A joint approach to shape-based human tracking and behavior analysis

In this paper a joint human tracking and recognition system is proposed. While usually these two functions are performed separately, it will be shown that it is possible to improve the estimation performances if these functions are done jointly. For this purpose, a Bayesian estimation framework is presented and implemented using sequential Monte Carlo techniques. Moreover it will be shown how the estimation can be performed efficiently by using the Generalized Hough Transform. The effectiveness of the proposed approach is demonstrated for a variety of image sequences.