关键词: 稀疏表示, 观测模型, 子区域匹配, 模板校正

Abstract: The traditional tracking method based on sparse representation may tend to be unstable when processing challenging videos and the phenomenon of tracking drifting may occur when the target is occluded during the process of object tracking. To solve the problem, a novel approach of object tracking based on sparse representation of sub-region matching is proposed. Firstly, the object template is divided into several sub-regions and the observation model is established by LK image registration algorithm to predict the object motion state of next frame. Then, the region of observation model of prediction is equally divided and the optimal sub-region in the matching process is searched. Finally, by introducing a new template correction mechanism in the process of template update, it overcomes the phenomenon of tracking drifting effectively. The experimental results demonstrate that the proposed tracking algorithm has ideal effect of tracking in the case of object occlusion, motion, illumination and complex background when the multiple object tracking algorithm is tested under different video sequences, and it has well tracking performance compared to traditional tracking method based on sparse representation.

Key words: sparse representation, observation model, sub-region matching, template correction