Grid features based visual tracking

Yi Zhou (1) , Hichem Snoussi (2) , Shibao Zheng (1)

1 Shanghai Jiao Tong University [Shanghai]
2 LM2S - Laboratoire Modélisation et Sûreté des Systèmes

Vulnerability to occlusion is one of the main issue in visual tracking. In this proposal, we exploit the local grid features to build a robust tracker. To improve performance under occlusion, local and global features are modeled for a target tracking. Cooperating with the novel features, a new segmentation and similarity measurement are proposed for exploring the local grid advantages. Experimental results show that our tracker outperforms other two effective visual tracking methods under occlusion.

Domains: Automatic

Yi Zhou, Hichem Snoussi, Shibao Zheng. Grid features based visual tracking. 2011 IEEE International Conference on Computer Science and Automation Engineering (CSAE), Jun 2011, Shanghai, China. pp.247-250, ⟨10.1109/CSAE.2011.5952844⟩. ⟨hal-02318963⟩