图像序列中的运动目标在跟踪过程中容易受到复杂环境以及严重遮挡所影响。针对该问题, 提出一种基于全局信息和局部信息的混合粒子滤波算法。新算法在传统粒子滤波的基础上引入了多子块纹理直方图, 它包含了目标的局部空间信息, 使得跟踪算法的鲁棒性有所提高; 根据目标受遮挡的程度自适应调节全局和局部信息对目标定位的贡献, 在一定程度上提高了算法的抗遮挡能力和适应能力, 实验结果表明该算法在目标处于部分遮挡和严重遮挡时能够达到比较理想的跟踪效果。

In order to solve the problem of complex environmental impact and serious occlusion during the object tracking in the sequence images, a hybrid particle filter tracking method based on the global and local information was proposed. The block texture histogram was imported into the traditional particle filter algorithm and made the algorithm be able to improve the robustness of the tracking algorithm which included the spatial information of target. The adaptability and occlusion resistance of the tracking algorithm was improved since adjusting adaptively the contribution of the global and local information by the degree of the object occlusion. Experimental results show that the proposed tracking algorithm exhibits good result in the presence of partial occlusion and serious occlusion.