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Computer Vision and Advanced Computational Algorithms for Risk Assessment and Performance Enhancement in Track and Field Teaching
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Author(s): Liming Cui (Faculty of Tai Chi Boxing, Jiaozuo University, China)and Lemin Li (Faculty of Foreign Language and Business, Jiaozuo Normal College, China)
Copyright: 2025
Volume: 21
Issue: 1
Pages: 21
Source title:
International Journal of e-Collaboration (IJeC)
Editor(s)-in-Chief: Jingyuan Zhao (University of Toronto, Canada)
DOI: 10.4018/IJeC.367573
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Abstract
This paper discusses the application of computer vision and advanced calculation algorithm in evaluating the teaching risk and teaching effect of track and field. Because of the inherent uncertainty and risk of PE and sports activities (especially track and field), it is necessary to establish an effective risk management mechanism. Using computer vision technology, this paper puts forward a method of analyzing and processing video data to detect and track moving objects, so as to identify potential risks in real time. This method not only improves the safety of students in track and field classes, but also provides valuable insights for improving teaching methods and reducing sports injuries. This paper discusses the background subtraction motion detection algorithm, which is very important for dynamic image modeling and shadow suppression, and can realize accurate motion state detection. The ultimate goal is to ensure the healthy development of school sports and optimize the teaching results of track and field sports.
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