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diff --git a/site/content/pages/datasets/duke_mtmc/index.md b/site/content/pages/datasets/duke_mtmc/index.md index 2a8bfe05..dd4551d9 100644 --- a/site/content/pages/datasets/duke_mtmc/index.md +++ b/site/content/pages/datasets/duke_mtmc/index.md @@ -52,29 +52,31 @@ Citations from the United States and Europe show a similar trend to that in Chin | IARPA, IBM, CloudWalk | Horizontal Pyramid Matching for Person Re-identification | [arxiv.org](https://arxiv.org/abs/1804.05275) | 2018 | ✔ | | Microsoft | ReXCam: Resource-Efficient, Cross-CameraVideo Analytics at Enterprise Scale | [arxiv.org](https://arxiv.org/abs/1811.01268) | 2018 | ✔ | | Microsoft | Scaling Video Analytics Systems to Large Camera Deployments | [arxiv.org](https://arxiv.org/pdf/1809.02318.pdf) | 2018 | ✔ | -| University College of London, National University of Defense Technology | Unsupervised Multi-Object Detection for Video Surveillance Using Memory-Based RecurrentAttention Networks | [PDF](https://pdfs.semanticscholar.org/59f3/57015054bab43fb8cbfd3f3dbf17b1d1f881.pdf) | 2018 | ✔ | +| University College of London, National University of Defense Technology | Unsupervised Multi-Object Detection for Video Surveillance Using Memory-Based RecurrentAttention Networks | [SemanticScholar.org](https://pdfs.semanticscholar.org/59f3/57015054bab43fb8cbfd3f3dbf17b1d1f881.pdf) | 2018 | ✔ | | Vision Semantics Ltd. | Unsupervised Person Re-identification by Deep Learning Tracklet Association | [arxiv.org](https://arxiv.org/abs/1809.02874) | 2018 | ✔ | | US Dept. of Homeland Security | Re-Identification with Consistent Attentive Siamese Networks | [arxiv.org](https://arxiv.org/abs/1811.07487/) | 2019 | ✔ | By some metrics the dataset is considered a huge success. It is regarded as highly influential research and has contributed to hundreds, if not thousands, of projects to advance artificial intelligence for person tracking and monitoring. All the above citations, regardless of which country is using it, align perfectly with the original [intent](http://vision.cs.duke.edu/DukeMTMC/) of the Duke MTMC dataset: "to accelerate advances in multi-target multi-camera tracking". -The same logic applies for all the new extensions of the Duke MTMC dataset including [Duke MTMC Re-ID](https://github.com/layumi/DukeMTMC-reID_evaluation), [Duke MTMC Video Re-ID](https://github.com/Yu-Wu/DukeMTMC-VideoReID), Duke MTMC Groups, and [Duke MTMC Attribute](https://github.com/vana77/DukeMTMC-attribute). And it also applies to all the new specialized datasets that will be created from Duke MTMC, such as the low-resolution face recognition dataset called [QMUL-SurvFace](https://qmul-survface.github.io/), which was funded in part by [SeeQuestor](https://seequestor.com), a computer vision provider to law enforcement agencies including Scotland Yards and Queensland Police. From the perspective of academic researchers, companies, and defense agencies using these datasets to advance their organization's work, Duke MTMC contributes value their their bottom line. Regardless of who is using these datasets or how they're used, they are simple provided to make networks of surveillance cameras more powerful. +The same logic applies for all the new extensions of the Duke MTMC dataset including [Duke MTMC Re-ID](https://github.com/layumi/DukeMTMC-reID_evaluation), [Duke MTMC Video Re-ID](https://github.com/Yu-Wu/DukeMTMC-VideoReID), Duke MTMC Groups, and [Duke MTMC Attribute](https://github.com/vana77/DukeMTMC-attribute). And it also applies to all the new specialized datasets that will be created from Duke MTMC, such as the low-resolution face recognition dataset called [QMUL-SurvFace](https://qmul-survface.github.io/), which was funded in part by [SeeQuestor](https://seequestor.com), a computer vision provider to law enforcement agencies including Scotland Yards and Queensland Police. From the perspective of academic researchers, security contractors, and defense agencies using these datasets to advance their organization's work, Duke MTMC provides significant value regardless of who else is using it so long as it accelerate advances their own interests in artificial intelligence.  -But from a privacy and human rights perspective the creation and distribution of the Duke MTMC illustrates an egregious prioritization of surveillance technologies over individual rights, where the simple act of going to class could implicate your biometric data in a surveillance training dataset. + +But this perspective comes at significant cost to civil rights, human rights, and privacy. The creation and distribution of the Duke MTMC illustrates an egregious prioritization of surveillance technologies over individual rights, where the simple act of going to class could implicate your biometric data in a surveillance training dataset, perhaps even used by foreign defense agencies against your own ethics, against universal human rights, or against your own political interests. For the approximately 2,000 students in Duke MTMC dataset there is unfortunately no escape. It would be impossible to remove oneself from all copies of the dataset downloaded around the world. Instead, over 2,000 students and visitors who happened to be walking to class on March 13, 2014 will forever remain in all downloaded copies of the Duke MTMC dataset and all its extensions, contributing to a global supply chain of data that powers governmental and commercial expansion of biometric surveillance technologies. + + + + {% include 'dashboard.html' %} {% include 'supplementary_header.html' %} - - - #### Video Timestamps diff --git a/site/public/datasets/duke_mtmc/index.html b/site/public/datasets/duke_mtmc/index.html index 48c90d66..def7b8fa 100644 --- a/site/public/datasets/duke_mtmc/index.html +++ b/site/public/datasets/duke_mtmc/index.html @@ -182,7 +182,7 @@ <tr> <td>University College of London, National University of Defense Technology</td> <td>Unsupervised Multi-Object Detection for Video Surveillance Using Memory-Based RecurrentAttention Networks</td> -<td><a href="https://pdfs.semanticscholar.org/59f3/57015054bab43fb8cbfd3f3dbf17b1d1f881.pdf">PDF</a></td> +<td><a href="https://pdfs.semanticscholar.org/59f3/57015054bab43fb8cbfd3f3dbf17b1d1f881.pdf">SemanticScholar.org</a></td> <td>2018</td> <td>✔</td> </tr> @@ -203,10 +203,10 @@ </tbody> </table> <p>By some metrics the dataset is considered a huge success. It is regarded as highly influential research and has contributed to hundreds, if not thousands, of projects to advance artificial intelligence for person tracking and monitoring. All the above citations, regardless of which country is using it, align perfectly with the original <a href="http://vision.cs.duke.edu/DukeMTMC/">intent</a> of the Duke MTMC dataset: "to accelerate advances in multi-target multi-camera tracking".</p> -<p>The same logic applies for all the new extensions of the Duke MTMC dataset including <a href="https://github.com/layumi/DukeMTMC-reID_evaluation">Duke MTMC Re-ID</a>, <a href="https://github.com/Yu-Wu/DukeMTMC-VideoReID">Duke MTMC Video Re-ID</a>, Duke MTMC Groups, and <a href="https://github.com/vana77/DukeMTMC-attribute">Duke MTMC Attribute</a>. And it also applies to all the new specialized datasets that will be created from Duke MTMC, such as the low-resolution face recognition dataset called <a href="https://qmul-survface.github.io/">QMUL-SurvFace</a>, which was funded in part by <a href="https://seequestor.com">SeeQuestor</a>, a computer vision provider to law enforcement agencies including Scotland Yards and Queensland Police. From the perspective of academic researchers, companies, and defense agencies using these datasets to advance their organization's work, Duke MTMC contributes value their their bottom line. Regardless of who is using these datasets or how they're used, they are simple provided to make networks of surveillance cameras more powerful.</p> -</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_saliencies.jpg' alt=' Duke MTMC pedestrian detection saliency maps for 8 cameras deployed on campus © megapixels.cc'><div class='caption'> Duke MTMC pedestrian detection saliency maps for 8 cameras deployed on campus © megapixels.cc</div></div></section><section><p>But from a privacy and human rights perspective the creation and distribution of the Duke MTMC illustrates an egregious prioritization of surveillance technologies over individual rights, where the simple act of going to class could implicate your biometric data in a surveillance training dataset.</p> +<p>The same logic applies for all the new extensions of the Duke MTMC dataset including <a href="https://github.com/layumi/DukeMTMC-reID_evaluation">Duke MTMC Re-ID</a>, <a href="https://github.com/Yu-Wu/DukeMTMC-VideoReID">Duke MTMC Video Re-ID</a>, Duke MTMC Groups, and <a href="https://github.com/vana77/DukeMTMC-attribute">Duke MTMC Attribute</a>. And it also applies to all the new specialized datasets that will be created from Duke MTMC, such as the low-resolution face recognition dataset called <a href="https://qmul-survface.github.io/">QMUL-SurvFace</a>, which was funded in part by <a href="https://seequestor.com">SeeQuestor</a>, a computer vision provider to law enforcement agencies including Scotland Yards and Queensland Police. From the perspective of academic researchers, security contractors, and defense agencies using these datasets to advance their organization's work, Duke MTMC provides significant value regardless of who else is using it so long as it accelerate advances their own interests in artificial intelligence.</p> +</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_saliencies.jpg' alt=' Duke MTMC pedestrian detection saliency maps for 8 cameras deployed on campus © megapixels.cc'><div class='caption'> Duke MTMC pedestrian detection saliency maps for 8 cameras deployed on campus © megapixels.cc</div></div></section><section><p>But this perspective comes at significant cost to civil rights, human rights, and privacy. The creation and distribution of the Duke MTMC illustrates an egregious prioritization of surveillance technologies over individual rights, where the simple act of going to class could implicate your biometric data in a surveillance training dataset, perhaps even used by foreign defense agencies against your own ethics, against universal human rights, or against your own political interests.</p> <p>For the approximately 2,000 students in Duke MTMC dataset there is unfortunately no escape. It would be impossible to remove oneself from all copies of the dataset downloaded around the world. Instead, over 2,000 students and visitors who happened to be walking to class on March 13, 2014 will forever remain in all downloaded copies of the Duke MTMC dataset and all its extensions, contributing to a global supply chain of data that powers governmental and commercial expansion of biometric surveillance technologies.</p> -</section><section> +</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_cameras.jpg' alt=' Duke MTMC camera views for 8 cameras deployed on campus © megapixels.cc'><div class='caption'> Duke MTMC camera views for 8 cameras deployed on campus © megapixels.cc</div></div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_camera_map.jpg' alt=' Duke MTMC camera locations on Duke University campus. Open Data Commons Attribution License.'><div class='caption'> Duke MTMC camera locations on Duke University campus. Open Data Commons Attribution License.</div></div></section><section> <h3>Who used Duke MTMC Dataset?</h3> <p> @@ -266,7 +266,7 @@ <h2>Supplementary Information</h2> -</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_camera_map.jpg' alt=' Duke MTMC camera locations on Duke University campus. Open Data Commons Attribution License.'><div class='caption'> Duke MTMC camera locations on Duke University campus. Open Data Commons Attribution License.</div></div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_cameras.jpg' alt=' Duke MTMC camera views for 8 cameras deployed on campus © megapixels.cc'><div class='caption'> Duke MTMC camera views for 8 cameras deployed on campus © megapixels.cc</div></div></section><section><h4>Video Timestamps</h4> +</section><section><h4>Video Timestamps</h4> <p>The video timestamps contain the likely, but not yet confirmed, date and times of capture. Because the video timestamps align with the start and stop <a href="http://vision.cs.duke.edu/DukeMTMC/details.html#time-sync">time sync data</a> provided by the researchers, it at least aligns the relative time. The <a href="https://www.wunderground.com/history/daily/KIGX/date/2014-3-19?req_city=Durham&req_state=NC&req_statename=North%20Carolina&reqdb.zip=27708&reqdb.magic=1&reqdb.wmo=99999">rainy weather</a> on that day also contribute towards the likelihood of March 14, 2014..</p> </section><section><div class='columns columns-2'><div class='column'><table> <thead><tr> |