New method uses machine learning to extrapolate features from thermal images.
It’s no mean feat for a computer to identify an individual’s face in daylight. The process involves precisely measuring a photograph — eye size, distance from nose to mouth, etc. — adjusting the distances for three dimensions, and searching a database for a match. But to do it at night, when all you have is far lower-resolution thermal images, the Army Research Lab used a technique that allows software to mimic the human brain.
Our brains “see” by extrapolating a picture from a relatively small amount of sensory data, filtered through the eye. The brain uses several times more neuronal mass to construct images from visual data than the eye does collecting the data.
The Army researchers saw a parallel with thermal images. Such images show what parts of the face are hotter and cooler, but generally contain fewer data points than a comparable optical image from a camera, making it hard to pick out distinct features.