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Face indexing and searching from videos

Face indexing and searching from videos can be widely used in multimedia applications, information mining and biometric recognition. This paper presents a novel method for effective indexing and searching in videos. Differing from traditional methods, we sequentially integrate visual appearance with temporal continuity and position continuity for face comparison. Subgroups are so formed. Then, exemplars attached corresponding weights are selected from subgroups to form signatures. Lastly, subgroups are incorporated into groups with Earth Mover's Distance for hierarchical indexing and searching purposes. Experiments on some videos have demonstrated that the algorithm can achieve satisfying performance by full exploiting visual and timing information in videos.