Two in One: Joint Pose Estimation and Face Recognition with Pca

Face recognition based on 3D techniques is a promising approach since it takes advantage of the additional information provided by the 3D world, i.e. information of depth and of all possible view angles of the face is available making the whole approach more robust against illumination and pose variations. However, these 3D approaches require the cooperation of the person to acquire accurate 3D data; thus, they are not appropriated for some applications like video surveillance or restricted area access points where only a 2D face image is disposable. In this paper, a novel approach is presented which takes advantage of 3D data in the training stage but only requires 2D data in the recognition stage. The proposed method can be used for both pose estimation and face recognition. Moreover, the estimation of the pose can be used as side information to improve the performance of the face recognition stage. The experiments have been performed on the public UPC face database which is composed of 23 persons with faces that vary from -90o to +90o.