中文摘要：

针对复杂环境下的视觉目标鲁棒跟踪问题,模拟人视觉选择注意显著区域的智能特性,提出一种在线选择目标显著子区域的跟踪方法.根据中心-周围差异和相对背景的差异提取具有区分性的子区域,通过跟踪误差分析子区域时序一致性,选择稳定的显著子区域,利用子区域局部与目标整体的空间关系估计目标位置.实验结果表明,通过动态选择显著的目标子区域,能够提高对部分遮挡和背景相似干扰影响的适应性.

英文摘要：

A method of online selecting local salient subregions for object tracking in the complex environment is proposed by imitating human vision characteristic of selective attention on salient regions. Subregions are randomly sampled and selected according to center-surrounding discrimination and discrimination to background, and the temporal coherence of each subregion is evaluated by the tracking confidence. Then, stable subregions with low tracking errors are selected as the support cues to estimate object state by consistence of positions. Experimental result shows the ability to handle partial occlusion and background distractions by selecting salient subregions dynamically, which leads to more robust tracking.