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diff --git a/site/public/datasets/duke_mtmc/index.html b/site/public/datasets/duke_mtmc/index.html index 431cf7ff..9664181e 100644 --- a/site/public/datasets/duke_mtmc/index.html +++ b/site/public/datasets/duke_mtmc/index.html @@ -4,7 +4,7 @@ <title>MegaPixels</title> <meta charset="utf-8" /> <meta name="author" content="Adam Harvey" /> - <meta name="description" content="Duke MTMC is a dataset of CCTV footage of students at Duke University" /> + <meta name="description" content="Duke MTMC is a dataset of surveillance camera footage of students on Duke University campus" /> <meta name="referrer" content="no-referrer" /> <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" /> <link rel='stylesheet' href='/assets/css/fonts.css' /> @@ -26,12 +26,17 @@ </header> <div class="content content-dataset"> - <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span class="dataset-name">Duke MTMC</span> is a dataset of CCTV footage of students at Duke University</span></div><div class='hero_subdesc'><span class='bgpad'>Duke MTMC contains over 2 million video frames and 2,000 unique identities collected from 8 cameras at Duke University campus in March 2014 -</span></div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Collected</div><div>March 19, 2014</div></div><div><div class='gray'>Cameras</div><div>8</div></div><div><div class='gray'>Video Frames</div><div>2,000,000</div></div><div><div class='gray'>Identities</div><div>Over 2,000</div></div><div><div class='gray'>Used for</div><div>Person re-identification, <br>face recognition</div></div><div><div class='gray'>Sector</div><div>Academic</div></div><div><div class='gray'>Website</div><div><a href="http://vision.cs.duke.edu/DukeMTMC/">duke.edu</a></div></div></div></div><h2>Duke Multi-Target, Multi-Camera Tracking Dataset (Duke MTMC)</h2> -<p>(PAGE UNDER DEVELOPMENT)</p> + <section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'><span class="dataset-name">Duke MTMC</span> is a dataset of surveillance camera footage of students on Duke University campus</span></div><div class='hero_subdesc'><span class='bgpad'>Duke MTMC contains over 2 million video frames and 2,000 unique identities collected from 8 HD cameras at Duke University campus in March 2014 +</span></div></div></section><section><div class='left-sidebar'><div class='meta'><div><div class='gray'>Created</div><div>2014</div></div><div><div class='gray'>Identities</div><div>Over 2,700</div></div><div><div class='gray'>Used for</div><div>Face recognition, person re-identification</div></div><div><div class='gray'>Created by</div><div>Computer Science Department, Duke University, Durham, US</div></div><div><div class='gray'>Website</div><div><a href="http://vision.cs.duke.edu/DukeMTMC/">duke.edu</a></div></div></div></div><h2>Duke Multi-Target, Multi-Camera Tracking Dataset (Duke MTMC)</h2> +<p>[ PAGE UNDER DEVELOPMENT ]</p> +<p>Duke MTMC is a dataset of video recorded on Duke University campus during for the purpose of training, evaluating, and improving <em>multi-target multi-camera tracking</em>. The videos were recorded during February and March 2014 and cinclude</p> +<p>Includes a total of 888.8 minutes of video (ind. verified)</p> +<p>"We make available a new data set that has more than 2 million frames and more than 2,700 identities. It consists of 8×85 minutes of 1080p video recorded at 60 frames per second from 8 static cameras deployed on the Duke University campus during periods between lectures, when pedestrian traffic is heavy."</p> +<p>The dataset includes approximately 2,000 annotated identities appearing in 85 hours of video from 8 cameras located throughout Duke University's campus.</p> +</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_cam5_average_comp.jpg' alt=' Duke MTMC pixel-averaged image of camera #5 is shown with the bounding boxes for each student drawn in white. (c) Adam Harvey'><div class='caption'> Duke MTMC pixel-averaged image of camera #5 is shown with the bounding boxes for each student drawn in white. (c) Adam Harvey</div></div></section><section><p>According to the dataset authors,</p> </section><section> - <h3>Information Supply Chain</h3> + <h3>Biometric Trade Routes</h3> <!-- <div class="map-sidebar right-sidebar"> <h3>Legend</h3> @@ -43,35 +48,35 @@ </div> --> <p> - To understand how Duke MTMC Dataset 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 Duke MTMC Dataset has been used around the world for commercial, military and academic research; publicly available research citing Duke Multi-Target, Multi-Camera Tracking Project 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. </p> </section> -<section class="applet_container"> +<section class="applet_container fullwidth"> <div class="applet" data-payload="{"command": "map"}"></div> + </section> <div class="caption"> <ul class="map-legend"> <li class="edu">Academic</li> - <li class="com">Industry</li> - <li class="gov">Government / Military</li> + <li class="com">Commercial</li> + <li class="gov">Military / Government</li> <li class="source">Citation data is collected using <a href="https://semanticscholar.org" target="_blank">SemanticScholar.org</a> then dataset usage verified and geolocated.</li> </ul> </div> -<section> +<!-- <section> <p class='subp'> [section under development] Duke MTMC Dataset ... 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. </p> -</section><section> +</section> + --><section> <h3>Who used Duke MTMC Dataset?</h3> <p> - 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. </p> </section> @@ -80,14 +85,7 @@ <!-- <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> </div> --> <div class="applet" data-payload="{"command": "chart"}"></div> -</section><section> - <p> - These pie charts show overall totals based on country and institution type. - </p> - - </section> - -<section class="applet_container"> +</section><section class="applet_container"> <div class="applet" data-payload="{"command": "piechart"}"></div> </section><section> @@ -97,13 +95,13 @@ <div class="hr-wave-line hr-wave-line2"></div> </div> - <h2>Supplementary Information</h2> + <h3>Supplementary Information</h3> + </section><section class="applet_container"> - <h3>Citations</h3> + <h3>Dataset Citations</h3> <p> - Citations were collected from <a href="https://www.semanticscholar.org">Semantic Scholar</a>, 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 <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. </p> <p> Add [button/link] to download CSV. Add search input field to filter. |