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  • Open Access

    ARTICLE

    Automatic Team Assignment and Jersey Number Recognition in Football Videos

    Ragd Alhejaily1, Rahaf Alhejaily1, Mai Almdahrsh1, Shareefah Alessa1, Saleh Albelwi1,2,*

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2669-2684, 2023, DOI:10.32604/iasc.2023.033062 - 15 March 2023

    Abstract Football is one of the most-watched sports, but analyzing players’ performance is currently difficult and labor intensive. Performance analysis is done manually, which means that someone must watch video recordings and then log each player’s performance. This includes the number of passes and shots taken by each player, the location of the action, and whether or not the play had a successful outcome. Due to the time-consuming nature of manual analyses, interest in automatic analysis tools is high despite the many interdependent phases involved, such as pitch segmentation, player and ball detection, assigning players to… More >

  • Open Access

    ARTICLE

    An Automated Player Detection and Tracking in Basketball Game

    P. K. Santhosh1,*, B. Kaarthick2

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 625-639, 2019, DOI:10.32604/cmc.2019.05161

    Abstract Vision-based player recognition is critical in sports applications. Accuracy, efficiency, and Low memory utilization is alluring for ongoing errands, for example, astute communicates and occasion classification. We developed an algorithm that tracks the movements of different players from a video of a basketball game. With their position tracked, we then proceed to map the position of these players onto an image of a basketball court. The purpose of tracking player is to provide the maximum amount of information to basketball coaches and organizations, so that they can better design mechanisms of defence and attack. Overall,… More >

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