关键词: 稀疏表示, 多源数据融合, 目标跟踪

Abstract: The traditional parse representation based visual tracking mainly uses the grayscale feature of the target to construct the sparse representation model. Since grayscale feature is sensitive to the change of illumination, which may reduce the robustness of the target tracking in complex scenarios. The multisource data based visual tracking can significantly improve the visual tracking robustness, but how to effectively fuse different dimensions, different types of multi-source target features become the key issues to be solved in the multisource data fusion. This paper proposes a target state and grayscale feature fusion based sparse representation method for robust visual tracking. The proposed method can effectively fuse two features with different dimensions through using the kernel sparse representation model to explore the relation between target state and grayscale. The proposed method can improve the accuracy of the visual tracking in complex scenarios.

Key words: sparse representation, multisource data fusion, target tracking