Automatic pose-normalized 3D face modeling and recognition systems

Pose-variation factors present a big problem in 2D face recognition. To solve this problem, we designed a 3D face acquisition system which was able to generate multi-view images. However, this created another pose-estimation problem in terms of normalizing the 3D face data. This paper presents an automatic pose-normalized 3D face data acquisition method that is able to perform both 3D face modeling and 3D face pose-normalization at once. The proposed method uses 2D information with the AAM (Active Appearance Model) and 3D information with a 3D normal vector. The proposed system is based on stereo vision and a structured light system which consists of 2 cameras and I projector. In orsder to verify the performance of the proposed method, we designed an experiment for 2.5D face recognition. Experimental results showed that the proposed method is robust against pose variation.