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Face expression recognition is useful for designing new interactive devices offering the possibility of new ways for human to interact with computer systems. In this paper we develop a facial expression recognition system , based on the facial features extracted from facial characteristic points in frontal image sequences. Selected facial feature points(More)
interpersonal communication. Most of the current works on the facial expression recognition attempt to recognize a small set of the prototypic expressions such as happy, surprise, anger, sad, disgust and fear. However the most of the human emotions are communicated by changes in one or two of discrete features. In this paper, we develop a facial expressions(More)
Mutual information has been used in many clustering algorithms for measuring general dependencies between random data variables, but its difficulties in computing for small size datasets has limited its efficiency for clustering in many applications. A novel clustering method is proposed which estimates mutual information based on information potential(More)
The most of the human emotions are communicated by changes in one or two of discrete facial features. Theses changes are coded as Action Units (AUs). Among the facial features mouth has most flexible deformability and it is highly complicated to track. In this paper, we develop a lip shape extraction and lip motion tracking system both in static and dynamic(More)