diff options
| author | adamhrv <adam@ahprojects.com> | 2019-04-06 10:42:28 +0200 |
|---|---|---|
| committer | adamhrv <adam@ahprojects.com> | 2019-04-06 10:42:28 +0200 |
| commit | 117662d58786cade03b07493167f267220ba6b57 (patch) | |
| tree | f46bff3cd7b384da022349c2a4dae31485e6e643 | |
| parent | c4261b83aaf5632e16350bdc5e10ca601a00f072 (diff) | |
add duke mtmc saliency
22 files changed, 108 insertions, 39 deletions
diff --git a/site/content/pages/datasets/brainwash/assets/background.jpg b/site/content/pages/datasets/brainwash/assets/background.jpg Binary files differindex e6393ab5..83499088 100644..100755 --- a/site/content/pages/datasets/brainwash/assets/background.jpg +++ b/site/content/pages/datasets/brainwash/assets/background.jpg diff --git a/site/content/pages/datasets/brainwash/assets/brainwash_saliency_map.jpg b/site/content/pages/datasets/brainwash/assets/brainwash_saliency_map.jpg Binary files differnew file mode 100755 index 00000000..38e540f0 --- /dev/null +++ b/site/content/pages/datasets/brainwash/assets/brainwash_saliency_map.jpg diff --git a/site/content/pages/datasets/brainwash/assets/index.jpg b/site/content/pages/datasets/brainwash/assets/index.jpg Binary files differindex e5004ec0..d47aa68d 100755 --- a/site/content/pages/datasets/brainwash/assets/index.jpg +++ b/site/content/pages/datasets/brainwash/assets/index.jpg diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md index 494555ab..1f13f568 100644 --- a/site/content/pages/datasets/brainwash/index.md +++ b/site/content/pages/datasets/brainwash/index.md @@ -25,12 +25,12 @@ Brainwash is not a widely used dataset but since its publication by Stanford Uni If you happen to have been at Brainwash cafe in San Francisco at any time on October 26, November 13, or November 24 in 2014 you are most likely included in the Brainwash dataset and have unwittingly contributed to surveillance research. - - {% include 'dashboard.html' %} {% include 'supplementary_header.html' %} + +   diff --git a/site/content/pages/datasets/duke_mtmc/assets/background.jpg b/site/content/pages/datasets/duke_mtmc/assets/background.jpg Binary files differindex 2275bd9e..080939ba 100755..100644 --- a/site/content/pages/datasets/duke_mtmc/assets/background.jpg +++ b/site/content/pages/datasets/duke_mtmc/assets/background.jpg diff --git a/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam1.jpg b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam1.jpg Binary files differnew file mode 100644 index 00000000..9d4388df --- /dev/null +++ b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam1.jpg diff --git a/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam2.jpg b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam2.jpg Binary files differnew file mode 100644 index 00000000..2581ec33 --- /dev/null +++ b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam2.jpg diff --git a/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam3.jpg b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam3.jpg Binary files differnew file mode 100644 index 00000000..3d81c974 --- /dev/null +++ b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam3.jpg diff --git a/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam4.jpg b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam4.jpg Binary files differnew file mode 100644 index 00000000..e375abb9 --- /dev/null +++ b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam4.jpg diff --git a/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam5.jpg b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam5.jpg Binary files differnew file mode 100644 index 00000000..3d311f99 --- /dev/null +++ b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam5.jpg diff --git a/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam6.jpg b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam6.jpg Binary files differnew file mode 100644 index 00000000..f5b8d0d0 --- /dev/null +++ b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam6.jpg diff --git a/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam7.jpg b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam7.jpg Binary files differnew file mode 100644 index 00000000..116fe2ea --- /dev/null +++ b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam7.jpg diff --git a/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam8.jpg b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam8.jpg Binary files differnew file mode 100644 index 00000000..f4b9e4e6 --- /dev/null +++ b/site/content/pages/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam8.jpg diff --git a/site/content/pages/datasets/duke_mtmc/assets/index.jpg b/site/content/pages/datasets/duke_mtmc/assets/index.jpg Binary files differindex 7b144b42..1062e85c 100755..100644 --- a/site/content/pages/datasets/duke_mtmc/assets/index.jpg +++ b/site/content/pages/datasets/duke_mtmc/assets/index.jpg diff --git a/site/content/pages/datasets/duke_mtmc/index.md b/site/content/pages/datasets/duke_mtmc/index.md index b8c359d2..e8c7556f 100644 --- a/site/content/pages/datasets/duke_mtmc/index.md +++ b/site/content/pages/datasets/duke_mtmc/index.md @@ -30,16 +30,97 @@ The 8 cameras deployed on Duke's campus were specifically setup to capture stude #### Data Visualizations - +=== columns 2 + + + +===== + + + +==== end columns + + +=== columns 2 + + + +===== + + + +==== end columns + + +=== columns 2 + + + +===== + + + +==== end columns + + +=== columns 2 + + + +===== + + + +==== end columns + + +### Alternate Layout + + +=== columns 4 + + + +===== + + + +==== + + + +==== + + + +==== end columns + + +=== columns 4 + + + +===== + + + +==== + + + +===== + + + +==== end columns + ### TODO -- change to heatmap overlay of each location -- make fancy viz of foot trails with bbox and blurred persons - expand story - add google street view images of each camera location? - add actual head detections to header image with faces blurred - add 4 diverse example images with faces blurred -- add map location of the brainwash cafe +- add links to google map locations of each camera ### Footnotes
\ No newline at end of file diff --git a/site/content/pages/datasets/oxford_town_centre/index.md b/site/content/pages/datasets/oxford_town_centre/index.md index d2d37230..e65f27a9 100644 --- a/site/content/pages/datasets/oxford_town_centre/index.md +++ b/site/content/pages/datasets/oxford_town_centre/index.md @@ -3,7 +3,7 @@ status: published title: Oxford Town Centre desc: Oxford Town Centre is a dataset of surveillance camera footage from Cornmarket St Oxford, England -subdesc: The Oxford Town Centre dataset includes +subdesc: The Oxford Town Centre dataset includes approximately 2,200 identities and is used for research and development of face recognition systems slug: oxford_town_centre cssclass: dataset image: assets/background.jpg @@ -21,11 +21,9 @@ authors: Adam Harvey [ page under development ] -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 activity recognition, remote biometric analysis, and non-cooperative face recognition. [^ben_benfold_orig] +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.[^ben_benfold_orig] 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. -REVISE - -Although Oxford Town Centre dataset first appears as a pedestrian dataset, it was created to improve the stabilization of pedstrian detections in order to extract a more accurate head region that would lead to improvements in face recognition. +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. {% include 'dashboard.html' %} @@ -33,11 +31,9 @@ Although Oxford Town Centre dataset first appears as a pedestrian dataset, it wa ### Location -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 [source](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). 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. Combined with stability of camera 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. - - +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 [source](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). 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. -Halfway through the video a peculiar and somewhat rude man enters the video and stands directly over top a water drain for over a minute. His unusual demeanor and apparently scripted behavior suggests a possible relationship to the CCTV operators. + ### Demo Videos Using Oxford Town Centre Dataset @@ -51,12 +47,9 @@ Several researchers have posted their demo videos using the Oxford Town Centre d - [VTD - towncenter.avi](https://www.youtube.com/watch?v=LwMOmqvhnoc) -[ add visualization ] - - TODO -- make visualization +- make heatmap viz - add license info diff --git a/site/content/pages/datasets/uccs/assets/.~lock.uccs_camera_exif.csv# b/site/content/pages/datasets/uccs/assets/.~lock.uccs_camera_exif.csv# deleted file mode 100644 index 61ef22ef..00000000 --- a/site/content/pages/datasets/uccs/assets/.~lock.uccs_camera_exif.csv# +++ /dev/null @@ -1 +0,0 @@ -,adam,adam,05.04.2019 12:39,file:///home/adam/.config/libreoffice/4;
\ No newline at end of file diff --git a/site/content/pages/datasets/uccs/index.md b/site/content/pages/datasets/uccs/index.md index 8827b227..05e683af 100644 --- a/site/content/pages/datasets/uccs/index.md +++ b/site/content/pages/datasets/uccs/index.md @@ -80,7 +80,7 @@ The images in UCCS were taken on 18 non-consecutive days during 2012–2013. ### Location -The location of the camera and subjects can confirmed using the *Bellingcat method*. The visual clues that lead to location of the camera and subjects include the unique pattern of the sidewalk that is only used on the UCCS Pedestrian Spine near the West Lawn, the two UCCS sign poles with matching graphics still visible in Google Street View, the no parking sign and directionality of its arrow, the back of street sign next to it, the slight bend in the sidewalk, the presence of cars passing in the background of the image, and the far wall of the parking garage all match images in the dataset. The [original papers](https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1) also provides another clue: a [picture of the camera](https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1/figure/1) inside the office that was used to create the dataset. The window view in this image provides another match for the brick pattern on the north facade of the Kraember Family Library and the green metal fence along the sidewalk. View the [location on Google Maps](https://www.google.com/maps/place/University+of+Colorado+Colorado+Springs/@38.8934297,-104.7992445,27a,35y,258.51h,75.06t/data=!3m1!1e3!4m5!3m4!1s0x87134fa088fe399d:0x92cadf3962c058c4!8m2!3d38.8968312!4d-104.8049528) +The location of the camera and subjects can confirmed using several visual cues in the dataset images: the unique pattern of the sidewalk that is only used on the UCCS Pedestrian Spine near the West Lawn, the two UCCS sign poles with matching graphics still visible in Google Street View, the no parking sign and directionality of its arrow, the back of street sign next to it, the slight bend in the sidewalk, the presence of cars passing in the background of the image, and the far wall of the parking garage all match images in the dataset. The [original papers](https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1) also provides another clue: a [picture of the camera](https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1/figure/1) inside the office that was used to create the dataset. The window view in this image provides another match for the brick pattern on the north facade of the Kraember Family Library and the green metal fence along the sidewalk. View the [location on Google Maps](https://www.google.com/maps/place/University+of+Colorado+Colorado+Springs/@38.8934297,-104.7992445,27a,35y,258.51h,75.06t/data=!3m1!1e3!4m5!3m4!1s0x87134fa088fe399d:0x92cadf3962c058c4!8m2!3d38.8968312!4d-104.8049528)  diff --git a/site/public/datasets/brainwash/index.html b/site/public/datasets/brainwash/index.html index 02bb18d4..c367d8b1 100644 --- a/site/public/datasets/brainwash/index.html +++ b/site/public/datasets/brainwash/index.html @@ -52,7 +52,7 @@ <p><em>Brainwash</em> is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 11,918 images of "everyday life of a busy downtown cafe"<a class="footnote_shim" name="[^readme]_1"> </a><a href="#[^readme]" class="footnote" title="Footnote 1">1</a> captured at 100 second intervals throught the entire day. Brainwash dataset was captured during 3 days in 2014: October 27, November 13, and November 24. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com.<a class="footnote_shim" name="[^end_to_end]_1"> </a><a href="#[^end_to_end]" class="footnote" title="Footnote 2">2</a></p> <p>Brainwash is not a widely used dataset but since its publication by Stanford University in 2015, it has notably appeared in several research papers from the National University of Defense Technology in Changsha, China. In 2016 and in 2017 researchers there conducted studies on detecting people's heads in crowded scenes for the purpose of surveillance. <a class="footnote_shim" name="[^localized_region_context]_1"> </a><a href="#[^localized_region_context]" class="footnote" title="Footnote 3">3</a> <a class="footnote_shim" name="[^replacement_algorithm]_1"> </a><a href="#[^replacement_algorithm]" class="footnote" title="Footnote 4">4</a></p> <p>If you happen to have been at Brainwash cafe in San Francisco at any time on October 26, November 13, or November 24 in 2014 you are most likely included in the Brainwash dataset and have unwittingly contributed to surveillance research.</p> -</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/brainwash_mean_overlay.jpg' alt=' A visualization of 81,973 head annotations from the Brainwash dataset training partition. (c) Adam Harvey'><div class='caption'> A visualization of 81,973 head annotations from the Brainwash dataset training partition. (c) Adam Harvey</div></div></section><section> +</section><section> <h3>Who used Brainwash Dataset?</h3> <p> @@ -112,7 +112,7 @@ <h2>Supplementary Information</h2> -</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/00425000_960.jpg' alt=' An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)'><div class='caption'> An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)</div></div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/brainwash_montage.jpg' alt=' 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)'><div class='caption'> 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)</div></div></section><section><p>TODO</p> +</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/brainwash_saliency_map.jpg' alt=' A visualization of 81,973 head annotations from the Brainwash dataset training partition. © megapixels.cc'><div class='caption'> A visualization of 81,973 head annotations from the Brainwash dataset training partition. © megapixels.cc</div></div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/00425000_960.jpg' alt=' An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)'><div class='caption'> An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)</div></div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/brainwash_montage.jpg' alt=' 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)'><div class='caption'> 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)</div></div></section><section><p>TODO</p> <ul> <li>include the images referenced in the chinese defence papers?</li> <li>change supp images to 2x2 grid with bboxes</li> diff --git a/site/public/datasets/duke_mtmc/index.html b/site/public/datasets/duke_mtmc/index.html index 37a77387..06a9ed1b 100644 --- a/site/public/datasets/duke_mtmc/index.html +++ b/site/public/datasets/duke_mtmc/index.html @@ -38,7 +38,7 @@ <div>1,812 </div> </div><div class='meta'> <div class='gray'>Purpose</div> - <div>Person re-identification, multi-camera tracking</div> + <div>Person re-identification and multi-camera tracking</div> </div><div class='meta'> <div class='gray'>Created by</div> <div>Computer Science Department, Duke University, Durham, US</div> @@ -110,15 +110,14 @@ <h2>Supplementary Information</h2> </section><section><h4>Data Visualizations</h4> -</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><h3>TODO</h3> +</section><section><div class='columns columns-2'><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam1.jpg' alt=' Camera 1 © megapixels.cc'><div class='caption'> Camera 1 © 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_saliency_cam2.jpg' alt=' Camera 2 © megapixels.cc'><div class='caption'> Camera 2 © megapixels.cc</div></div></section></div></section><section><div class='columns columns-2'><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam3.jpg' alt=' Camera 3 © megapixels.cc'><div class='caption'> Camera 3 © 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_saliency_cam4.jpg' alt=' Camera 4 © megapixels.cc'><div class='caption'> Camera 4 © megapixels.cc</div></div></section></div></section><section><div class='columns columns-2'><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam5.jpg' alt=' Camera 5 © megapixels.cc'><div class='caption'> Camera 5 © 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_saliency_cam6.jpg' alt=' Camera 6 © megapixels.cc'><div class='caption'> Camera 6 © megapixels.cc</div></div></section></div></section><section><div class='columns columns-2'><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam7.jpg' alt=' Camera 7 © megapixels.cc'><div class='caption'> Camera 7 © 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_saliency_cam8.jpg' alt=' Camera 8 © megapixels.cc'><div class='caption'> Camera 8 © megapixels.cc</div></div></section></div></section><section><h3>Alternate Layout</h3> +</section><section><div class='columns columns-4'><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam1.jpg' alt=' Camera 1 © megapixels.cc'><div class='caption'> Camera 1 © 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_saliency_cam2.jpg' alt=' Camera 2 © megapixels.cc'><div class='caption'> Camera 2 © 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_saliency_cam3.jpg' alt=' Camera 3 © megapixels.cc'><div class='caption'> Camera 3 © 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_saliency_cam4.jpg' alt=' Camera 4 © megapixels.cc'><div class='caption'> Camera 4 © megapixels.cc</div></div></section></div></section><section><div class='columns columns-4'><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/duke_mtmc/assets/duke_mtmc_saliency_cam5.jpg' alt=' Camera 5 © megapixels.cc'><div class='caption'> Camera 5 © 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_saliency_cam6.jpg' alt=' Camera 6 © megapixels.cc'><div class='caption'> Camera 6 © 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_saliency_cam7.jpg' alt=' Camera 7 © megapixels.cc'><div class='caption'> Camera 7 © 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_saliency_cam8.jpg' alt=' Camera 8 © megapixels.cc'><div class='caption'> Camera 8 © megapixels.cc</div></div></section></div></section><section><h3>TODO</h3> <ul> -<li>change to heatmap overlay of each location</li> -<li>make fancy viz of foot trails with bbox and blurred persons</li> <li>expand story</li> <li>add google street view images of each camera location?</li> <li>add actual head detections to header image with faces blurred</li> <li>add 4 diverse example images with faces blurred</li> -<li>add map location of the brainwash cafe</li> +<li>add links to google map locations of each camera</li> </ul> </section> diff --git a/site/public/datasets/oxford_town_centre/index.html b/site/public/datasets/oxford_town_centre/index.html index 34234e50..3f2a698a 100644 --- a/site/public/datasets/oxford_town_centre/index.html +++ b/site/public/datasets/oxford_town_centre/index.html @@ -26,7 +26,7 @@ </header> <div class="content content-dataset"> - <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 + <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> @@ -47,9 +47,8 @@ <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 activity recognition, 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></p> -<p>REVISE</p> -<p>Although Oxford Town Centre dataset first appears as a pedestrian dataset, it was created to improve the stabilization of pedstrian detections in order to extract a more accurate head region that would lead to improvements in face recognition.</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> @@ -111,9 +110,8 @@ <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. Combined with stability of camera 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 Sreet 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 Sreet View and Oxford Town Centre dataset</div></div></section><section><p>Halfway through the video a peculiar and somewhat rude man enters the video and stands directly over top a water drain for over a minute. His unusual demeanor and apparently scripted behavior suggests a possible relationship to the CCTV operators.</p> -<h3>Demo Videos Using Oxford Town Centre Dataset</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> @@ -123,10 +121,9 @@ <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>[ add visualization ]</p> <p>TODO</p> <ul> -<li>make visualization</li> +<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> diff --git a/site/public/datasets/uccs/index.html b/site/public/datasets/uccs/index.html index c26caddc..c9faac68 100644 --- a/site/public/datasets/uccs/index.html +++ b/site/public/datasets/uccs/index.html @@ -29,7 +29,7 @@ <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</span> is a dataset of long-range surveillance photos of students at University of Colorado in Colorado Springs</span></div><div class='hero_subdesc'><span class='bgpad'>The UnConstrained College Students dataset includes 16,149 images and 1,732 identities of subjects on University of Colorado Colorado Springs campus and is used for making face recognition and face detection algorithms </span></div></div></section><section><div class='left-sidebar'><div class='meta'> <div class='gray'>Published</div> - <div>2016</div> + <div>2018</div> </div><div class='meta'> <div class='gray'>Images</div> <div>16,149 </div> @@ -209,7 +209,7 @@ </tbody> </table> </div></div></section><section><h3>Location</h3> -<p>The location of the camera and subjects can confirmed using the <em>Bellingcat method</em>. The visual clues that lead to location of the camera and subjects include the unique pattern of the sidewalk that is only used on the UCCS Pedestrian Spine near the West Lawn, the two UCCS sign poles with matching graphics still visible in Google Street View, the no parking sign and directionality of its arrow, the back of street sign next to it, the slight bend in the sidewalk, the presence of cars passing in the background of the image, and the far wall of the parking garage all match images in the dataset. The <a href="https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1">original papers</a> also provides another clue: a <a href="https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1/figure/1">picture of the camera</a> inside the office that was used to create the dataset. The window view in this image provides another match for the brick pattern on the north facade of the Kraember Family Library and the green metal fence along the sidewalk. View the <a href="https://www.google.com/maps/place/University+of+Colorado+Colorado+Springs/@38.8934297,-104.7992445,27a,35y,258.51h,75.06t/data=!3m1!1e3!4m5!3m4!1s0x87134fa088fe399d:0x92cadf3962c058c4!8m2!3d38.8968312!4d-104.8049528">location on Google Maps</a></p> +<p>The location of the camera and subjects can confirmed using several visual cues in the dataset images: the unique pattern of the sidewalk that is only used on the UCCS Pedestrian Spine near the West Lawn, the two UCCS sign poles with matching graphics still visible in Google Street View, the no parking sign and directionality of its arrow, the back of street sign next to it, the slight bend in the sidewalk, the presence of cars passing in the background of the image, and the far wall of the parking garage all match images in the dataset. The <a href="https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1">original papers</a> also provides another clue: a <a href="https://www.semanticscholar.org/paper/Large-scale-unconstrained-open-set-face-database-Sapkota-Boult/07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1/figure/1">picture of the camera</a> inside the office that was used to create the dataset. The window view in this image provides another match for the brick pattern on the north facade of the Kraember Family Library and the green metal fence along the sidewalk. View the <a href="https://www.google.com/maps/place/University+of+Colorado+Colorado+Springs/@38.8934297,-104.7992445,27a,35y,258.51h,75.06t/data=!3m1!1e3!4m5!3m4!1s0x87134fa088fe399d:0x92cadf3962c058c4!8m2!3d38.8968312!4d-104.8049528">location on Google Maps</a></p> </section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_map.jpg' alt=' Location on campus where students were unknowingly photographed with a telephoto lens to be used for defense and intelligence agency funded research on face recognition. Image: Google Maps'><div class='caption'> Location on campus where students were unknowingly photographed with a telephoto lens to be used for defense and intelligence agency funded research on face recognition. Image: Google Maps</div></div></section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/uccs/assets/uccs_map_3d.jpg' alt=' 3D view showing the angle of view of the surveillance camera used for UCCS dataset. Image: Google Maps'><div class='caption'> 3D view showing the angle of view of the surveillance camera used for UCCS dataset. Image: Google Maps</div></div></section><section><h3>Funding</h3> <p>The 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". Collectively, these papers and the creation of the dataset have received funding from the following organizations:</p> <ul> |
