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In this paper, we show that different body parts do not play equallyimportant roles in recognizing a human action in video data. We investigate towhat extent a body part plays a role in recognition of different actions andhence propose a generic method of assigning weights to different body points.The approach is inspired by the strong evidence in the applied perceptioncommunity that humans perform recognition in a foveated manner, that is theyrecognize events or objects by only focusing on visually significant aspects.An important contribution of our method is that the computation of the weightsassigned to body parts is invariant to viewing directions and camera parametersin the input data. We have performed extensive experiments to validate theproposed approach and demonstrate its significance. In particular, results showthat considerable improvement in performance is gained by taking into accountthe relative importance of different body parts as defined by our approach.

An Invariant Model of the Significance of Different Body Parts in Recognizing Different Actions