3-D Face Recognition Under Occlusion Using Masked Projection

With advances in sensor technology, the three-dimensional (3-D) face has become an emerging biometric modality, preferred especially in high security applications. However, dealing with occlusions covering the facial surface is a great challenge, which should be handled to enable applicability to fully automatic security systems. In this paper, we propose a fully automatic 3-D face recognition system which is robust to occlusions. We basically consider two problems: 1) occlusion handling for surface registration, and 2) missing data handling for classification based on subspace analysis techniques. For the alignment problem, we employ an adaptively-selected-model-based registration scheme, where a face model is selected for an occluded face such that only the valid nonoccluded patches are utilized. After registering to the model, occlusions are detected and removed. In the classification stage, a masking strategy, which we call masked projection, is proposed to enable the use of subspace analysis techniques with incomplete data. Furthermore, a regional scheme suitable for occlusion handling is incorporated in classification to improve the overall results. Experimental results on two databases with realistic facial occlusions, namely, the Bosphorus and the UMB-DB, are reported. Experimental results confirm that registration based on the adaptively selected model together with the masked subspace analysis classification offer an occlusion robust face recognition system.