Rapid stereo-vision enhanced face recognition

This paper presents a real-time face recognition system. The system uses a stereo camera to locate, track, and recognize a person's face. Our algorithm improves state-of-the-art monocular 2D object recognition techniques by additionally considering the facial 3D surface, which is relatively stable under different lighting conditions. First, faces are detected and their surfaces are reconstructed from the stereo images. Afterwards, a 3D face is composed by joining 2D image data and appropriate depth data. The 3D face is then decomposed into its principal components. The principal components are used to recognize a 3D face by comparing characteristics of the current face to those of known individuals in a database. The result is an efficient and accurate face recognition algorithm. To evaluate our approach, we compared its performance to a classical monocular face recognition algorithm and observed that the recognition rate increased on average by 7.7 percent.