Masked projection for 3D face recognition under occlusion

With advances in sensor technology, three dimensional (3D) face has become an emerging biometric modality, preferred especially in high security applications. However, dealing with facial occlusions is a great challenge, which should be handled to enable applicability to fully automatic security systems. In this paper, we propose a technique to deal with occlusions at 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, confirm that the masked subspace analysis offer an occlusion robust face recognition system.