Description: Identification of actors for the behavior problems caused by changes in direction, a 3D model of human behavior based on 2D behavior recognition algorithms. In learning behavior
Classifier when the 3D mesh that acts of take samples of 3D joint points extracted human behavior characteristics as described for each type of sample-based behavioral training a hidden Markov
Seoul Markov model (Exemplar-based hidden Markov model, EHMM), while selected samples from the 3D behavior of a number of key frames as a 3D position set, the
Observed sample collection is connected 2D and 3D joint points of human feature of the bridge. 2D behavior in the identification, 2D sample sequence can be observed by one or more non-calibrated camera
Camera acquisition. First of all key positions in the 3D 2D focus for each frame with which the observed sample to find the best match of the 3D key frame position, followed by the classifier behavior observed on 2D
Sample sequence corresponding to the 3D se
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基于人体行为3D模型的2D行为识别.kdh
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