3D Face and Ear Recognition based on Partial MARS Map

This paper proposes a 3D face recognition approach based on facial pose estimation, which is robust to large pose variations in the unconstrained scene. Deep learning method is used to facial pose estimation, and the generation of partial MARS (Multimodal fAce and eaR Spherical) map reduces the probability of feature points appearing in the deformed region. Then we extract the features from the depth and texture maps. Finally, the matching scores from two types of maps should be calculated by Bayes decision to generate the final result. In the large pose variations, the recognition rate of the method in this paper is 94.6%. The experimental results show that our approach has superior performance than the existing methods used on the MARS map, and has potential to deal with 3D face recognition in unconstrained scene.