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Single target tracking via correlation filter and context adaptively

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Abstract

Recently, tracking methods based on correlation filter show impressive performance in a variety of complex environments for their excellent classification performance. However, most of the existing methods only focus on the information in the bounding box regions of the target, and do not fully utilized the contextual information and the internal structure information of the target. Thus, when the target scenes experience dramatic change, the learned filter could not accurately adapt to the appearance change, which will lead to model degradation of the target. To address this issue, a novel approach via correlation filter and context jointly is proposed in this paper. First, we decompose the target into multiple independent parts, and each part learns the filtering response separately. Through the joint learning of multiple independent filters, the target model can effectively maintain the structural information of the object and is not sensitive to partial occlusion, and etc. Second, we introduce multi-channel features in the representation based on the parts of the target and the contextual information to migrate the background influences. With the introduction of collaborative representation strategy, the impact of background noise can be effectively suppressed. To evaluate the proposed approach, we conduct extensive experiments on several challenging benchmark datasets including OTB-2013 and OTB-2015 datasets. The results show our method demonstrates comparable performance against several state-of-the-art methods.

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Acknowledgments

This work was partially supported by the National Natural Science Foundation of China (61201429) and Nature Science Research Project of Anhui province (1908085MF217).

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Authors and Affiliations

  1. School of Electrical Engineering and Automation, Anhui University, Hefei, 230601, People’s Republic of China

    Hua Bao, Yixiang Lu & Qijun Wang

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  1. Hua Bao
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  2. Yixiang Lu
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  3. Qijun Wang
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Correspondence to Qijun Wang.

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Bao, H., Lu, Y. & Wang, Q. Single target tracking via correlation filter and context adaptively. Multimed Tools Appl 79, 27465–27482 (2020). https://doi.org/10.1007/s11042-020-09309-3

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  • DOI: https://doi.org/10.1007/s11042-020-09309-3

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