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Conference Paper A Study on Sports Player Tracking based on Video using Deep Learning
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Authors
JungSoo Lee, Sungwon Moon, Do-Won Nam, Jiwon Lee, Ah Reum Oh, Wonyoung Yoo
Issue Date
2020-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2020, pp.1161-1163
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC49870.2020.9289223
Abstract
Tracking the players in the game is essential for the correct evaluation of the players. In order to obtain evaluation indicators for players, such as the moving distance and average speed during a game, it is necessary to continuously track the location and trajectory of the player. The players' movement and events' analysis in the games are mainly recorded by professional analysts. To compensate for this, some sports fields use image processing tools for player tracking and event analysis. In this paper, we study the method that shows excellent performance in the detection and tracking objects recently using deep learning, and discuss how to apply it to sports field.
KSP Keywords
Average speed, Detection and tracking, Evaluation indicators, Image processing(IP), Moving distance, Player Tracking, Processing tools, Tracking objects, deep learning(DL), deep learning tracking, event analysis