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 facemodel 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.