Natural interaction is the evolutive direction of human computer interaction, and the goal is to give computer the ability to communicate and interact with user according to the cognitional habit and manner formed unselfconsciously when human is communicating with nature. As the most natural and intuitive interaction manners, facial expression and hand gesture play important roles in social activities. It will be very helpful for natural human computer interface realization to do research on facial expression and hand gesture using computer vision techniques. In this dissertation, we study on facial expression and hand gesture analysis, and the main contributions of this thesis are as follows: 1. As for face and facial expression modeling, a 3d parameterized model called CANDIDE is used to model the face and facial actions, a weak perspective projection method is used to model the head pose. Restriction based on physical structure is used in the model, so actually impossible facial expressions are avoided and the efficiency of latter tracking and recognition is promoted. In addition, appropriate facial action parameters are picked out for facial feature tracking and facial expression recognition according to the characteristics of facial expression. 2. As for facial feature tracking, we start from the two problems of observation modeling and model fitting. Firstly, an adaptive method based on online learning and robust feature combining edge strength and raw intensity is proposed to build the observation model, and the robustness of tracking is promoted. Secondly, to solve the time-consuming model fitting problem, an iterative model fitting algorithm combining Inverse Compositional Image Alignment with online appearance models is proposed, which improves the fitting efficiency. 3. As for facial expression analysis, a fuzzy clustering algorithm based on Gaussian basis distance measure to do expression recognition; while augmented variance ratio is used as the penalty factor of Gaussian basis measure and the clustering performance is promoted. We give a total consideration of the anterior alignment and tracking with the posterior facial expression classification, and the facial parameters obtained by tracking are directly used to do facial expression recognition, so the impact caused by facial diversity of different person is eliminated. Fuzzy description of facial expression is presented in recognition on account of its complication and uncertainty. 4....
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