An improved MCMC particle filter based on greedy algorithm for video object tracking
Song Wang, Huiyuan Wang, Xiufen Wang · 2011
In this paper, an improved MCMC (Markov Chain Monte Carlo) particle filter for video tracking is proposed. MCMC plays an important role in video tracking and so is of popular use in this field. However, it is still very difficult to satisfy the requirement of real-time application for its high computation complexity. To solve this problem, the concept of greedy algorithm is adopted questioning this study. Experiment results show that the proposed approach performs well in both tracking robustness and computational efficiency.