利用超像素混合投票的在线目标跟踪算法

doi:10.3969/j.issn.1001-2400.2015.03.011

Abstract

Abstract:

It is a great challenge to track an object robustly when variations occur such as changes in illumination, appearance or partial occlusion. In this paper, we propose a target tracking algorithm combining superpixel and hybrid Hough voting. Local features are extracted from the context as supporters to construct a hybrid voting model. By this model, the target center is estimated by the Hough voting scheme. Local features are also distinguished to vote for the target and background, respectively. These voting results are combined into superpixels. Finally, the tracking task is formulated as the maximum a posterior estimate in the voting space. We demonstrate the performance of the algorithm on several public video sequences, which shows that our method is better than other online tracking approaches.

Key words: visual tracking, local features, segmentation, Hough transforms

HE Wenhua;LIU Zhijing;QU Jianming. Online visual tracking method based on superpixel hybrid voting[J].J4, 2015, 42(3): 61-66.

References

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Online visual tracking method based on superpixel hybrid voting

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