diff options
| -rw-r--r-- | site/content/pages/datasets/afad/index.md | 2 | ||||
| -rw-r--r-- | site/content/pages/research/01_from_1_to_100_pixels/index.md | 19 |
2 files changed, 13 insertions, 8 deletions
diff --git a/site/content/pages/datasets/afad/index.md b/site/content/pages/datasets/afad/index.md index 6b5b96ed..3b0ca3c3 100644 --- a/site/content/pages/datasets/afad/index.md +++ b/site/content/pages/datasets/afad/index.md @@ -18,8 +18,6 @@ authors: Adam Harvey + Origin: RenRen -**Unconstrained College Students** is a large-scale, unconstrained face detection and recognition dataset. It includes - ----- ## Research diff --git a/site/content/pages/research/01_from_1_to_100_pixels/index.md b/site/content/pages/research/01_from_1_to_100_pixels/index.md index 29204168..409dcf02 100644 --- a/site/content/pages/research/01_from_1_to_100_pixels/index.md +++ b/site/content/pages/research/01_from_1_to_100_pixels/index.md @@ -3,7 +3,7 @@ status: published title: From 1 to 100 Pixels desc: High resolution insights from low resolution imagery -tagline: 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. +tagline: A breif description of this post, appears in the index page overview image: assets/intro.jpg slug: from-1-to-100-pixels published: 2018-12-04 @@ -21,23 +21,30 @@ This post will be about the meaning of "face". How do people define it? How to b What can you know from a very small amount of information? - 1 pixel grayscale -- 2x2 pixels grayscale, font example -- 4x4 pixels -- 8x8 yotta yotta -- 5x7 face recognition +- 2x2 pixels grayscale, font example, can encode letters +- 3x3 pixels: can create a font +- 4x4 pixels: how many variations +- 8x8 yotta yotta, many more variations +- 5x7 face recognition - 12x16 activity recognition - 6/5 (up to 124/106) pixels in height/width, and the average is 24/20 for QMUL SurvFace +- (prepare a Progan render of the QMUL dataset and TinyFaces) - 20x16 tiny faces paper - 20x20 MNIST handwritten images <http://yann.lecun.com/exdb/mnist/> - 24x24 haarcascade detector idealized images - 32x32 CIFAR image dataset - 40x40 can do emotion detection, face recognition at scale, 3d modeling of the face. include datasets with faces at this resolution including pedestrian. +- NIST standards begin to appear from 40x40, distinguish occular pixels - need more material from 60-100 - 60x60 show how texture emerges and pupils, eye color, higher resolution of features and compare to lower resolution faces +- 100x100 all you need for medical diagnosis - 100x100 0.5% of one Instagram photo +Ideas: -Find specific cases of facial resolution being used in legal cases, forensic investigations, or military footage +- Find specific cases of facial resolution being used in legal cases, forensic investigations, or military footage +- resolution of boston bomber face +- resolution of the state of the union image ### Research |