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Human activity recognition is a challenging area of research because of its various potential applications in visual surveillance. A spatio-temporal template matching based approach for activity recognition is proposed in this paper. We model the background in a scene using a simple statistical model and extract the foreground objects in a scene. Spatio-temporal templates are constructed using the motion history images (MHI) and object shape information for different human activities in a video like walking, standing, bending, sleeping and jumping. Experimental results show that the method can recognize these multiple activities for multiple objects with accuracy and speed.

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