From f5141a7b48ee569089b07428bc75cb84a55c4834 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Tue, 28 May 2019 14:49:58 +0200 Subject: update press, fix uccs license --- site/public/datasets/uccs/index.html | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) (limited to 'site/public/datasets') diff --git a/site/public/datasets/uccs/index.html b/site/public/datasets/uccs/index.html index 5044af2a..9b366c8a 100644 --- a/site/public/datasets/uccs/index.html +++ b/site/public/datasets/uccs/index.html @@ -77,8 +77,8 @@

The UCCS dataset includes over 1,700 unique identities, most of which are students walking to and from class. As of 2018, it was the "largest surveillance [face recognition] benchmark in the public domain." 4 The photos were taken during the spring semesters of 2012 – 2013 on the West Lawn of the University of Colorado Colorado Springs campus. The photographs were timed to capture students during breaks between their scheduled classes in the morning and afternoon during Monday through Thursday. "For example, a student taking Monday-Wednesday classes at 12:30 PM will show up in the camera on almost every Monday and Wednesday." 2.

The location at University of Colorado Colorado Springs where students were surreptitiously photographed with a long-range surveillance camera for use in a defense and intelligence agency funded research project on face recognition. Image: Google Maps
The location at University of Colorado Colorado Springs where students were surreptitiously photographed with a long-range surveillance camera for use in a defense and intelligence agency funded research project on face recognition. Image: Google Maps

The long-range surveillance images in the UnConsrained College Students dataset were taken using a Canon 7D 18-megapixel digital camera fitted with a Sigma 800mm F5.6 EX APO DG HSM telephoto lens and pointed out an office window across the university's West Lawn. The students were photographed from a distance of approximately 150 meters through an office window. "The camera [was] programmed to start capturing images at specific time intervals between classes to maximize the number of faces being captured." 2 Their setup made it impossible for students to know they were being photographed, providing the researchers with realistic surveillance images to help build face recognition systems for real world applications for defense, intelligence, and commercial partners.

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Example images from the UnConstrained College Students Dataset.
Example images from the UnConstrained College Students Dataset.

The EXIF data embedded in the images shows that the photo capture times follow a similar pattern to that outlined by the researchers, but also highlights that the vast majority of photos (over 7,000) were taken on Tuesdays around noon during students' lunch break. The lack of any photos taken between Friday through Sunday shows that the researchers were only interested in capturing images of students during the peak campus hours.

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UCCS photos captured per weekday © megapixels.cc
UCCS photos captured per weekday © megapixels.cc
UCCS photos captured per weekday © megapixels.cc
UCCS photos captured per weekday © megapixels.cc

The two research papers associated with the release of the UCCS dataset (Unconstrained Face Detection and Open-Set Face Recognition Challenge and Large Scale Unconstrained Open Set Face Database), acknowledge that the primary funding sources for their work were United States defense and intelligence agencies. Specifically, development of the UnContsrianed College Students dataset was funded by the Intelligence Advanced Research Projects Activity (IARPA), Office of Director of National Intelligence (ODNI), Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative (ONR MURI), and the Special Operations Command and Small Business Innovation Research (SOCOM SBIR) amongst others. UCCS's VAST site also explicitly states their involvement in the IARPA Janus face recognition project developed to serve the needs of national intelligence, establishing that immediate benefactors of this dataset include United States defense and intelligence agencies, but it would go on to benefit other similar organizations.

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Example images from the UnConstrained College Students Dataset. Photos from UnConstrained College Students dataset, made available under a modified ODC Attribution License http://www.vast.uccs.edu/UCCS/License.txt
Example images from the UnConstrained College Students Dataset. Photos from UnConstrained College Students dataset, made available under a modified ODC Attribution License http://www.vast.uccs.edu/UCCS/License.txt

The EXIF data embedded in the images shows that the photo capture times follow a similar pattern to that outlined by the researchers, but also highlights that the vast majority of photos (over 7,000) were taken on Tuesdays around noon during students' lunch break. The lack of any photos taken between Friday through Sunday shows that the researchers were only interested in capturing images of students during the peak campus hours.

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UCCS photos captured per weekday. Contains information from UCCS: UnConstrained College Students dataset, made available under a modified ODC Attribution License http://www.vast.uccs.edu/UCCS/License.txt
UCCS photos captured per weekday. Contains information from UCCS: UnConstrained College Students dataset, made available under a modified ODC Attribution License http://www.vast.uccs.edu/UCCS/License.txt
UCCS photos captured per weekday. Contains information from UCCS: UnConstrained College Students dataset, made available under a modified ODC Attribution License
UCCS photos captured per weekday. Contains information from UCCS: UnConstrained College Students dataset, made available under a modified ODC Attribution License

The two research papers associated with the release of the UCCS dataset (Unconstrained Face Detection and Open-Set Face Recognition Challenge and Large Scale Unconstrained Open Set Face Database), acknowledge that the primary funding sources for their work were United States defense and intelligence agencies. Specifically, development of the UnContsrianed College Students dataset was funded by the Intelligence Advanced Research Projects Activity (IARPA), Office of Director of National Intelligence (ODNI), Office of Naval Research and The Department of Defense Multidisciplinary University Research Initiative (ONR MURI), and the Special Operations Command and Small Business Innovation Research (SOCOM SBIR) amongst others. UCCS's VAST site also explicitly states their involvement in the IARPA Janus face recognition project developed to serve the needs of national intelligence, establishing that immediate benefactors of this dataset include United States defense and intelligence agencies, but it would go on to benefit other similar organizations.

In 2017, one year after its public release, the UCCS face dataset formed the basis for a defense and intelligence agency funded face recognition challenge project at the International Joint Biometrics Conference in Denver, CO. And in 2018 the dataset was again used for the 2nd Unconstrained Face Detection and Open Set Recognition Challenge at the European Computer Vision Conference (ECCV) in Munich, Germany.

As of April 15, 2019, the UCCS dataset is no longer available for public download. But during the three years it was publicly available (2016-2019) the UCCS dataset appeared in at least 6 publicly available research papers including verified usage from Beihang University who is known to provide research and development for China's military; and Vision Semantics Ltd who lists the UK Ministry of Defence as a project partner.

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Supplementary Information

Since this site To show the types of face images used in the UCCS student dataset while protecting their individual privacy, a generative adversarial network was used to interpolate between identities in the dataset. The image below shows a generative adversarial network trained on the UCCS face bounding box areas from 16,000 images and over 90,000 face regions.

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GAN generated approximations of students in the UCCS dataset. © megapixels.cc 2018
GAN generated approximations of students in the UCCS dataset. © megapixels.cc 2018

UCCS photos taken in 2012

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GAN generated approximations of students in the UCCS dataset. © megapixels.cc 2018. Based on the UnConstrained College Students dataset, made available under a modified ODC Attribution License
GAN generated approximations of students in the UCCS dataset. © megapixels.cc 2018. Based on the UnConstrained College Students dataset, made available under a modified ODC Attribution License

UCCS photos taken in 2012

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Ethics

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Credits

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This analysis contains information from UCCS: UnConstrained College Students dataset, made available under a modified ODC Attribution License http://www.vast.uccs.edu/UCCS/License.txt

Cite Our Work

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