A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions

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.

When Taekwondo Meets Artificial Intelligence: The Development of Taekwondo

“…More accurate refereeing decisions are being made in sports such as soccer, tennis, and volleyball through advanced technologies [22].…”

Predicting Football Team Performance with Explainable AI: Leveraging SHAP to Identify Key Team-Level Performance Metrics

“…Moreover, Natural Language Processing techniques were applied for the analysis of the content of news articles, social media posts, and other sources of information to gain insights into the sentiment and emotions of fans, players, and teams [15]. Computer vision techniques [16,17] have been used to analyze video footage of matches to extract data on player and team performance, such as ball possession, passing accuracy, and tactical formation. The use of AI in football predictions is still in its early stages, and most of the current solutions are based on historical data.…”

A court line extraction algorithm for badminton tournament videos with horizontal line projection learning

“…It is essential to develop the sophisticated content‐based analysis techniques for retrieving sport videos efficiently. The researches on sport video analysis have increased largely [1‐23]. The paper [23] has done a comprehensive review of computer vision in sports.…”

“…The researches on sport video analysis have increased largely [1‐23]. The paper [23] has done a comprehensive review of computer vision in sports. In the sport videos, the court line extraction and object detection are the key techniques for the implementation of the tactical analysis and the semantic video retrieval system.…”