Segmentation and Classification of Human Activities∗
نویسندگان
چکیده
This paper describes an algorithm for segmenting and classifying human activities from video sequences of a shopping center. These activities comprise entering or exiting a shop, passing, or browsing in front of shop windows. The proposed approach recognizes these activities by using a priori knowledge of the layout of the shopping view. Human actions are represented by a bank of switch dynamical models, each tailored to describe a specific motion regime. Experimental tests illustrate the effectiveness of the proposed approach with synthetic and real data.
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