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diff --git a/site/public/about/index.html b/site/public/about/index.html index 71038691..e2ce409d 100644 --- a/site/public/about/index.html +++ b/site/public/about/index.html @@ -31,13 +31,20 @@ <ul> <li><a href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> +<li><a href="/about/research/">Research Methodology</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> </ul> -</section><section><div class='right-sidebar'><h3>Project Statistics</h3> -<div class='meta'><div><div class='gray'>Project Started</div><div>2012</div></div><div><div class='gray'>Datasets Discovered</div><div>325</div></div><div><div class='gray'>Analyzed So Far</div><div>10</div></div></div><h3>Credits</h3> -<div class='meta'><div><div class='gray'>Author</div><div>Adam Harvey</div></div><div><div class='gray'>Development</div><div>Jules LaPlace</div></div><div><div class='gray'>Research Assistance</div><div>Berit Gilma</div></div><div><div class='gray'>Supported by</div><div>Mozilla</div></div></div></div><p>MegaPixels is an art and research project about the origins and ethics of facial analysis datasets. Where do they come from? Who's included? Who created it and for what reason?</p> +</section><section><div class='right-sidebar'><h3>Recent Press</h3> +<ul> +<li><a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">TheVerge: Transgender YouTubers had their videos grabbed to train facial recognition software</a> by James Vincent </li> +<li><a href="https://www.theverge.com/2017/8/22/16180080/transgender-youtubers-ai-facial-recognition-dataset">TheVerge: Transgender YouTubers had their videos grabbed to train facial recognition software</a> by James Vincent </li> +<li>[change to small button]Read more <a href="/about/press">press</a></li> +</ul> +</div><p>MegaPixels is an art and research project by Adam Harvey about the origins and ethics of facial analysis datasets. Where do they come from? Who's included? Who created it and for what reason?</p> +<p>MegaPixels sets out to answer to these questions and reveal the stories behind the millions of images used to train, evaluate, and power the facial recognition surveillance algorithms used today. MegaPixels is authored by Adam Harvey, developed in collaboration with Jules LaPlace, and produced in partnership with Mozilla.</p> +<p>MegaPixels sets out to answer to these questions and reveal the stories behind the millions of images used to train, evaluate, and power the facial recognition surveillance algorithms used today. MegaPixels is authored by Adam Harvey, developed in collaboration with Jules LaPlace, and produced in partnership with Mozilla.</p> <p>MegaPixels sets out to answer to these questions and reveal the stories behind the millions of images used to train, evaluate, and power the facial recognition surveillance algorithms used today. MegaPixels is authored by Adam Harvey, developed in collaboration with Jules LaPlace, and produced in partnership with Mozilla.</p> </section><section class='images'><div class='sideimage'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/about/assets/adam-harvey.jpg' alt='Adam Harvey'><div><p><strong>Adam Harvey</strong> is an American artist and researcher based in Berlin. His previous projects (CV Dazzle, Stealth Wear, and SkyLift) explore the potential for countersurveillance as artwork. He is the founder of VFRAME (visual forensics software for human rights groups), the recipient of 2 PrototypeFund awards, and is currently a researcher in residence at Karlsruhe HfG studying artifical intelligence and datasets.</p> </div></div></section><section class='images'><div class='sideimage'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/about/assets/jules-laplace.jpg' alt='Jules LaPlace'><div><p><strong>Jules LaPlace</strong> is an American artist and technologist also based in Berlin. He was previously the CTO of a NYC digital agency and currently works at VFRAME, developing computer vision for human rights groups, and building creative software for artists.</p> diff --git a/site/public/about/terms/index.html b/site/public/about/terms/index.html index 76cf1159..c90f1c9d 100644 --- a/site/public/about/terms/index.html +++ b/site/public/about/terms/index.html @@ -32,6 +32,7 @@ <li><a href="/about/">About</a></li> <li><a href="/about/press/">Press</a></li> <li><a href="/about/credits/">Credits</a></li> +<li><a href="/about/research/">Research Methodology</a></li> <li><a href="/about/disclaimer/">Disclaimer</a></li> <li><a href="/about/terms/">Terms and Conditions</a></li> <li><a href="/about/privacy/">Privacy Policy</a></li> diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html index a8a0aa4b..9657b866 100644 --- a/site/public/datasets/lfw/index.html +++ b/site/public/datasets/lfw/index.html @@ -43,7 +43,7 @@ <p>The LFW dataset includes 13,233 images of 5,749 people that were collected between 2002-2004. LFW is a subset of <em>Names of Faces</em> and is part of the first facial recognition training dataset created entirely from images appearing on the Internet. The people appearing in LFW are...</p> <p>The <em>Names and Faces</em> dataset was the first face recognition dataset created entire from online photos. However, <em>Names and Faces</em> and <em>LFW</em> are not the first face recognition dataset created entirely "in the wild". That title belongs to the <a href="/datasets/ucd_faces/">UCD dataset</a>. Images obtained "in the wild" means using an image without explicit consent or awareness from the subject or photographer.</p> <h3>Biometric Trade Routes</h3> -<p>To understand how this dataset has been used, its citations have been geocoded to show an approximate geographic digital trade route of the biometric data. Lines indicate an organization (education, commercial, or governmental) that has cited the LFW dataset in their research. Data is compiled from <a href="https://www.semanticscholar.org">Semantic Scholar</a>.</p> +<p>[convert to template] To understand how this dataset has been used, its citations have been geocoded to show an approximate geographic digital trade route of the biometric data. Lines indicate an organization (education, commercial, or governmental) that has cited the LFW dataset in their research. Data is compiled from <a href="https://www.semanticscholar.org">Semantic Scholar</a>.</p> </section><section class='applet_container'><div class='applet' data-payload='{"command": "map"}'></div></section><section><h3>Synthetic Faces</h3> <p>To visualize the types of photos in the dataset without explicitly publishing individual's identities a generative adversarial network (GAN) was trained on the entire dataset. The images in this video show a neural network learning the visual latent space and then interpolating between archetypical identities within the LFW dataset.</p> </section><section class='images'><div class='image'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/datasets/lfw/assets/synthetic_01.jpg' alt='Synthetically generated face from the visual space of LFW dataset'><div class='caption'>Synthetically generated face from the visual space of LFW dataset</div></div> diff --git a/site/public/datasets/vgg_face2/index.html b/site/public/datasets/vgg_face2/index.html index f06bc879..d0a161cb 100644 --- a/site/public/datasets/vgg_face2/index.html +++ b/site/public/datasets/vgg_face2/index.html @@ -32,6 +32,25 @@ <ul> <li>The VGG Face 2 dataset includes approximately 1,331 actresses, 139 presidents, 16 wives, 3 husbands, 2 snooker player, and 1 guru</li> </ul> +<h3>Names and descriptions</h3> +<ul> +<li>The original VGGF2 name list has been updated with the results returned from Google Knowledge</li> +<li>Names with a similarity score greater than 0.75 where automatically updated. Scores computed using <code>import difflib; seq = difflib.SequenceMatcher(a=a.lower(), b=b.lower()); score = seq.ratio()</code></li> +<li>The 97 names with a score of 0.75 or lower were manually reviewed and includes name changes validating using Wikipedia.org results for names such as "Bruce Jenner" to "Caitlyn Jenner", spousal last-name changes, and discretionary changes to improve search results such as combining nicknames with full name when appropriate, for example changing "Aleksandar Petrović" to "Aleksandar 'Aco' Petrović" and minor changes such as "Mohammad Ali" to "Muhammad Ali"</li> +<li>The 'Description' text was automatically added when the Knowledge Graph score was greater than 250</li> +</ul> +<h2>TODO</h2> +<ul> +<li>create name list, and populate with Knowledge graph information like LFW</li> +<li>make list of interesting number stats, by the numbers</li> +<li>make list of interesting important facts</li> +<li>write intro abstract</li> +<li>write analysis of usage</li> +<li>find examples, citations, and screenshots of useage</li> +<li>find list of companies using it for table</li> +<li>create montages of the dataset, like LFW</li> +<li>create right to removal information</li> +</ul> </section> </div> |