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A novel background-weighted histogram scheme based on foreground saliency for mean-shift tracking

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Abstract

Effective appearance models are one critical factor for robust object tracking. In this paper, we introduce foreground feature saliency concept into the background modelling, and put forward a novel foreground saliency-based background-weighted histogram scheme (FSBWH) for target representation and tracking, which exploits salient features from both foreground and background. We think that background and foreground salient features are both crucial for target representation and tracking. Experimental results show that the proposed FSBWH scheme can improve the robustness and performance of tracker significantly especially in complex occlusions and similar background scenes.

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Notes

  1. An early version of this work was presented in [31].

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Acknowledgments

This work is supported by the National Natural Science Foundation of China (NSFC) under Grant 61300140.

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Authors and Affiliations

  1. School of Computer Science and Technology, Huazhong University of Science and Technology , Wuhan, 430074, China

    Dejun Wang, Weiping Sun, Shengsheng Yu, Lin Li & Wei Liu

  2. Donghua Software Co., Ltd., Beijing, 100190, China

    Dejun Wang

  3. School of Computer Science and Technology, Wuhan University of Technology, Wuhan, 430070, China

    Lin Li

  4. School of Computer Science, Central China Normal University, Wuhan, 430079, China

    Wei Liu

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  1. Dejun Wang
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  2. Weiping Sun
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  3. Shengsheng Yu
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  4. Lin Li
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  5. Wei Liu
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Correspondence to Weiping Sun.

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Wang, D., Sun, W., Yu, S. et al. A novel background-weighted histogram scheme based on foreground saliency for mean-shift tracking. Multimed Tools Appl 75, 10271–10289 (2016). https://doi.org/10.1007/s11042-015-3078-3

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  • DOI: https://doi.org/10.1007/s11042-015-3078-3

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