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<div class='site_name'>MegaPixels</div>
<div class='page_name'>Brainwash Dataset</div>
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<a href="/datasets/">Datasets</a>
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<section class='intro_section' style='background-image: url(https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/background.jpg)'><div class='inner'><div class='hero_desc'><span class='bgpad'>Brainwash is a dataset of webcam images taken from the Brainwash Cafe in San Francisco in 2014</span></div><div class='hero_subdesc'><span class='bgpad'>The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection surveillance algorithms
</span></div></div></section><section><h2>Brainwash Dataset</h2>
</section><section><div class='right-sidebar'><div class='meta'>
<div class='gray'>Published</div>
<div>2015</div>
</div><div class='meta'>
<div class='gray'>Images</div>
<div>11,917 </div>
</div><div class='meta'>
<div class='gray'>Purpose</div>
<div>Head detection</div>
</div><div class='meta'>
<div class='gray'>Created by</div>
<div>Stanford University (US), Max Planck Institute for Informatics (DE)</div>
</div><div class='meta'>
<div class='gray'>Funded by</div>
<div>Max Planck Center for Visual Computing and Communication</div>
</div><div class='meta'>
<div class='gray'>Download Size</div>
<div>4.1 GB</div>
</div><div class='meta'>
<div class='gray'>Website</div>
<div><a href='https://purl.stanford.edu/sx925dc9385' target='_blank' rel='nofollow noopener'>stanford.edu</a></div>
</div></div><p>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"<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. 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 <a href="https://www.semanticscholar.org/paper/End-to-End-People-Detection-in-Crowded-Scenes-Stewart-Andriluka/1bd1645a629f1b612960ab9bba276afd4cf7c666">reserach paper</a> 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>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 their image would end up in dataset used for surveillance research and development, but that is exactly what happened to customers at Brainwash cafe in San Francisco.</p>
<p>Although Brainwash appears to be a less popular dataset, it notably was used in 2016 and 2017 by researchers affiliated the National University of Defense Technology in China for two <a href="https://www.semanticscholar.org/paper/Localized-region-context-and-object-feature-fusion-Li-Dou/b02d31c640b0a31fb18c4f170d841d8e21ffb66c">research</a> <a href="https://www.semanticscholar.org/paper/A-Replacement-Algorithm-of-Non-Maximum-Suppression-Zhao-Wang/591a4bfa6380c9fcd5f3ae690e3ac5c09b7bf37b">projects</a> on advancing the capabilities of object detection to more accurately isolate the target region in an image (<a href="https://www.itm-conferences.org/articles/itmconf/pdf/2017/04/itmconf_ita2017_05006.pdf">PDF</a>). <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>. The dataset also appears in a 2017 <a href="https://ieeexplore.ieee.org/document/7877809">research paper</a> from Peking University for the purpose of improving surveillance capabilities for "people detection in the crowded scenes".</p>
</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/brainwash_grid.jpg' alt=' A visualization of 81,973 head annotations from the Brainwash dataset training partition. Credit: megapixels.cc. License: Open Data Commons Public Domain Dedication (PDDL)'><div class='caption'> A visualization of 81,973 head annotations from the Brainwash dataset training partition. Credit: megapixels.cc. License: Open Data Commons Public Domain Dedication (PDDL)</div></div></section><section>
<h3>Who used Brainwash Dataset?</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>
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<h3>Biometric Trade Routes</h3>
<p>
To help understand how Brainwash Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Brainwash Dataset 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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<ul class="map-legend">
<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 >
</div>
<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. If you use our data, please <a href="/about/attribution">cite our work</a>.
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<h2>Supplementary Information</h2>
</section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/brainwash/assets/brainwash_example.jpg' alt=' An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The dataset contains 11,916 more images like this one. Credit: megapixels.cc. 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 dataset contains 11,916 more images like this one. Credit: megapixels.cc. 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_saliency_map.jpg' alt=' A visualization of the active regions for 81,973 head annotations from the Brainwash dataset training partition. Credit: megapixels.cc. License: Open Data Commons Public Domain Dedication (PDDL)'><div class='caption'> A visualization of the active regions for 81,973 head annotations from the Brainwash dataset training partition. Credit: megapixels.cc. License: Open Data Commons Public Domain Dedication (PDDL)</div></div></section><section>
<h4>Cite Our Work</h4>
<p>
If you use our data, research, or graphics please cite our work:
<pre id="cite-bibtex">
@online{megapixels,
author = {Harvey, Adam. LaPlace, Jules.},
title = {MegaPixels: Origins, Ethics, and Privacy Implications of Publicly Available Face Recognition Image Datasets},
year = 2019,
url = {https://megapixels.cc/},
urldate = {2019-04-18}
}</pre>
</p>
</section><section><h3>References</h3><section><ul class="footnotes"><li>1 <a name="[^readme]" class="footnote_shim"></a><span class="backlinks"><a href="#[^readme]_1">a</a></span>"readme.txt" <a href="https://exhibits.stanford.edu/data/catalog/sx925dc9385">https://exhibits.stanford.edu/data/catalog/sx925dc9385</a>.
</li><li>2 <a name="[^end_to_end]" class="footnote_shim"></a><span class="backlinks"><a href="#[^end_to_end]_1">a</a></span>Stewart, Russel. Andriluka, Mykhaylo. "End-to-end people detection in crowded scenes". 2016.
</li><li>3 <a name="[^localized_region_context]" class="footnote_shim"></a><span class="backlinks"><a href="#[^localized_region_context]_1">a</a></span>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.
</li><li>4 <a name="[^replacement_algorithm]" class="footnote_shim"></a><span class="backlinks"><a href="#[^replacement_algorithm]_1">a</a></span>Zhao. X, Wang Y, Dou, Y. A Replacement Algorithm of Non-Maximum Suppression Base on Graph Clustering.
</li></ul></section></section>
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