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authoradamhrv <adam@ahprojects.com>2019-02-24 21:04:34 +0100
committeradamhrv <adam@ahprojects.com>2019-02-24 21:04:34 +0100
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-<!doctype html>
-<html>
-<head>
- <title>MegaPixels</title>
- <meta charset="utf-8" />
- <meta name="author" content="Adam Harvey<br> Berit Gilma<br> Matthew Stender" />
- <meta name="description" content="High resolution insights from low resolution imagery" />
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-<body>
- <header>
- <a class='slogan' href="/">
- <div class='logo'></div>
- <div class='site_name'>MegaPixels</div>
- <span class='sub'>The Darkside of Datasets</span>
- </a>
- <div class='links'>
- <a href="/search">Face Search</a>
- <a href="/datasets">Datasets</a>
- <a href="/research/from_1_to_100_pixels/">Research</a>
- <a href="/about">About</a>
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- </header>
- <div class="content">
-
- <section>
- <h1>From 1 to 100 Pixels</h1>
- <div class='meta'>
- <div>
- <div class='gray'>Posted</div>
- <div>2018-12-04</div>
- </div>
- <div>
- <div class='gray'>By</div>
- <div>Adam Harvey<br> Berit Gilma<br> Matthew Stender</div>
- </div>
-
- </div>
- </section>
-
- <section><h2>High resolution insights from low resolution data</h2>
-<p>This post will be about the meaning of "face". How do people define it? How to biometrics researchers define it? How has it changed during the last decade.</p>
-<p>What can you know from a very small amount of information?</p>
-<ul>
-<li>1 pixel grayscale</li>
-<li>2x2 pixels grayscale, font example</li>
-<li>4x4 pixels</li>
-<li>8x8 yotta yotta</li>
-<li>5x7 face recognition</li>
-<li>12x16 activity recognition</li>
-<li>6/5 (up to 124/106) pixels in height/width, and the average is 24/20 for QMUL SurvFace</li>
-<li>20x16 tiny faces paper</li>
-<li>20x20 MNIST handwritten images <a href="http://yann.lecun.com/exdb/mnist/">http://yann.lecun.com/exdb/mnist/</a></li>
-<li>24x24 haarcascade detector idealized images</li>
-<li>32x32 CIFAR image dataset</li>
-<li>40x40 can do emotion detection, face recognition at scale, 3d modeling of the face. include datasets with faces at this resolution including pedestrian.</li>
-<li>need more material from 60-100</li>
-<li>60x60 show how texture emerges and pupils, eye color, higher resolution of features and compare to lower resolution faces</li>
-<li>100x100 0.5% of one Instagram photo</li>
-</ul>
-<p>Find specific cases of facial resolution being used in legal cases, forensic investigations, or military footage</p>
-<p>Research</p>
-<ul>
-<li>NIST report on sres states several resolutions</li>
-<li>"Results show that the tested face recognition systems yielded similar performance for query sets with eye-to-eye distance from 60 pixels to 30 pixels" <sup class="footnote-ref" id="fnref-nist_sres"><a href="#fn-nist_sres">1</a></sup></li>
-</ul>
-<div class="footnotes">
-<hr>
-<ol><li id="fn-nist_sres"><p>NIST 906932. Performance Assessment of Face Recognition Using Super-Resolution. Shuowen Hu, Robert Maschal, S. Susan Young, Tsai Hong Hong, Jonathon P. Phillips<a href="#fnref-nist_sres" class="footnote">&#8617;</a></p></li>
-</ol>
-</div>
-</section>
-
- <section>
- <h3>MORE RESEARCH</h3>
- <div class='blogposts'>
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- </div>
- </section>
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