Review of computer vision in sports

Xinyu Shao

doi:10.54254/2755-2721/5/20230519

Research Article

Open access

Published on 31 May 2023

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Shao,X. (2023). Review of computer vision in sports. Applied and Computational Engineering,5,28-33.

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Review of computer vision in sports

Xinyu Shao *^,1,

¹ University of Manchester, Manchester, United Kingdom

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/5/20230519

Abstract

All industries employ machine learning extensively, and one of the most promising fields is computer vision. Computer vision is a simulation of the human visual system that uses cameras and computers to take the role of the human eye to find the target, follow it, and gather data from it so that a decision may be made on whether to take further action or provide recommendations. The various uses of computer vision in sports are covered in this paper. Currently, computer vision is mostly utilized for broadcast enhancement, tracking and detection of players and balls. Although the game’s graphics has been substantially improved by this technology, there are still several flaws. For instance, some areas are not suited to employ this technology. Another is the issue of players being blocked in multiplayer sports. For broadcasters, computer vision has significant commercial value. For athletes, this technique can improve their performance.

Keywords

Machine Learning, Computer Vision, Sport, Tracking, Detection, Broadcast Enhancements.

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References

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Cite this article

Shao,X. (2023). Review of computer vision in sports. Applied and Computational Engineering,5,28-33.

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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 3rd International Conference on Signal Processing and Machine Learning

Conference website: http://www.confspml.org

ISBN：978-1-915371-57-7(Print) / 978-1-915371-58-4(Online)

Conference date: 25 February 2023

Editor：Omer Burak Istanbullu

Series: Applied and Computational Engineering

Volume number: Vol.5

ISSN：2755-2721(Print) / 2755-273X(Online)

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