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Recognizing Human Activities in Video by Multi-resolutional Optical Flows

A method to recognize human activities captured in video is proposed. The method classifies basic human body activities, such as walking, running, gymnastic exercises and others. Applying Burt-Adelson Pyramid approach, the system extracts useful features consisting of multi-resolutional optical flows. This paper also reports coarseness limit of spatial resolution of optical flow for activity recognition; optical flows of 8 sub-areas covering the human body area are minimum requirement for the recognition. Also, the experiment examines effective weighting of multi-resolutional feature components. These results on recognition of coarse video will be useful for designing surveillance camera system