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Facial expression is one of the most powerful, natural, and abrupt means for human beings which have the knack to communicate emotion and regulate inter-personal behaviour. In this paper, the authors present a novel approach for facial expression detection using decision tree. Facial expression information is mostly concentrate on facial expression information regions, so the mouth, eye and eyebrow regions are segmented from the facial expression images firstly. Using these templates they calculate 30 Facial Characteristics Points (FCP's). These facial characteristic points describe the position and shape of the above three organs to find diverse parameters which are input to the decision tree for recognizing different facial expressions.
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