Recognizing Occluded 3D Faces Using an Efficient ICP Variant

This paper proposes an efficient variant of the Iterative Closest Point (ICP) algorithm for 3D face recognition in the presence of occlusion. The new ICP variant improves the original one in two aspects: the computational efficiency and the robustness to occlusion changes. For the former one, a facial surface is firstly described as a Spherical Depth Map (SDM), based on which uniform down-sampling can be conveniently applied to remove redundant vertices, aiming to decrease the consumed time of ICP. For the latter one, since occlusions can be considered as face outliers, a rejection strategy is embedded into ICP to eliminate their impacts. The proposed method is validated in face verification and identification scenarios on the Bosphorus database, and the experimental results clearly demonstrate its effectiveness and efficiency.