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<meta name="author" content="Adam Harvey" />
<meta name="description" content="Oxford Town Centre is a dataset of surveillance camera footage from Cornmarket St Oxford, England" />
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<div class='site_name'>MegaPixels</div>
<div class='splash'>TownCentre</div>
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<section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/oxford_town_centre/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'>Oxford Town Centre is a dataset of surveillance camera footage from Cornmarket St Oxford, England</span></div><div class='hero_subdesc'><span class='bgpad'>The Oxford Town Centre dataset includes approximately 2,200 identities and is used for research and development of face recognition systems
</span></div></div></section><section><div class='left-sidebar'><div class='meta'>
<div class='gray'>Published</div>
<div>2011</div>
</div><div class='meta'>
<div class='gray'>Videos</div>
<div>1 </div>
</div><div class='meta'>
<div class='gray'>Purpose</div>
<div>Person detection, gaze estimation</div>
</div><div class='meta'>
<div class='gray'>Funded by</div>
<div>EU FP6 Hermes project and Oxford Risk </div>
</div><div class='meta'>
<div class='gray'>Download Size</div>
<div>0.118 GB</div>
</div><div class='meta'>
<div class='gray'>Website</div>
<div><a href='http://www.robots.ox.ac.uk/ActiveVision/Research/Projects/2009bbenfold_headpose/project.html' target='_blank' rel='nofollow noopener'>ox.ac.uk</a></div>
</div></div><h2>Oxford Town Centre</h2>
<p>[ page under development ]</p>
<p>The Oxford Town Centre dataset is a video of pedestrians in a busy downtown area in Oxford used for creating surveillance algorithms with potential applications in remote biometric analysis and non-cooperative face recognition.<a class="footnote_shim" name="[^ben_benfold_orig]_1"> </a><a href="#[^ben_benfold_orig]" class="footnote" title="Footnote 1">1</a> The dataset was originally created to build algorithms that improve the stability of pedestrian detectors to provide more accurate head location estimates, leading to more accurate face recognition.</p>
<p>Oxford Town Centre dataset is unique in that it uses footage from a public CCTV camera that is designated for public safety. Since its publication in 2009, the Oxford Town Centre CCTV footage dataset, and all 2,200 people in the video, have been redistributed around the world for the purpose of surveillance research and development. There are over 80 verified research projects that have used the Oxford Town Centre dataset. The usage even extends to commercial organizations including Amazon, Disney, and OSRAM.</p>
</section><section>
<h3>Who used TownCentre?</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.
</p>
</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>Biometric Trade Routes</h3>
<p>
To help understand how TownCentre has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Oxford Town Centre 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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<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 class="applet_container">
<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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<h2>Supplementary Information</h2>
</section><section><h3>Location</h3>
<p>The street location of the camera used for the Oxford Town Centre dataset can be easily confirmed using only two visual clues in video: the GAP store and the main road <a href="https://www.google.com/maps/@51.7528162,-1.2581152,3a,50.3y,310.59h,87.23t/data=!3m7!1e1!3m5!1s3FsGN-PqYC-VhQGjWgmBdQ!2e0!5s20120601T000000!7i13312!8i6656">source</a>. The camera angle and field of view indicate that the camera was elevated and placed at the corner. The edge of the building is visible and there is a small white nylon strap and pigeon deterrent spikes visible on the upper perimeter of the building. The field of view indicates the camera uses a wide angle lens. Combined with the camera's stability and pigeon appearances in front of the camera at 1:24 and 3:29, these visual cues indicate that the camera was mounted outside on the corner of the building just above the deterrence spikes.</p>
</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/oxford_town_centre/assets/oxford_town_centre_cctv.jpg' alt=' Footage from this public CCTV camera was used to create the Oxford Town Centre dataset. Image sources: Google Street View and Oxford Town Centre dataset'><div class='caption'> Footage from this public CCTV camera was used to create the Oxford Town Centre dataset. Image sources: Google Street View and Oxford Town Centre dataset</div></div></section><section><h3>Demo Videos Using Oxford Town Centre Dataset</h3>
<p>Several researchers have posted their demo videos using the Oxford Town Centre dataset on YouTube:</p>
<ul>
<li><a href="https://www.youtube.com/watch?v=nO-3EM9dEd4">Multi target tracking on Oxford Dataset</a></li>
<li>[Multi-pedestrian tracking (TownCentre dataset)]<a href="https://www.youtube.com/watch?v=nO-3EM9dEd4">https://www.youtube.com/watch?v=nO-3EM9dEd4</a></li>
<li><a href="https://www.youtube.com/watch?v=SKXk6uB8348">Multiple object tracking with kalman tracker and sort</a></li>
<li><a href="https://www.youtube.com/watch?v=RM_RdXH7pSY">Multi target tracking on Oxford dataset</a></li>
<li><a href="https://www.youtube.com/watch?v=ErLtfUAJA8U">towncentre</a></li>
<li><a href="https://www.youtube.com/watch?v=LwMOmqvhnoc">VTD - towncenter.avi</a></li>
</ul>
<p>TODO</p>
<ul>
<li>make heatmap viz</li>
<li>add license info</li>
</ul>
</section><section><ul class="footnotes"><li><a name="[^ben_benfold_orig]" class="footnote_shim"></a><span class="backlinks"><a href="#[^ben_benfold_orig]_1">a</a></span><p>Benfold, Ben and Reid, Ian. "Stable Multi-Target Tracking in Real-Time Surveillance Video". CVPR 2011. Pages 3457-3464.</p>
</li><li><a name="[^guiding_surveillance]" class="footnote_shim"></a><span class="backlinks"></span><p>"Guiding Visual Surveillance by Tracking Human Attention". 2009.</p>
</li></ul></section>
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