In recent years, the increasing number of unmanned aerial vehicles (UAVs) in the low-altitude airspace have not only brought convenience to people’s work and life, but also great threats and challenges. In the process of UAV detection and tracking, there are common problems such as target deformation, target occlusion, and targets being submerged by complex background clutter. This paper proposes an anti-occlusion UAV tracking algorithm for low-altitude complex backgrounds by integrating an attention mechanism that mainly solves the problems of complex backgrounds and occlusion when tracking UAVs. First, extracted features are enhanced by using the SeNet attention mechanism. Second, the occlusion-sensing module is used to judge whether the target is occluded. If the target is not occluded, tracking continues. Otherwise, the LSTM trajectory prediction network is used to predict the UAV position of subsequent frames by using the UAV flight trajectory before occlusion. This study was verified on the OTB-100, GOT-10k and integrated UAV datasets. The accuracy and success rate of integrated UAV datasets were 79% and 50.5% respectively, which were 10.6% and 4.9% higher than those of the SiamCAM algorithm. Experimental results show that the algorithm could robustly track a small UAV in a low-altitude complex background.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Anti-Occlusion UAV Tracking Algorithm with a Low-Altitude Complex Background by Integrating Attention Mechanism


    Beteiligte:
    Chuanyun Wang (Autor:in) / Zhongrui Shi (Autor:in) / Linlin Meng (Autor:in) / Jingjing Wang (Autor:in) / Tian Wang (Autor:in) / Qian Gao (Autor:in) / Ershen Wang (Autor:in)


    Erscheinungsdatum :

    2022




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Tracking Multiple Unmanned Aerial Vehicles through Occlusion in Low-Altitude Airspace

    Sufyan Ali Memon / Hungsun Son / Wan-Gu Kim et al. | DOAJ | 2023

    Freier Zugriff


    A Background Layer Model for Object Tracking through Occlusion

    Zhou, Y. / Tao, H. / IEEE | British Library Conference Proceedings | 2003


    Anti-Occlusion UAV Target Detection Based on Attention Feature Fusion

    Zhu, Xiaoyong / Luo, Cai / Lv, Xinrong et al. | IEEE | 2023