Target tracking based on the UAV platform is difficult to avoid the problem of large-scale variation. Due to the large change in the relative position between the UAV and the target, the size of the target in the video sequence will also change accordingly, resulting in poor tracking accuracy and low success rate. In order to solve the challenge of large-scale variation, based on the Siamese series of target tracking algorithms, the author proposes two improved methods to optimize the tracking frame and update the template. The optimization process is supplemented by updating the observation model to make it better adapt to the large-scale changes in the relative movement of the UAV and the target. Through the improvement of the target tracking algorithm based on the Siamese network, the target under large-scale transformation can be effectively tracked.


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    Title :

    Target Tracking Under Large-Scale Variation Based on UAV Platform


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Fu, Wenxing (editor) / Gu, Mancang (editor) / Niu, Yifeng (editor) / Jiang, Zijian (author) / Huang, Hanqiao (author) / Guo, Yunhe (author) / Liang, Xiaoxi (author) / He, Xiang (author)

    Conference:

    International Conference on Autonomous Unmanned Systems ; 2022 ; Xi'an, China September 23, 2022 - September 25, 2022



    Publication date :

    2023-03-10


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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