Smile, you’re on identity camera

Inspired by recent advances in psychological studies on motion-based face perception, we examine in this paper, from the viewpoint of pattern recognition, the identity information behind a smile. A smile video database is collected, from which we compute dense optical flow fields and generate features by summing up the flow fields over time during the neutral-to-smile period. We investigate the relationship between smiles and identity by studying the class separability of the features. Our experiment results indicate a strong identity-specific characteristic of smile dynamics. Moreover, we compare the discriminating power of the features generated from different face regions as well as from different periods of motion.

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