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Facial expression is one of the most powerful and natural signals for human beings conveying their emotional states and intentions. Recently, facial expression recognition from facial cues based on FACS is investigated, where facial expressions can be described by a subset of AUs, and the facial expression categories could be easily extended. The goal of our work is the proposal of an action unit analysis enhanced facial expression recognition system based on evolutional deep learning approach. The main contributions of our work include the following three aspects: (1) the temporal dynamic based 3DLeNets is exploited for video analysis based AUs detection. And a general evolutionary framework is conducted for the deep neural networks optimization. (2) The correlations among AUs and the correlation between AUs and emotions are investigated, and the relationship probability model between AUs and …