Marine target recognition and tracking are of great significance for achieving intelligent perception of the marine environment, avoiding ship collisions, and maintaining ship navigation safety. Propose a sea multi-target tracking model based on visual, AIS, and radar data fusion to achieve real-time monitoring of sea navigation targets. Firstly, an imagebased maritime target recognition model is established based on the YOLOv3 algorithm to achieve automatic recognition of maritime navigation targets around ships; Secondly, based on the SORT framework, a maritime navigation target tracking model was established to achieve real-time tracking of multiple targets at sea. The actual ship test results show that the average accuracy, average detection time, average tracking accuracy, and tracking precision of multi-target detection results at sea under different weather conditions can provide effective technical support for multi-target tracking tasks at sea.


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    Titel :

    Research on maritime target detection and tracking based on YOLOv3 and SORT framework


    Beteiligte:
    Liu, Jinping (Herausgeber:in) / Subramaniyam, Kannimuthu (Herausgeber:in) / Baohong, Han (Autor:in)

    Kongress:

    International Conference on Optics and Machine Vision (ICOMV 2024) ; 2024 ; Nanchang, China


    Erschienen in:

    Proc. SPIE ; 13179


    Erscheinungsdatum :

    18.07.2024





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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