Abstract: A rapid method for 3D face recognition based on rejection algorithm is proposed. First, the automatically segmented face with a different pose is normalized by means of principal component analysis (PCA), and transformed into the uniform pose coordinate system. Then, the central profile is extracted and matched based on the least trimmed square Hausdorff distance (LTS-HD) to form a rejection classifier which can eliminate a large number of candidate faces. Finally, the remaining faces are verified using a novel region-based iterative closest point (ICP) algorithm, and the result of the recognition is obtained. The simulation experiment on FRGC V2.0 database demonstrates that the proposed method is simple, efficient, and robust.