Multi-Directional Face Acquisition and Recognition of Moving People

Abstract

Multi-directional face image acquisition of moving people and techniques for recognizing them are described. Our system uses an extra active camera in addition to a conventional fixed camera. When the fixed camera detects a person who moves toward the active camera, it zooms in towards the person's head and captures close-up multi-directional face images by using multi-directional-averaged-face templates. It captures 3.9 times as many multi-directional face images as the technique using the front averaged-face template only. Our technique substantially increases the chance of identifying a person in a looking-at-people system. Further more, the obtained face image is recognized by using the template matching technique. The recognition system showed a correct recognition rate of 86.0 % for the face images automatically obtained from people in experimental environments. Our technique would be useful for this system to recover people's names if face-recognition fails at a specific place such as a room entrance, a person steps out of view and quickly comes back into view, or an original ID is reinstated after occlusion ends.