Region-based Matching for Robust 3D Face Recognition

We present a novel region-based matching approach for automatic 3D face recognition which is robust to facial expressions, facial hair, illumination changes and large occlusions. Each 3D face in the gallery is segmented ofine into three disjoint regions, namely eyes-forehead, nose and cheeks. Recognition is performed on the basis of only the eyes-forehead and nose regions to avoid the effects of expressions and artifacts that occur in 3D faces due to a mustache or beard. These two regions of the gallery are matched with a probe using a modied version of the ICP algorithm and their matching scores are fused. The identity of the gallery face which gets the highest score is declared as the identity of the probe. Experiments were performed on the UND Biometrics Database which is so far the largest known database of 3D faces. We achieved a combined identication rate of 100% and a maximum verication rate of 99.42%. Our results also show that the eyes-forehead is the most signicant region for 3D face recognition with individual identication and verication rates of 97.32% and 97.25% respectively.