Umpire’s Signal Recognition in Cricket Using an Attention based DC-GRU Network
محل انتشار: ماهنامه بین المللی مهندسی، دوره: 37، شماره: 4
سال انتشار: 1403
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 54
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شناسه ملی سند علمی:
JR_IJE-37-4_008
تاریخ نمایه سازی: 21 بهمن 1402
چکیده مقاله:
Computer vision has extensive applications in various sports domains, and cricket, a complex game with different event types, is no exception. Recognizing umpire signals during cricket matches is essential for fair and accurate decision-making in gameplay. This paper presents the Cricket Umpire Action Video dataset (CUAVd), a novel dataset designed for detecting umpire postures in cricket matches. As the umpire possesses the power to make crucial judgments concerning incidents that occur on the field, this dataset aims to contribute to the advancement of automated systems for umpire recognition in cricket. The proposed Attention-based Deep Convolutional GRU Network accurately detects and classifies various umpire signal actions in video sequences. The method achieved remarkable results on our prepared CUAVd dataset and publicly available datasets, namely HMDB۵۱, Youtube Actions, and UCF۱۰۱. The DC-GRU Attention model demonstrated its effectiveness in capturing temporal dependencies and accurately recognizing umpire signal actions. Compared to other advanced models like traditional CNN architectures, CNN-LSTM with Attention, and the ۳DCNN+GRU model, the proposed model consistently outperformed them in recognizing umpire signal actions. It achieved a high validation accuracy of ۹۴.۳۸% in classifying umpire signal videos correctly. The paper also evaluated the models using performance metrics like F۱-Measure and Confusion Matrix, confirming their effectiveness in recognizing umpire signal actions. The suggested model has practical applications in real-life situations such as sports analysis, referee training, and automated referee assistance systems where precise identification of umpire signals in videos is vital.
کلیدواژه ها:
نویسندگان
A. Dey
Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, India
S. Biswas
Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, India
L. Abualigah
Computer Science Department, Prince Hussein Bin Abdullah Faculty for Information Technology, Al al-Bayt University, Mafra, Jordan
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