Towards more accurate 3D face registration under the guidance of prior anatomical knowledge on human faces

Three-dimensional face registration is a critical step in 3D face recognition. A fully automatic registration method for aligning frontal 3D face data is presented in this paper with high accuracy and robustness to facial expressions. In our method, the nose region, which is relatively more rigid than other facial regions in Anatomy sense, is automatically located and analyzed for computing the precise location of a symmetry plane. We then proceed on to find a stable reference point and a nose line from the global information of the nose region. In this way, the six degrees of freedom as well as a unified coordinate system can be determined for each face. Extensive experiments have been conducted on the FRGC V1.0 benchmark face dataset to evaluate the accuracy and robustness of our registration method. Firstly, we compare its results with two other registration methods. One of such methods employs manually marked points on visualized face data and the other is based on the use of a symmetry plane analysis obtained from the whole face region. Secondly, we test its application in a 3-D face verification system. Preliminary experiment results show that this approach can efficiently reduce the intra-class distance and performs better than the other two registration methods in face recognition.