An Effective Approach to Pose Invariant 3D Face Recognition

• Main Authors: WANG, Dayong, HOI, Steven C. H., HE, Ying
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2011
• Subjects: Computer Sciences; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/2357; https://ink.library.smu.edu.sg/context/sis_research/article/3357/viewcontent/An_Effective_Approach_to_Pose_Invariant_3D_Face_Recognition.pdf
• Institution: Singapore Management University

One critical challenge encountered by existing face recognition techniques lies in the difficulties of handling varying poses. In this paper, we propose a novel pose invariant 3D face recognition scheme to improve regular face recognition from two aspects. Firstly, we propose an effective geometry based alignment approach, which transforms a 3D face mesh model to a well-aligned 2D image. Secondly, we propose to represent the facial images by a Locality Preserving Sparse Coding (LPSC) algorithm, which is more effective than the regular sparse coding algorithm for face representation. We conducted a set of extensive experiments on both 2D and 3D face recognition, in which the encouraging results showed that the proposed scheme is more effective than the regular face recognition solutions