A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions
Open Access
- 27 April 2022
- journal article
- review article
- Published by MDPI AG in Applied Sciences
- Vol. 12 (9), 4429
- https://doi.org/10.3390/app12094429
Abstract
Recent developments in video analysis of sports and computer vision techniques have achieved significant improvements to enable a variety of critical operations. To provide enhanced information, such as detailed complex analysis in sports such as soccer, basketball, cricket, and badminton, studies have focused mainly on computer vision techniques employed to carry out different tasks. This paper presents a comprehensive review of sports video analysis for various applications: high-level analysis such as detection and classification of players, tracking players or balls in sports and predicting the trajectories of players or balls, recognizing the team’s strategies, and classifying various events in sports. The paper further discusses published works in a variety of application-specific tasks related to sports and the present researcher’s views regarding them. Since there is a wide research scope in sports for deploying computer vision techniques in various sports, some of the publicly available datasets related to a particular sport have been discussed. This paper reviews detailed discussion on some of the artificial intelligence (AI) applications, GPU-based work-stations and embedded platforms in sports vision. Finally, this review identifies the research directions, probable challenges, and future trends in the area of visual recognition in sports.Keywords
This publication has 171 references indexed in Scilit:
- A real-time trajectory-based ball detection-and-tracking framework for basketball videoJournal of Optics, 2013
- Soccer Ball Detection by Comparing Different Feature Extraction MethodologiesAdvances in Artificial Intelligence, 2012
- Real Time Colour Based Player Tracking in Indoor SportsPublished by Springer Science and Business Media LLC ,2010
- Space–time coordination dynamics in basketball: Part 2. The interaction between the two teamsJournal of Sports Sciences, 2010
- Space–time coordination dynamics in basketball: Part 1. Intra- and inter-couplings among player dyadsJournal of Sports Sciences, 2010
- Physics-based ball tracking and 3D trajectory reconstruction with applications to shooting location estimation in basketball videoJournal of Visual Communication and Image Representation, 2009
- Prediction of athletes performance using neural networks: An application in cricket team selectionExpert Systems with Applications, 2009
- Automatic player detection, labeling and tracking in broadcast soccer videoPattern Recognition Letters, 2009
- Ball detection from broadcast soccer videos using static and dynamic featuresJournal of Visual Communication and Image Representation, 2008
- Instantly indexed multimedia databases of real world eventsIEEE Transactions on Multimedia, 2002