Abstract
The advancement in information and communication technologies (ICTs) has contributed to the popularity of campus football among college students in recent years. ICT in football has given rise to the video assistant referee (VAR) platform that integrates big data, machine vision, cloud computing and the Internet of Things for decision-making. The popularity of VAR platform means various research areas need to be explored to enhance decision-making efficiency in football matches. Among them, event management is an important research direction that needs to be explored to analyze the series of events by using 3D images and pixels. This paper focuses on the event management system for campus football by analyzing the administration system and suggests a machine vision approach by using an underlying neural network. Images of three different regions, A, B, and C, were used as the experimental objects in this work. This paper analyzes machine vision, a discrete Hopfield neural network, to establish a Hopfield model for recognizing cross-line types.
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LZ wrote the main manuscript text and ZL prepared figures and Tables. All authors reviewed the manuscript.
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Zhang, L., Liu, Z. Designing an event management system for campus football using 3D images and machine vision. SIViP 18, 2965–2974 (2024). https://doi.org/10.1007/s11760-023-02963-8
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DOI: https://doi.org/10.1007/s11760-023-02963-8