A 3D Face Recognition System Using Passive Stereo Vision and Its Performance Evaluation

This paper proposes a three-dimensional (3D) face recognition system using passive stereo vision. So far, the reported 3D face recognition systems assume the use of active 3D measurement for 3D facial capture. However, active methods employ structured illumination or laser scanning, which is not desirable in many human recognition applications. Addressing this problem, we propose a 3D face recognition system that uses (i) AdaBoost-based face detection to automatically extract a face region from an image, (ii) passive stereo vision to capture 3D facial information, and (iii) 3D face matching based on a simple ICP (iterative closest point) algorithm. Experimental evaluation demonstrates an efficient recognition performance of the proposed system