中文摘要：

该文提出了一种对粒子滤波跟踪器进行分裂和合并的自重构算法.该算法能够通过分裂跟踪器以应对复杂多变的跟踪环境,同时,合并过程能够从多个跟踪器中选出最优跟踪器,合并冗余的跟踪器以达到减少计算量的效果.通过使用分裂和合并,能够在使用较少粒子的情况下达到很好的跟踪效果,在一定程度上解决了粒子滤波跟踪中计算量大的问题.分裂出来的多个跟踪器能够同时从多个位置多个方向跟踪目标,降低了复杂环境下目标跟踪丢失的概率,避免了粒子滤波中跟踪丢失时需重新选定目标的问题.通过和其他算法对比,文中提出的算法在跟踪准确性和跟踪效率两个方面表现优秀.

英文摘要：

We propose a novel algorithm named ARPF （Auto-Reconstructing Particle Filter） which reconstructs particle filter trackers automatically using split and merge technology.The algorithm deals with complicated and inconstant environments by splitting the tracker into two or more ones.In the merge process the best one is selected from the trackers constructed in the split process,and as a result the computation cost is reduced by merging useless trackers.With split and merge,the algorithm can get good tracking results even using fewer particles.The trackers constructed in the split process can track a target from different positions and directions,and therefore can reduce the probability of losing the target.Compared with other methods,the experimental results of our ARPF method show better effectiveness and efficiency.