Video-Based Face Recognition Using the Intra-Personal/Extra-Personal Difference Dictionary
In Proceedings British Machine Vision Conference 2014
AbstractFace recognition in unconstrained videos is challenging due to large variations in pose, illumination, expression etc. In this paper, we address the problem from two different aspects: To handle pose variations, we learn a Structural-SVM based detector which can simultaneously localize face fiducial points and estimate face pose. By adopting a different optimization criterion from existing algorithms, we are able to improve localization accuracy. We model face variations of other kinds using intra-personal/extra-personal dictionaries. The proposed framework is advantageous in terms of both accuracy and scalability. We demonstrate through experiments that our algorithm outperforms state-of-the-art approaches on challenging public databases.
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