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Correlation Filter of Multiple Candidates Match for Anti-Obscure Tracking in Unmanned Aerial Vehicle Scenario

Author

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  • Zhen Chen

    (College of Computer Science and Technology/College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing 211006, China)

  • Hongyuan Zheng

    (College of Computer Science and Technology/College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing 211006, China
    Key Laboratory of Safety-Critical Software, Ministry of Industry and Information Technology, Nanjing 211106, China)

  • Xiangping (Bryce) Zhai

    (College of Computer Science and Technology/College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing 211006, China
    Key Laboratory of Safety-Critical Software, Ministry of Industry and Information Technology, Nanjing 211106, China)

  • Kangliang Zhang

    (College of Computer Science and Technology/College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing 211006, China)

  • Hua Xia

    (College of Computer Science and Technology/College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing 211006, China)

Abstract

Due to the complexity of Unmanned Aerial Vehicle (UAV) target tracking scenarios, tracking drift caused by target occlusion is common and has no suitable solution. In this paper, an occlusion-resistant target tracking algorithm based on the correlated filter tracking model is proposed. First, instead of the traditional target tracking model that uses single template matching to locate the target, we locate the target by finding the optimal match based on multiple candidates templates matching. Then, in order to increase the accuracy of matching, we use the self-attentive mechanism for feature enhancement. We experiment our proposed algorithm on datasets OTB100 and UAV123, respectively, and the results show that the tracking accuracy of our algorithm outperforms the traditional correlated filtered target tracking model. In addition, we have also tested the anti-occlusion performance of our proposed algorithm on some video sequences in which the target is occluded. The results show that our proposed algorithm has a certain resistance to occlusion, especially in the UAV tracking scenario.

Suggested Citation

  • Zhen Chen & Hongyuan Zheng & Xiangping (Bryce) Zhai & Kangliang Zhang & Hua Xia, 2022. "Correlation Filter of Multiple Candidates Match for Anti-Obscure Tracking in Unmanned Aerial Vehicle Scenario," Mathematics, MDPI, vol. 11(1), pages 1-14, December.
    • Handle: RePEc:gam:jmathe:v:11:y:2022:i:1:p:163-:d:1018156
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    References listed on IDEAS

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    1. Alan S. Manne, 1958. "A Target-Assignment Problem," Operations Research, INFORMS, vol. 6(3), pages 346-351, June.
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