100% accurate face recognition achieved

Psychology researchers at the Glasgow University have been able to eliminate the variable effects of age, hairstyle, expression, lighting, and different camera equipment in a face recognition algorithm, resulting in a “100% success rate“. They achieved this by producing a composite “average face” for a person from 20 different pictures.

From the two researchers:
“We modeled human familiarity by using image averaging to derive stable face representations from naturally varying photographs. This simple procedure increased the accuracy of an industry standard face-recognition algorithm from 54 per cent to 100 per cent, bringing the robust performance of a familiar human to an automated system.”

Of course, there’s a catch. By 100% the researchers really mean that the detection in each one of their tests was correct, not that they are sure it would work 100% of the time in real life.

Although probably not perfect, this is still a valuable increase from the old detection methods and could help in today’s facial recognition applications. Of course, this is provided that 20 photos of the person already exist in some database. An image of John Travolta’s “average” face after the jump.