From 1 to 100 Pixels

High resolution insights from low resolution data

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.

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
• 12x16 activity recognition
• 6/5 (up to 124/106) pixels in height/width, and the average is 24/20 for QMUL SurvFace
• 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.
• 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 0.5% of one Instagram photo

Find specific cases of facial resolution being used in legal cases, forensic investigations, or military footage

Research

• NIST report on sres states several resolutions
• "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" ¹

MORE RESEARCH