From 07dd05f733c8618ea8dc687f7a48a7add6f5a83b Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Mon, 1 Apr 2019 14:42:20 +0200 Subject: fix --- site/public/datasets/uccs/index.html | 52 +++++++++++++++++------------------- 1 file changed, 25 insertions(+), 27 deletions(-) (limited to 'site/public/datasets/uccs/index.html') diff --git a/site/public/datasets/uccs/index.html b/site/public/datasets/uccs/index.html index ca106022..2477c9f8 100644 --- a/site/public/datasets/uccs/index.html +++ b/site/public/datasets/uccs/index.html @@ -4,7 +4,7 @@ MegaPixels - + @@ -26,12 +26,12 @@
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Unconstrained College Students (UCCS) is a dataset of images ...
The UCCS dataset includes ... -
Collected
TBD
Published
TBD
Images
TBD
Faces
TBD

Unconstrained College Students ...

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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 +
Published
2018
Images
16,149
Identities
1,732
Used for
Face recognition, face detection
Created by
Unviversity of Colorado Colorado Springs (US)
Funded by
ODNI, IARPA, ONR MURI, Amry SBIR, SOCOM SBIR

Unconstrained College Students ...

(PAGE UNDER DEVELOPMENT)

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

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Biometric Trade Routes

- To understand how UCCS has been used around the world... - affected global research on computer vision, surveillance, defense, and consumer technology, the and where this dataset has been used the locations of each organization that used or referenced the datast + 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.

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  • Academic
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  • Government / Military
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  • Commercial
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  • Military / Government
  • Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
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Who used UCCS?

- This bar chart presents a ranking of the top countries where citations originated. Mouse over individual columns - to see yearly totals. These charts show at most the top 10 countries. + 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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- These pie charts show overall totals based on country and institution type. -

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Supplementary Information

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Supplementary Information

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Citations

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Dataset Citations

- Citations were collected from Semantic Scholar, a website which aggregates - and indexes research papers. The citations were 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. + 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.

Add [button/link] to download CSV. Add search input field to filter.

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Bounding box visualization
Bounding box visualization

Research Notes

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Research Notes

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

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" In most face detection/recognition datasets, the majority of images are “posed”, i.e. the subjects know they are being photographed, and/or the images are selected for publication in public media. Hence, blurry, occluded and badly illuminated images are generally uncommon in these datasets. In addition, most of these challenges are close-set, i.e. the list of subjects in the gallery is the same as the one used for testing.

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This challenge explores more unconstrained data, by introducing the new UnConstrained College Students (UCCS) dataset, where subjects are photographed using a long-range high-resolution surveillance camera without their knowledge. Faces inside these images are of various poses, and varied levels of blurriness and occlusion. The challenge also creates an open set recognition problem, where unknown people will be seen during testing and must be rejected.

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With this challenge, we hope to foster 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.

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UnConstrained College Students (UCCS) Dataset

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The UCCS dataset was collected over several months using Canon 7D camera fitted with Sigma 800mm F5.6 EX APO DG HSM lens, taking images at one frame per second, during times when many students were walking on the sidewalk. "

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

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