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<section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span class="dataset-name">Unconstrained College Students (UCCS)</span> is a dataset of long-range surveillance photos of students at University of Colorado</span></div><div class='hero_subdesc'><span class='bgpad'>The UCCS dataset includes 16,149 images and 1,732 identities of subjects on University of Colorado Colorado Springs campus and is used for face recognition and face detection
</span></div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Published</div><div>2018</div></div><div><div class='gray'>Images</div><div>16,149</div></div><div><div class='gray'>Identities</div><div>1,732</div></div><div><div class='gray'>Used for</div><div>Face recognition, face detection</div></div><div><div class='gray'>Created by</div><div>Unviversity of Colorado Colorado Springs (US)</div></div><div><div class='gray'>Funded by</div><div>ODNI, IARPA, ONR MURI, Amry SBIR, SOCOM SBIR</div></div><div><div class='gray'>Website</div><div><a href="https://vast.uccs.edu/Opensetface/">vast.uccs.edu</a></div></div></div></div><h2>Unconstrained College Students (UCCS)</h2>
<p>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" <a class="footnote_shim" name="[^funding_uccs]_1"> </a><a href="#[^funding_uccs]" class="footnote" title="Footnote 2">2</a>. The images were captured using a Canon 7D digital camera fitted with a Sigma 800mm telephoto lens pointed out the window of an office aimed at students walking to and from classes.</p>
<p>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. <a class="footnote_shim" name="[^funding_sb]_1"> </a><a href="#[^funding_sb]" class="footnote" title="Footnote 1">1</a> <a class="footnote_shim" name="[^funding_uccs]_2"> </a><a href="#[^funding_uccs]" class="footnote" title="Footnote 2">2</a></p>
<p>The images in UCCS were taken on 19 non-consecutive days during 2012 - 2013 and include a variety of weather and clothing variation. The embedded <a href="assets/uccs_camera_exif.csv">EXIF data</a> in the images reveals that the images were taken on the following dates:</p>
</section><section><div class='columns columns-2'><div class='column'><h4>UCCS photos taken in 2012</h4>
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<th>Date</th>
<th>Photos</th>
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<td>Feb 23, 2014</td>
<td>132</td>
</tr>
<tr>
<td>March 6, 2014</td>
<td>-</td>
</tr>
<tr>
<td>March 8, 2014</td>
<td>-</td>
</tr>
</tbody>
</table>
</div><div class='column'><h4>UCCS photos taken in 2013</h4>
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<thead><tr>
<th>Date</th>
<th>Photos</th>
</tr>
</thead>
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<td>Feb 23, 2014</td>
<td>132</td>
</tr>
<tr>
<td>March 6, 2014</td>
<td>-</td>
</tr>
<tr>
<td>March 8, 2014</td>
<td>-</td>
</tr>
</tbody>
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</div></div></section><section>
<h3>Biometric Trade Routes</h3>
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<p>
To help understand how UCCS has been used around the world by commercial, military and academic organizations; 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 research projects at that location.
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<li class="edu">Academic</li>
<li class="com">Commercial</li>
<li class="gov">Military / Government</li>
</ul>
<div class="source">Citation data is collected using <a href="https://semanticscholar.org" target="_blank">SemanticScholar.org</a> then dataset usage verified and geolocated.</div >
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[section under development] UCCS ... Standardized paragraph of text about the map. Sed ut perspiciatis, unde omnis iste natus error sit voluptatem accusantium doloremque laudantium, totam rem aperiam eaque ipsa, quae ab illo inventore veritatis et quasi architecto beatae vitae dicta sunt, explicabo.
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<h3>Who used UCCS?</h3>
<p>
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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</section>
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<!-- <div style="position: absolute;top: 0px;right: -55px;width: 180px;font-size: 14px;">Labeled Faces in the Wild Dataset<br><span class="numc" style="font-size: 11px;">20 citations</span>
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<h3>Dataset Citations</h3>
<p>
The dataset citations used in the visualizations were collected from <a href="https://www.semanticscholar.org">Semantic Scholar</a>, 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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</section><section><h2>Opting Out</h2>
<p>If you attended University of Colorado Colorado Springs and were captured by the long range surveillance camera used to create this dataset, there is unfortunatley no way to be removed. The authors do not provide any option for students to opt-out nor were any students informed they would be used for training face recognition. According to the authors, the lack of any consent is what provides part of the value of the Unconstrained College Students Dataset.</p>
<p>More information and contact emails are provided on the UCCS dataset site: <a href="https://vast.uccs.edu/Opensetface/">https://vast.uccs.edu/Opensetface/</a></p>
</section><section>
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<h3>Supplementary Information</h3>
</section><section><h4>Data Visualizations</h4>
</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_mean_bboxes_comp.jpg' alt=' The pixel-average of all Uconstrained College Students images is shown with all 51,838 face annotations. (c) Adam Harvey'><div class='caption'> The pixel-average of all Uconstrained College Students images is shown with all 51,838 face annotations. (c) Adam Harvey</div></div></section><section><h4>Funding</h4>
<p>As mentioned above, 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". Collective these papers, and the creation of the dataset have received funding from the following organizations:</p>
<ul>
<li>ONR (Office of Naval Research) MURI (The Department of Defense Multidisciplinary University Research Initiative) grant N00014-08-1-0638</li>
<li>Army SBIR (Small Business Innovation Research) grant W15P7T-12-C-A210</li>
<li>SOCOM (Special Operations Command) SBIR (Small Business Innovation Research) grant H92222-07-P-0020</li>
<li>National Science Foundation Grant IIS-1320956</li>
<li>ODNI (Office of Director of National Intelligence)</li>
<li>IARPA (Intelligence Advance Research Projects Activity) R&D contract 2014-14071600012</li>
</ul>
<h4>TODO</h4>
<ul>
<li>parse dates into CSV using Python</li>
<li>get google image showing line of sight?</li>
</ul>
</section><section><ul class="footnotes"><li><a name="[^funding_sb]" class="footnote_shim"></a><span class="backlinks"><a href="#[^funding_sb]_1">a</a></span><p>Sapkota, Archana and Boult, Terrance. "Large Scale Unconstrained Open Set Face Database." 2013.</p>
</li><li><a name="[^funding_uccs]" class="footnote_shim"></a><span class="backlinks"><a href="#[^funding_uccs]_1">a</a><a href="#[^funding_uccs]_2">b</a></span><p>Günther, M. et. al. "Unconstrained Face Detection and Open-Set Face Recognition Challenge," 2018. Arxiv 1708.02337v3.</p>
</li></ul></section>
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