目的 遮挡是目标跟踪领域一个棘手的问题，如何处理好遮挡是衡量跟踪算法鲁棒性的关键。本文就此问题，提出了一种基于分片跟踪下的遮挡处理算法。方法 本算法在目标发生部分遮挡或者形变后，通过剩余有效片的强度信息，继续对目标实现可靠跟踪，并结合卡尔曼滤波有效的处理跟踪过程中的遮挡。算法采用分片的思想，利用Bhattacharyya系数作为候选目标片与相应模板片的相似性度量，有效的跟踪目标，采用H分量的反向投影的方法辨别遮挡和形变，根据遮挡的不同类型，做相应的处理，实现对目标的鲁棒性跟踪。结果 实验就遮挡提出了关联性遮挡和非关联性遮挡的概念，针对不同遮挡情况的处理，提高了跟踪的鲁棒性。结论 通过分片跟踪方式，并考虑目标物与遮挡物之间的关联性，跟踪效率明显提高。

Objective Occlusion is an issue in the tracking field, and the handling of occlusion is a key measure for robust tracking algorithms. In this article, we propose a new algorithm of handling occlusion fragments-based tracking. Method When the target is partially occluded or the pose changes, the strength of the remaining effective patch of information remains credible. Our algorithm uses the Bhattacharyya coefficient of similarity measure as a candidate target piece with the corresponding template piece to track a target effectively. Using H back projection method to distinguish between occlusion and pose change. According to the different types of occlusion, it makes the appropriate handle to realize robust tracking of the target. Result The present experiment proposed the concept of relevance occlusion and non-relevance occlusion, increasing the reliability of algorithm for tracking. Conclusion Through fragments-based tracking,and taking into account the correlation between the target and obstructions,it will make improved about the tracking efficiency significantly.