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authoradamhrv <adam@ahprojects.com>2018-12-17 01:39:39 +0100
committeradamhrv <adam@ahprojects.com>2018-12-17 01:39:39 +0100
commitc7e73f613fc5189c0adeda9fd693cb6aca3d4247 (patch)
treef4ee5eb0fd84d84780b2d31d48c5ab666ab63236 /site/public/research/01_from_1_to_100_pixels
parent88ec48e1c4d93ba9cd3aa186c068ef2aa4c27c56 (diff)
parent6a6af799c528e7d2c865db75757e90cd921f85ae (diff)
Merge branch 'master' of github.com:adamhrv/megapixels_dev
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</div>
</section>
- <section><h2>High resolution insights from low resolution data</h2>
+ <section><h3>High resolution insights from low resolution data</h3>
<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>
@@ -64,7 +64,7 @@
<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>
+<h3>Research</h3>
<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>