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This paper addresses the problem of occluded human segmentation and then uses its results for human behavior recognition. To tackle this ill-posed problem, a novel clustering scheme is proposed for constructing a model space for posture classification. Then, a model-driven approach is proposed for separating an occluded region to individual objects. For reducing the model space, a particle filtering...
This paper presents a new behavior classification system that can analyze human behaviors from arbitrary views. Technically, if different viewing angle are used for observing a person, his appearances will change significantly. To freely recognize his behaviors, traditional methods tend to adopt 3-D data for behavior analysis. However, its inherent correspondence process will make it inappropriate...
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