TEMPORAL-SPATIAL FACE RECOGNITION USING MULTI-ATLAS AND MARKOV PROCESS MODEL

Although video-based face recognition algorithms can pro-vide more information than image-based algorithms, their performance is affected by subjects ’ head poses, expressions, illumination and so on. In this paper, we present an effec-tive video-based face recognition algorithm. Multi-atlas is employed to efficiently represent faces of individual persons under various conditions, such as different poses and expres-sions. The Markov process model is used to propagate the temporal information between adjacent video frames. The combination of multi-atlas and Markov model provides robust face recognition by taking both spatial and temporal infor-mation into account. The performance of our algorithm was evaluated on three standard test databases: the Honda/UCSD video database, the CMU Motion of Body database, and the multi-modal VidTIMIT database. Experimental results demonstrate that our video-based face recognition algorithm outperforms other methods on all three test databases. Index Terms — Video-based face recognition, temporal-spatial face recognition, multi-atlas, Markov process model 1