Nasal region-based 3D face recognition under pose and expression variations

Abstract

In this work, we propose a fully automatic pose and expression invariant part-based 3D face recognition system. The proposed system is based on pose correction and curvature-based nose segmentation. Since the nose is the most stable part of the face, it is largely invariant under expressions. For this reason, we have concentrated on locating the nose tip and segmenting the nose. Furthermore, the nose direction is utilized to correct pose variations. We try both one-to-all and Average Nose Model-based methodologies for registration. Our results show that the utilization of anatomically-cropped nose region increases the recognition accuracy up to 94.10 per cent for frontal facial expressions and 79.41 per cent for pose variations in the Bosphorus 2D/3D face database. © Springer-Verlag Berlin Heidelberg 2009.