4 files changed, 168 insertions, 10 deletions
diff --git a/site/public/research/00_introduction/index.html b/site/public/research/00_introduction/index.html
index 395bd268..b661b939 100644
--- a/site/public/research/00_introduction/index.html
+++ b/site/public/research/00_introduction/index.html
@@ -25,7 +25,7 @@
       <a href="/about/">About</a>
     </div>
   </header>
-  <div class="content">
+  <div class="content content-">
     
   <section>
     <h1>00: Introduction</h1>
diff --git a/site/public/research/01_from_1_to_100_pixels/index.html b/site/public/research/01_from_1_to_100_pixels/index.html
index c11e966e..87a08886 100644
--- a/site/public/research/01_from_1_to_100_pixels/index.html
+++ b/site/public/research/01_from_1_to_100_pixels/index.html
@@ -25,7 +25,7 @@
       <a href="/about/">About</a>
     </div>
   </header>
-  <div class="content">
+  <div class="content content-">
     
   <section>
     <h1>From 1 to 100 Pixels</h1>
@@ -47,22 +47,31 @@
 <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>2x2 pixels grayscale, font example, can encode letters</li>
+<li>3x3 pixels: can create a font</li>
+<li>4x4 pixels: how many variations</li>
+<li>8x8 yotta yotta, many more variations</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>(prepare a Progan render of the QMUL dataset and TinyFaces)</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>NIST standards begin to appear from 40x40, distinguish occular pixels</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 all you need for medical diagnosis</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>Ideas:</p>
+<ul>
+<li>Find specific cases of facial resolution being used in legal cases, forensic investigations, or military footage</li>
+<li>resolution of boston bomber face</li>
+<li>resolution of the state of the union image</li>
+</ul>
 <h3>Research</h3>
 <ul>
 <li>NIST report on sres states several resolutions</li>
diff --git a/site/public/research/02_what_computers_can_see/index.html b/site/public/research/02_what_computers_can_see/index.html
new file mode 100644
index 00000000..6826955f
--- /dev/null
+++ b/site/public/research/02_what_computers_can_see/index.html
@@ -0,0 +1,150 @@
+<!doctype html>
+<html>
+<head>
+  <title>MegaPixels</title>
+  <meta charset="utf-8" />
+  <meta name="author" content="Adam Harvey" />
+  <meta name="description" content="What Computers Can See" />
+  <meta name="referrer" content="no-referrer" />
+  <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" />
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+      <div class='logo'></div>
+      <div class='site_name'>MegaPixels</div>
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+    <div class='links'>
+      <a href="/datasets/">Datasets</a>
+      <a href="/research/">Research</a>
+      <a href="/about/">About</a>
+    </div>
+  </header>
+  <div class="content content-">
+    
+  <section>
+    <h1>What Computers Can See</h1>
+    <div class='meta'>
+      <div>
+        <div class='gray'>Posted</div>
+        <div>2018-12-15</div>
+      </div>
+      <div>
+        <div class='gray'>By</div>
+        <div>Adam Harvey</div>
+      </div>
+      
+    </div>
+  </section>
+
+  <section><p>A list of 100 things computer vision can see, eg:</p>
+<ul>
+<li>age, race, gender, ancestral origin, body mass index</li>
+<li>eye color, hair color, facial hair, glasses</li>
+<li>beauty score, </li>
+<li>intelligence</li>
+<li>what you're looking at</li>
+<li>medical conditions</li>
+<li>tired, drowsiness in car</li>
+<li>affectiva: interest in product, intent to buy</li>
+</ul>
+<h2>From PubFig Dataset</h2>
+<ul>
+<li>Male</li>
+<li>Asian</li>
+<li>White</li>
+<li>Black</li>
+<li>Baby</li>
+<li>Child</li>
+<li>Youth</li>
+<li>Middle Aged</li>
+<li>Senior</li>
+<li>Black Hair</li>
+<li>Blond Hair</li>
+<li>Brown Hair</li>
+<li>Bald</li>
+<li>No Eyewear</li>
+<li>Eyeglasses</li>
+<li>Sunglasses</li>
+<li>Mustache</li>
+<li>Smiling Frowning</li>
+<li>Chubby</li>
+<li>Blurry</li>
+<li>Harsh Lighting</li>
+<li>Flash</li>
+<li>Soft Lighting</li>
+<li>Outdoor Curly Hair</li>
+<li>Wavy Hair</li>
+<li>Straight Hair</li>
+<li>Receding Hairline</li>
+<li>Bangs</li>
+<li>Sideburns</li>
+<li>Fully Visible Forehead </li>
+<li>Partially Visible Forehead </li>
+<li>Obstructed Forehead</li>
+<li>Bushy Eyebrows </li>
+<li>Arched Eyebrows</li>
+<li>Narrow Eyes</li>
+<li>Eyes Open</li>
+<li>Big Nose</li>
+<li>Pointy Nose</li>
+<li>Big Lips</li>
+<li>Mouth Closed</li>
+<li>Mouth Slightly Open</li>
+<li>Mouth Wide Open</li>
+<li>Teeth Not Visible</li>
+<li>No Beard</li>
+<li>Goatee </li>
+<li>Round Jaw</li>
+<li>Double Chin</li>
+<li>Wearing Hat</li>
+<li>Oval Face</li>
+<li>Square Face</li>
+<li>Round Face </li>
+<li>Color Photo</li>
+<li>Posed Photo</li>
+<li>Attractive Man</li>
+<li>Attractive Woman</li>
+<li>Indian</li>
+<li>Gray Hair</li>
+<li>Bags Under Eyes</li>
+<li>Heavy Makeup</li>
+<li>Rosy Cheeks</li>
+<li>Shiny Skin</li>
+<li>Pale Skin</li>
+<li>5 o' Clock Shadow</li>
+<li>Strong Nose-Mouth Lines</li>
+<li>Wearing Lipstick</li>
+<li>Flushed Face</li>
+<li>High Cheekbones</li>
+<li>Brown Eyes</li>
+<li>Wearing Earrings</li>
+<li>Wearing Necktie</li>
+<li>Wearing Necklace</li>
+</ul>
+</section>
+
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+\ No newline at end of file
diff --git a/site/public/research/index.html b/site/public/research/index.html
index 56348040..e78e34c6 100644
--- a/site/public/research/index.html
+++ b/site/public/research/index.html
@@ -25,11 +25,10 @@
       <a href="/about/">About</a>
     </div>
   </header>
-  <div class="content">
+  <div class="content content-">
     
   <section><h1>Research Blog</h1>
-<h3>The darkside of datasets and the future of computer vision</h3>
-</section><div class='research_index'><a href='/research/00_introduction/'><section class='wide'><img src='data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==' alt='Research post' /><section><h1>00: Introduction</h1><h2></h2></section></section></a><a href='/research/01_from_1_to_100_pixels/'><section class='wide'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/research/01_from_1_to_100_pixels/assets/intro.jpg' alt='Research post' /><section><h1>From 1 to 100 Pixels</h1><h2>Photographs are for romantics. For the rest of us, it's all about data.  And a photo contains a massive amount of information about who you are.</h2></section></section></a></div>
+</section><div class='research_index'><a href='/research/00_introduction/'><section class='wide'><img src='data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==' alt='Research post' /><section><h1>00: Introduction</h1><h2></h2></section></section></a><a href='/research/01_from_1_to_100_pixels/'><section class='wide'><img src='https://nyc3.digitaloceanspaces.com/megapixels/v1/site/research/01_from_1_to_100_pixels/assets/intro.jpg' alt='Research post' /><section><h1>From 1 to 100 Pixels</h1><h2>A breif description of this post, appears in the index page overview</h2></section></section></a></div>
 
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