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authorjules@lens <julescarbon@gmail.com>2019-04-18 16:55:14 +0200
committerjules@lens <julescarbon@gmail.com>2019-04-18 16:55:14 +0200
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tree1a17bb4459776ac91f7006a2a407ca12edd3471e /site/content/pages/datasets/brainwash
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parentf8012f88641b0bb378ba79393f277c8918ebe452 (diff)
Merge branch 'master' of asdf.us:megapixels_dev
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@@ -14,49 +14,36 @@ authors: Adam Harvey
------------
-### sidebar
-### end sidebar
-
## Brainwash Dataset
-*Brainwash* 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"[^readme] 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 [cite orig paper].
-
-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 [^localized_region_context] [^replacement_algorithm].
-
-If you happen to have been at Brainwash cafe in San Franscisco at any time on October 26, November 13, or November 24 in 2014 you are most likely included in the Brainwash dataset.
+### sidebar
+### end sidebar
-![caption: The pixel-averaged image of all Brainwash dataset images is shown with 81,973 head annotations drawn from the Brainwash training partition. (c) Adam Harvey](assets/brainwash_mean_overlay.jpg)
+Brainwash is a dataset of livecam images taken from San Francisco's Brainwash Cafe. It includes 11,918 images of "everyday life of a busy downtown cafe"[^readme] captured at 100 second intervals throught the entire day. The Brainwash dataset includes 3 full days of webcam images taken on October 27, November 13, and November 24 in 2014. According the author's [reserach paper](https://www.semanticscholar.org/paper/End-to-End-People-Detection-in-Crowded-Scenes-Stewart-Andriluka/1bd1645a629f1b612960ab9bba276afd4cf7c666) introducing the dataset, the images were acquired with the help of Angelcam.com[^end_to_end]
+The Brainwash dataset is unique because it uses images from a publicly available webcam that records people inside a privately owned business without any consent. No ordinary cafe custom could ever suspect there image would end up in dataset used for surveillance reserach and development, but that is exactly what happened to customers at Brainwash cafe in San Francisco.
-{% include 'chart.html' %}
+Although Brainwash appears to be a less popular dataset, it was used in 2016 and 2017 by researchers from the National University of Defense Technology in China took note of the dataset and used it for two [research](https://www.semanticscholar.org/paper/Localized-region-context-and-object-feature-fusion-Li-Dou/b02d31c640b0a31fb18c4f170d841d8e21ffb66c) [projects](https://www.semanticscholar.org/paper/A-Replacement-Algorithm-of-Non-Maximum-Suppression-Zhao-Wang/591a4bfa6380c9fcd5f3ae690e3ac5c09b7bf37b) on advancing the capabilities of object detection to more accurately isolate the target region in an image ([PDF](https://www.itm-conferences.org/articles/itmconf/pdf/2017/04/itmconf_ita2017_05006.pdf)). [^localized_region_context] [^replacement_algorithm]. The dataset also appears in a 2017 [research paper](https://ieeexplore.ieee.org/document/7877809) from Peking University for the purpose of improving surveillance capabilities for "people detection in the crowded scenes".
-{% include 'piechart.html' %}
-{% include 'map.html' %}
+![caption: A visualization of 81,973 head annotations from the Brainwash dataset training partition. &copy; megapixels.cc](assets/brainwash_grid.jpg)
-{% include 'citations.html' %}
+{% include 'dashboard.html' %}
{% include 'supplementary_header.html' %}
-![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)](assets/00425000_960.jpg)
-
-![caption: 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)](assets/brainwash_montage.jpg)
-
-#### Additional Resources
-- The dataset author spoke about his research at the CVPR conference in 2016 <https://www.youtube.com/watch?v=Nl2fBKxwusQ>
+![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)](assets/brainwash_example.jpg)
+![caption: A visualization of 81,973 head annotations from the Brainwash dataset training partition. &copy; megapixels.cc](assets/brainwash_saliency_map.jpg)
-TODO
-
-- add bounding boxes to the header image
-- remake montage with randomized images, with bboxes
-- clean up intro text
-- verify quote citations
+{% include 'cite_our_work.html' %}
### Footnotes
+
[^readme]: "readme.txt" https://exhibits.stanford.edu/data/catalog/sx925dc9385.
+[^end_to_end]: Stewart, Russel. Andriluka, Mykhaylo. "End-to-end people detection in crowded scenes". 2016.
[^localized_region_context]: Li, Y. and Dou, Y. and Liu, X. and Li, T. Localized Region Context and Object Feature Fusion for People Head Detection. ICIP16 Proceedings. 2016. Pages 594-598.
-[^replacement_algorithm]: Zhao. X, Wang Y, Dou, Y. A Replacement Algorithm of Non-Maximum Suppression Base on Graph Clustering. \ No newline at end of file
+[^replacement_algorithm]: Zhao. X, Wang Y, Dou, Y. A Replacement Algorithm of Non-Maximum Suppression Base on Graph Clustering.