3D face recognition method by best fitting polynomials

A 3D face recognition method is proposed. For feature extraction, 3D point set is divided into number of slices to be projected on the central planes parallel to the slices. Feature vectors are formed by approximating best fitting polynomials for data on the planes. A multimodal approach in the score level and corresponding distance metrics for both unimodal and multimodal cases are presented.