Face recognition using optimized 3D information from stereo images

Abstract

In this paper we propose a new range-based face recognition for significant improvement in the recognition rate using an optimized stereo acquisition system. The optimized 3D acquisition system consists of an eyes detection algorithm, facial pose direction distinction, and principal component analysis (PCA). The proposed method is carried out in the YCbCr color space in order to detect the face candidate area. To detect the correct face, it acquires the correct distance of the face candidate area and depth information of eyes and mouth. After scaling, the system transfers the pose change according to the distance. The face is finally recognized by the optimized PCA for each area with the facial pose elements detected. Simulation results with face recognition rate of 95.83% (100cm) in the front and 98.3% with the pose change were obtained successfully. Therefore, proposed method can be used to obtain high recognition rate with an appropriate scaling and pose change according to the distance.