From b3bfb2f6f34f5065658e4c0ef289791ab24e5ae2 Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Tue, 16 Apr 2019 17:24:25 +0200 Subject: wide sidebar --- site/assets/css/css.css | 3 ++- site/content/pages/datasets/uccs/index.md | 10 +++------- site/public/datasets/lfw/index.html | 2 +- site/public/datasets/uccs/index.html | 31 ++++++++++++++++--------------- 4 files changed, 22 insertions(+), 24 deletions(-) (limited to 'site') diff --git a/site/assets/css/css.css b/site/assets/css/css.css index 1c7b8859..774f34f8 100644 --- a/site/assets/css/css.css +++ b/site/assets/css/css.css @@ -318,7 +318,8 @@ p.subp{ .right-sidebar { float: right; width: 240px; - margin: 75px 20px 20px 20px; + margin: 0px 20px 20px 20px; + padding-top: 12px; padding-left: 20px; border-left: 1px solid #333; font-family: 'Roboto'; diff --git a/site/content/pages/datasets/uccs/index.md b/site/content/pages/datasets/uccs/index.md index 767f8220..67c53893 100644 --- a/site/content/pages/datasets/uccs/index.md +++ b/site/content/pages/datasets/uccs/index.md @@ -15,18 +15,16 @@ authors: Adam Harvey ------------ +## UnConstrained College Students + ### sidebar ### end sidebar -## UnConstrained College Students - 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, over 1,700 students and pedestrians were "photographed using a long-range high-resolution surveillance camera without their knowledge" [^funding_uccs]. In this investigation, we examine the funding sources, contents of the dataset, photo EXIF data, and publicy available research project citations. According to the author's of the the UnConstrained College Students dataset it is primarliy used for research and development of "face detection and recognition research towards surveillance applications that are becoming more popular and more required nowadays, and where no automatic recognition algorithm has proven to be useful yet." Applications of this technology include usage by defense and intelligence agencies, who were also the primary funding sources of the UCCS dataset. - - -In the two papers associated with the release of the UCCS datasaet ([Unconstrained Face Detection and Open-Set Face Recognition Challenge](https://www.semanticscholar.org/paper/Unconstrained-Face-Detection-and-Open-Set-Face-G%C3%BCnther-Hu/d4f1eb008eb80595bcfdac368e23ae9754e1e745) and [Large Scale Unconstrained Open Set Face Database](https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1)), the researchers disclosed their funding sources as ODNI (United States 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. Further, UCCS's VAST site explicity [states](https://vast.uccs.edu/project/iarpa-janus/) they are part of the [IARPA Janus](https://www.iarpa.gov/index.php/research-programs/janus), a face recognition project developed to serve the needs of national intelligence interests. +In the two papers associated with the release of the UCCS dataset ([Unconstrained Face Detection and Open-Set Face Recognition Challenge](https://www.semanticscholar.org/paper/Unconstrained-Face-Detection-and-Open-Set-Face-G%C3%BCnther-Hu/d4f1eb008eb80595bcfdac368e23ae9754e1e745) and [Large Scale Unconstrained Open Set Face Database](https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1)), the researchers disclosed their funding sources as ODNI (United States 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. Further, UCCS's VAST site explicity [states](https://vast.uccs.edu/project/iarpa-janus/) they are part of the [IARPA Janus](https://www.iarpa.gov/index.php/research-programs/janus), a face recognition project developed to serve the needs of national intelligence interests. ![caption: 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](assets/uccs_map_aerial.jpg) @@ -122,8 +120,6 @@ If you attended University of Colorado Colorado Springs and were captured by the {% include 'cite_our_work.html' %} -{% include 'last_updated.html' %} - ### Footnotes [^funding_sb]: Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013. diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html index 2d91b065..60a6bf0e 100644 --- a/site/public/datasets/lfw/index.html +++ b/site/public/datasets/lfw/index.html @@ -27,7 +27,7 @@
Labeled Faces in The Wild (LFW) is the first facial recognition dataset created entirely from online photos
It includes 13,456 images of 4,432 people's images copied from the Internet during 2002-2004 and is the most frequently used dataset in the world for benchmarking face recognition algorithms. -

Location

The location of the camera and subjects can confirmed using several visual cues in the dataset images: 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
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
3D view showing the angle of view of the surveillance camera used for UCCS dataset. Image: Google Maps

Funding

+
 3D view showing the angle of view of the surveillance camera used for UCCS dataset. 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
  • @@ -250,8 +250,9 @@ }

    -

References

  • a

    Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013.

    -
  • ab

    Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3.

    +

References

  • Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013.

    +
  • a

    Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3.

    +
  • a

    "Surveillance Face Recognition Challenge". SemanticScholar

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