The main challenge in object tracking is how to track a target in real time and accurately in complex and changing environments. Correlation filters (CFs) have unique advantages in the field of target tracking and are widely used in unmanned aerial vehicle (UAV) platforms. We propose a new tracking algorithm that introduces adaptive background residuals to reduce the environmental interference during tracking. Experimental results on two benchmark datasets show that our tracking algorithm achieves first place in accuracy and success rate compared to nine other state-of-the-art tracking algorithms. Our tracker has excellent tracking performance.


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    Titel :

    Adaptive Background Residual Correlation Filters for UAV Tracking


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Jia, Limin (Herausgeber:in) / Zhang, Qiang (Herausgeber:in) / Xie, Zhengyu (Herausgeber:in) / Li, Haibin (Herausgeber:in) / Yong, Kenan (Herausgeber:in) / Wang, Li (Herausgeber:in) / Liu, Siyuan (Autor:in) / Lin, Junting (Autor:in)

    Kongress:

    International Conference on Artificial Intelligence and Autonomous Transportation ; 2024 ; Beijing, China December 06, 2024 - December 08, 2024



    Erscheinungsdatum :

    19.04.2025


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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