Investigating profile extracted from range data for 3D face recognition

In this paper we investigate the discriminative capability of facial profile extracted from range data for 3D face recognition. A robust symmetry plane detection method is proposed for profile extracting. A global profile matching approach based on k-th Hausdorff metric is presented to align and compare profiles, without detection of fiducial points that is often unreliable. The experiments are carried out on a low-quality database with 180 pieces of range data of 30 individuals acquired by a structured light system. Based on the experimental results, we observe that the profile is quite valuable information in 3D face recognition, and the best EER of 2.22% is achieved.