An Efficient 3D Face Recognition Algorithm

This paper proposes an efficient expression invariant algorithm for 3D face recognition of subjects. The proposed algorithm uses a surface-based approach to extract automatically and to define geometrically the facial features like eyebrows, nose and lips. These extracted features are used to obtain some unique control points that can be used for matching. The algorithm is tested on Binghamton University 3D Facial Expression (BU-3DFE) database where each subject is having at least 6 expressions and is found to be more than 98.5% accurate.