Abstract
In this paper, the problem of simultaneous motion estimation of multiple independently moving objects is addressed. A novel Bayesian approach is designed for solving this problem using the sequential importance sampling (SIS) method. In the proposed algorithm, a balancing step is added into the SIS procedure to preserve samples of low weights so that all objects have enough samples to propagate empirical motion distributions. By using the proposed algorithm, the relative motions of all moving objects with respect to camera can be simultaneously estimated . This algorithm has been tested on both synthetic and real image sequences. Improved results have been achieved.
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