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Grid features based visual tracking

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Abstract

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.
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Dates and versions

hal-02318963 , version 1 (17-10-2019)

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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⟩
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