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Proceedings Paper

Refining initial bounding-box for robust visual tracking
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Paper Abstract

Most of the visual tracking algorithms are very sensitive to the initialized bounding-box of the tracking object, while, how to obtain a precise bounding-box in the first frame needs further research. In this paper, we propose an automatic algorithm to refine the references of the tracking object after a roughly selected bounding-box in the first frame. Based on the input rough location and scale information, the proposed algorithm exploits the region merger algorithm based on maximal similarity to segment the superpixel regions into foreground or background. In order to improve the segmentation effect, a feature clustering strategy is exploited to obtain reliable foreground label and background label and color histogram in HSI space is exploited to describe the superpixel feature. The final refinement bounding-box is the minimal enclosing rectangle of the foreground region. Extensive experiments are performed and the results indicate that the proposed algorithm can reliably refine the initial bounding-box relying only on the first frame information and improve the robustness of the tracking algorithms distinctively.

Paper Details

Date Published: 6 May 2019
PDF: 10 pages
Proc. SPIE 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018), 1106942 (6 May 2019); doi: 10.1117/12.2524220
Show Author Affiliations
Wangsheng Yu, Air Force Engineering Univ. (China)
Xianxiang Qin, Air Force Engineering Univ. (China)
Peng Wang, Air Force Engineering Univ. (China)
Zhiqiang Hou, Xi'an Univ. of Posts and Telecommunications (China)


Published in SPIE Proceedings Vol. 11069:
Tenth International Conference on Graphics and Image Processing (ICGIP 2018)
Chunming Li; Hui Yu; Zhigeng Pan; Yifei Pu, Editor(s)

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