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Online Visual Tracking pp 87–100Cite as

Correlation Tracking

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Abstract

The correlation filter (CF) has become one of the most widely used formulas in visual tracking for its computation efficiency. With low computational load, the CF-based tracker can exploit large numbers of cyclically shifted samples for learning, thus showing superior performance. However, existing attempts usually focus on the former one while pay less attention to reliability learning, which makes the learned filters dominated by the unexpected salient regions on the feature map, thereby resulting in model degradation.

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Notes

  1. 1.

    ©2018 IEEE, Reprinted, with permission, from ref. [21].

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Authors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Huchuan Lu & Dong Wang

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  1. Huchuan Lu
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  2. Dong Wang
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Correspondence to Huchuan Lu .

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Lu, H., Wang, D. (2019). Correlation Tracking. In: Online Visual Tracking. Springer, Singapore. https://doi.org/10.1007/978-981-13-0469-9_6

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  • DOI: https://doi.org/10.1007/978-981-13-0469-9_6

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  • Print ISBN: 978-981-13-0468-2

  • Online ISBN: 978-981-13-0469-9

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