Converting facial expressions using recognition-based analysis of image Sequences
A method for converting one person's facial expression into another person's is proposed. The sequence of the feature vector for each expression is modeled by using HMM with the hidden states corresponding to the different muscle conditions (relaxed, contracting, and the end of contraction). The probability of each state is evaluated for each frame and the contraction rate of each muscle is obtained from the probability of each state using a matrix representing the characteristics of other people's expressions. The experiments showed the superior realism of the expression generated by our proposed method.
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