN Tech facial recognition receives high score in latest LFW test results". BiometricUpdate.com. Feb 13, 2017. https://www.biometricupdate.com/201702/ping-an-tech-facial-recognition-receives-high-score-in-latest-lfw-test-results

Who used MsCeleb?

@@ -65,30 +63,24 @@

+ +

Biometric Trade Routes

- +

- To help understand how MsCeleb has been used around the world for commercial, military and academic research; publicly available research citing Microsoft Celebrity Dataset is collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location. + To help understand how MsCeleb has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Microsoft Celebrity Dataset was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal research projects at that location.

@@ -96,26 +88,12 @@

Academic

Commercial

Military / Government

Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.

Add more analysis here

- -

Supplementary Information

- -

Dataset Citations

@@ -123,6 +101,15 @@

+ +

Supplementary Information

Additional Information

The dataset author spoke about his research at the CVPR conference in 2016 https://www.youtube.com/watch?v=Nl2fBKxwusQ

Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.

- -

Supplementary Information

- -

Dataset Citations

@@ -102,18 +98,16 @@

Research Notes

MegaPixels.cc - Disclaimer - Terms of Use - Privacy + Datasets About - Team + Press + Legal and Privacy

MegaPixels ©2017-19 Adam R. Harvey / diff --git a/site/public/datasets/pubfig/index.html b/site/public/datasets/pubfig/index.html new file mode 100644 index 00000000..c46eeea3 --- /dev/null +++ b/site/public/datasets/pubfig/index.html @@ -0,0 +1,117 @@ + + + + MegaPixels + + + + + + + + + + + +

+ +

MegaPixels

PubFig

+ +

+ Datasets + About +

+ +

PubFig is a dataset...

[ add subdescrition ] +

PubFig

[ PAGE UNDER DEVELOPMENT ]

Who used PubFig?

+ +

+ This bar chart presents a ranking of the top countries where dataset citations originated. Mouse over individual columns to see yearly totals. These charts show at most the top 10 countries. +

+ +

Biometric Trade Routes

+ +

+ To help understand how PubFig has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Public Figures Face Dataset was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal research projects at that location. +

+ +

Academic
Commercial
Military / Government

Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.

+ + +

+ +

Dataset Citations

+ +

+ + + + + \ No newline at end of file diff --git a/site/public/datasets/uccs/index.html b/site/public/datasets/uccs/index.html index 593ac498..5bb120ba 100644 --- a/site/public/datasets/uccs/index.html +++ b/site/public/datasets/uccs/index.html @@ -4,7 +4,7 @@ MegaPixels - + @@ -26,7 +26,7 @@

Unconstrained College Students (UCCS) is a dataset of long-range surveillance photos of students taken without their knowledge

The UCCS dataset includes 16,149 images and 1,732 identities of students at University of Colorado Colorado Springs campus and is used for face recognition and face detection +

UnConstrained College Students is a dataset of long-range surveillance photos of students at University of Colorado in Colorado Springs

The UnConstrained College Students dataset includes 16,149 images and 1,732 identities of subjects on University of Colorado Colorado Springs campus and is used for making face recognition and face detection algorithms

Unconstrained College Students ...

(PAGE UNDER DEVELOPMENT)

Unconstrained College Students (UCCS) is a dataset of long-range surveillance photos captured at University of Colorado Colorado Springs. According to the authors of two papers associated with the dataset, subjects were "photographed using a long-range high-resolution surveillance camera without their knowledge" [^funding_sb]. The images were captured using a Canon 7D digital camera fitted with a Sigma 800mm telephoto lens pointed out the window of an office.

The UCCS dataset was funded by ODNI (Office of Director of National Intelligence), IARPA (Intelligence Advance Research Projects Activity), ONR MURI Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative, Army SBIR (Small Business Innovation Research), SOCOM SBIR (Special Operations Command and Small Business Innovation Research), and the National Science Foundation.

The images in UCCS include students walking between classes on campus over 19 days in 2012 - 2013. The dates include:

UnConstrained College Students

[ page under development ]

UnConstrained College Students (UCCS) is a dataset of long-range surveillance photos captured at University of Colorado Colorado Springs. According to the authors of two papers associated with the dataset, subjects were "photographed using a long-range high-resolution surveillance camera without their knowledge" 2. To create the dataset, the researchers used a Canon 7D digital camera fitted with a Sigma 800mm telephoto lens and photographed students 150–200m away through their office window. Photos were taken during the morning and afternoon while students were walking to and from classes. The primary uses of this dataset are to train, validate, and build recognition and face detection algorithms for realistic surveillance scenarios.

What makes the UCCS dataset unique is that it includes the highest resolution images of any publicly available face recognition dataset discovered so far (18MP), that it was captured on a campus without consent or awareness using a long-range telephoto lens, and that it was funded by United States defense and intelligence agencies.

Combined funding sources for the creation of the initial and final release of the dataset include ODNI (Office of Director of National Intelligence), IARPA (Intelligence Advance Research Projects Activity), ONR MURI (Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative), Army SBIR (Small Business Innovation Research), SOCOM SBIR (Special Operations Command and Small Business Innovation Research), and the National Science Foundation. 1 2

In 2017 the UCCS face dataset was used for a defense and intelligence agency funded face recognition challenge at the International Joint Biometrics Conference in Denver, CO. And in 2018 the dataset was used for the 2nd Unconstrained Face Detection and Open Set Recognition Challenge at the European Computer Vision Conference (ECCV) in Munich, Germany. Additional research projects that have used the UCCS dataset are included below in the list of verified citations.

Who used UCCS?

+ +

+ This bar chart presents a ranking of the top countries where dataset citations originated. Mouse over individual columns to see yearly totals. These charts show at most the top 10 countries. +

+ +

Biometric Trade Routes

+ +

+ To help understand how UCCS has been used around the world by commercial, military, and academic organizations; existing publicly available research citing UnConstrained College Students Dataset was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal research projects at that location. +

+ +

Academic
Commercial
Military / Government

Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.

+ + +

+ +

Dataset Citations

+ +

Supplementary Information

+ +

Dates and Times

The images in UCCS were taken on 18 non-consecutive days during 2012–2013. Analysis of the EXIF data embedded in original images reveal that most of the images were taken on Tuesdays, and the most frequent capture time throughout the week was 12:30PM.

UCCS photos taken in 2012

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Year	Month	Day	Date	Time Range	Photos
2012	Februay	---	23	-	Feb 23, 2012	132
2012	March	---	6	-	-	March 6, 2012	288
2012	March	---	8	-	-	March 8, 2012	506
2012	March	---	13	-	-	March 13, 2012	160
2012	Februay	---	23	-	132	March 20, 2012	1,840
2012	March	---	6	-	-	March 22, 2012	445
2012	March	---	8	-	-	April 3, 2012	1,639
2012	March	---	13	-	-	April 12, 2012	14
2012	Februay	---	23	-	132	April 17, 2012	19
2012	March	---	6	-	-	April 24, 2012	63
2012	March	---	8	-	-	April 25, 2012	11
2012	March	---	13	-	-	April 26, 2012	20
2012	Februay	---	23	-	132

UCCS photos taken in 2013

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Date	Photos
2012	March	---	6	-	-	Jan 28, 2013	1,056
2012	March	---	8	-	-	Jan 29, 2013	1,561
2012	March	---	13	-	-	Feb 13, 2013	739
2012	Februay	---	23	-	132	Feb 19, 2013	723
2012	March	---	6	-	-	Feb 20, 2013	965
2012	March	---	8	-	-	Feb 26, 2013	736

2012-03-20 -2012-03-22 -2012-04-03 -2012-04-12 -2012-04-17 -2012-04-24 -2012-04-25 -2012-04-26 -2013-01-28 -2013-01-29 -2013-02-13 -2013-02-19 -2013-02-20 -2013-02-26

The pixel-average of all Uconstrained College Students images is shown with all 51,838 face annotations. (c) Adam Harvey

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Biometric Trade Routes

- -

- To help understand how UCCS has been used around the world for commercial, military and academic research; publicly available research citing UnConstrained College Students Dataset is collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location. -

- -

Academic
Commercial
Military / Government
Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.

- -

Who used UCCS?

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- This bar chart presents a ranking of the top countries where dataset citations originated. Mouse over individual columns to see yearly totals. These charts show at most the top 10 countries. -

- -

Dataset Citations

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Supplementary Information

- -

The original Sapkota and Boult dataset, from which UCCS is derived, received funding from¹:

Location

The location of the camera and subjects can confirmed using the Bellingcat method. The visual clues that lead to location of the camera and subjects include the unique pattern of the sidewalk that is only used on the UCCS Pedestrian Spine near the West Lawn, the two UCCS sign poles with matching graphics still visible in Google Street View, the no parking sign and directionality of its arrow, the back of street sign next to it, the slight bend in the sidewalk, the presence of cars passing in the background of the image, and the far wall of the parking garage all match images in the dataset. The original papers also provides another clue: a picture of the camera inside the office that was used to create the dataset. The window view in this image provides another match for the brick pattern on the north facade of the Kraember Family Library and the green metal fence along the sidewalk. View the location on Google Maps

Location on campus where students were unknowingly photographed with a telephoto lens to be used for defense and intelligence agency funded research on face recognition. Image: Google Maps

3D view showing the angle of view of the surveillance camera used for UCCS dataset. Image: Google Maps

Funding

The UnConstrained College Students dataset is associated with two main research papers: "Large Scale Unconstrained Open Set Face Database" and "Unconstrained Face Detection and Open-Set Face Recognition Challenge". Collectively, these papers and the creation of the dataset have received funding from the following organizations:

ONR (Office of Naval Research) MURI (The Department of Defense Multidisciplinary University Research Initiative) grant N00014-08-1-0638
Army SBIR (Small Business Innovation Research) grant W15P7T-12-C-A210
SOCOM (Special Operations Command) SBIR (Small Business Innovation Research) grant H92222-07-P-0020

The more recent UCCS version of the dataset received funding from ²:

National Science Foundation Grant IIS-1320956
ODNI (Office of Director of National Intelligence)
IARPA (Intelligence Advance Research Projects Activity) R&D contract 2014-14071600012

TODO

Opting Out

If you attended University of Colorado Colorado Springs and were captured by the long range surveillance camera used to create this dataset, there is unfortunately currently no way to be removed. The authors do not provide any options for students to opt-out nor were students informed they would be used for training face recognition. According to the authors, the lack of any consent or knowledge of participation is what provides part of the value of Unconstrained College Students Dataset.

Ethics

Please direct any questions about the ethics of the dataset to the University of Colorado Colorado Springs Ethics and Compliance Office

Technical Details

For further technical information about the dataset, visit the UCCS dataset project page.

Under Development

add tabulator module for dates
parse dates into CSV using Python
get google image showing line of sight?
fix up quote/citations
adding more verified locations to map and charts
add EXIF file to CDN

footnotes

Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013.↩
Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3.↩

a
Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013.
+
a b
Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3.
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Biometric Trade Routes

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- To help understand how VIPeR has been used around the world for commercial, military and academic research; publicly available research citing Viewpoint Invariant Pedestrian Recognition is collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal reserach projects at that location. + To help understand how VIPeR has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Viewpoint Invariant Pedestrian Recognition was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal research projects at that location.

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Academic

Commercial

Military / Government

Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.

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Supplementary Information

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Dataset Citations

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MegaPixels.cc - Disclaimer - Terms of Use - Privacy + Datasets About - Team + Press + Legal and Privacy

MegaPixels ©2017-19 Adam R. Harvey / diff --git a/site/public/datasets/youtube_celebrities/index.html b/site/public/datasets/youtube_celebrities/index.html index ee11f3c0..b19add4e 100644 --- a/site/public/datasets/youtube_celebrities/index.html +++ b/site/public/datasets/youtube_celebrities/index.html @@ -26,18 +26,68 @@

YouTube Celebrities

Years

TBD

Images

TBD

Identities

TBD

Origin

YouTube.com

Funded by

CIA, US Army

TODO

RESEARCH below these lines

Selected dataset sequences: (a) MBGC, (b) CMU MoBo, (c) First -Honda/UCSD, and (d) YouTube Celebrities. -This research is supported by the Central Intelligence Agency, the Biometrics +
YouTube Celebrities
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[ page under development ]
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Who used YouTube Celebrities?
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+ This bar chart presents a ranking of the top countries where dataset citations originated. Mouse over individual columns to see yearly totals. These charts show at most the top 10 countries. +
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Biometric Trade Routes
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+ To help understand how YouTube Celebrities has been used around the world by commercial, military, and academic organizations; existing publicly available research citing YouTube Celebrities was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal research projects at that location. +
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Academic
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Commercial
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Military / Government
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Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
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Dataset Citations
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+ The dataset citations used in the visualizations were collected from Semantic Scholar, a website which aggregates and indexes research papers. Each citation was geocoded using names of institutions found in the PDF front matter, or as listed on other resources. These papers have been manually verified to show that researchers downloaded and used the dataset to train or test machine learning algorithms. +
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Notes...
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Selected dataset sequences: (a) MBGC, (b) CMU MoBo, (c) First +Honda/UCSD, and (d) YouTube Celebrities.
+
This research is supported by the Central Intelligence Agency, the Biometrics Task Force and the Technical Support Working Group through US Army contract W91CRB-08-C-0093. The opinions, (cid:12)ndings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily re(cid:13)ect -the views of our sponsors.
-

in "Face Recognition From Video Draft 17"
International Journal of Pattern Recognition and Artifcial Intelligence WorldScientific Publishing Company

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Posted

Dec. 15

Author

Adam Harvey

Motivation

Posted

Dec. 15

Author

Adam Harvey

Facial recognition is a scam.

During the last 20 years commericial, academic, and governmental agencies have promoted the false dream of a future with face recognition. This essay debunks the popular myth that such a thing ever existed.

There is no such thing as face recognition. For the last 20 years, government agencies, commercial organizations, and academic institutions have played the public as a fool, selling a roadmap of the future that simply does not exist. Facial recognition, as it is currently defined, promoted, and sold to the public, government, and commercial sector is a scam.

Committed to developing robust solutions with superhuman accuracy, the industry has repeatedly undermined itself by never actually developing anything close to "face recognition".

There is only biased feature vector clustering and probabilistic thresholding.

Motivation

Ever since government agencies began developing face recognition in the early 1960's, datasets of face images have always been central to developing and validating face recognition technologies. Today, these datasets no longer originate in labs, but instead from family photo albums posted on photo sharing sites, surveillance camera footage from college campuses, search engine queries for celebrities, cafe livestreams, or videos on YouTube.

During the last year, hundreds of these facial analysis datasets created "in the wild" have been collected to understand how they contribute to a global supply chain of biometric data that is powering the global facial recognition industry.

While many of these datasets include public figures such as politicians, athletes, and actors; they also include many non-public figures: digital activists, students, pedestrians, and semi-private shared photo albums are all considered "in the wild" and fair game for research projects. Some images are used with creative commons licenses, yet others were taken in unconstrained scenarios without awareness or consent. At first glance it appears many of the datasets were created for seemingly harmless academic research, but when examined further it becomes clear that they're also used by foreign defense agencies.

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Col1	Col2	Col3
Content1	Content2	Content3

Team

Contributing Researchers

Code and Libraries

Dataset Citations

Funding

Dataset Title TBD

Supplementary Information

Dataset Citations

Research Notes

Location

Funding

TODO

Opting Out

Ethics

Technical Details

Under Development

footnotes