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

**Authors:** Banoth Thulasya Naik, Mohammad Farukh Hashmi, Neeraj Dhanraj Bokde  
**arXiv:** [2203.02281](https://arxiv.org/abs/2203.02281)  
**Date:** 2022-03-03  
**Summary page:** https://www.summarizepaper.com/en/paper/2203.02281v2/

## Key points

- Computer vision techniques and video analysis have advanced significantly in recent years for sports applications
- Studies focus on using computer vision to enhance detailed complex analysis in sports such as soccer, basketball, cricket, badminton, etc.
- Applications of sports video analysis include player detection and classification, tracking player or ball movements, predicting trajectories of players or balls, recognizing team strategies, and classifying events in sports fields
- The review provides a comprehensive survey of research carried out in computer vision-based sports video analysis and identifies challenges and future trends
- Artificial intelligence (AI) applications in sports vision are discussed along with GPU-based workstations, embedded platforms, movement recognition, motion analysis, content-aware analysis video summarization wearable technology in sports
- Machine learning and deep learning algorithms can be used for motion capture data processing while discussing the availability of datasets for specific types of sport.

## Summary

In recent years, computer vision techniques and video analysis of sports have made significant advancements, enabling various critical operations. To provide enhanced information for detailed complex analysis in sports such as soccer, basketball, cricket, badminton, etc., studies have mainly focused on employing computer vision techniques to carry out different tasks. This paper presents a comprehensive review of sports video analysis for various applications such as detection and classification of players; tracking player or ball movements; predicting the trajectories of player or ball; recognizing the teams' strategies; and classifying various events in sports fields. The proposed survey aims to establish a pathway for next-generation research in the sports domain by providing a proper and comprehensive survey of research carried out in computer vision-based sports video analysis. The review discusses published works related to application-specific tasks related to sports and the present researchers' views regarding them. Additionally, some publicly available datasets related to specific sports are provided since there is wide research scope in deploying computer vision techniques in various sports. The paper also reviews detailed discussions on some artificial intelligence (AI) applications in sports vision; GPU-based workstations; embedded platforms; movement recognition; motion analysis; content-aware analysis video summarization wearable technology in sports. Furthermore, the review identifies probable challenges and future trends in visual recognition in sports. Overall this review provides users with an ability to understand how computer vision techniques can be employed for high-level analysis such as detecting and classifying players; tracking player or ball movements; recognizing team strategies; classifying various events during gameplay. It also highlights how machine learning and deep learning algorithms can be used for motion capture data processing while discussing the availability of datasets for specific types of sport.