Player Performance Analysis in Sports: with Fusion of Machine Learning and Wearable Technology

Goud, Prakash; Roopa, Y. Mohana; Padmaja, B.

doi:10.1109/iccmc.2019.8819815

Cited by 7 publications

(1 citation statement)

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“…In sports such as table tennis [200], squash [201,202], and golf [203], ball detection and tracking and player pose detection [204] are challenging tasks. In ball-centric sports such as rugby, American football, handball, baseball, ball/player detection [205][206][207][208][209][210][211] and tracking [212][213][214][215][216][217][218][219][220][221], analyzing the action of the player [23,[222][223][224][225][226][227], event detection and classification [228][229][230][231][232], performance analysis of player [233][234][235], referee identification and gesture recognition are the major challenging tasks. Video highlight generation is a subclass of video summarization [236][237][238][239] which may be viewed as a subclass of sports video analysis.…”

Section: Miscellaneousmentioning

confidence: 99%

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

2022

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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.

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