Exploration of Player Behaviours from Broadcast Badminton Videos

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dc.contributor.authorChen, Wei‐Tingen_US
dc.contributor.authorWu, Hsiang‐Yunen_US
dc.contributor.authorShih, Yun‐Anen_US
dc.contributor.authorWang, Chih‐Chuanen_US
dc.contributor.authorWang, Yu‐Shuenen_US
dc.contributor.editorHauser, Helwig and Alliez, Pierreen_US
dc.date.accessioned2023-10-06T11:58:49Z
dc.date.available2023-10-06T11:58:49Z
dc.date.issued2023
dc.description.abstractUnderstanding an opposing player's behaviours and weaknesses is often the key to winning a badminton game. This study presents a system to extract game data from broadcast badminton videos, and visualize the extracted data to help coaches and players develop effective tactics. Specifically, we apply state‐of‐the‐art machine learning methods to partition a broadcast video into segments, in which each video segment shows a badminton rally. Next, we detect players' feet in each video frame and transform the player positions into the court coordinate system. Finally, we detect hit frames in each rally, in which the shuttle moves towards the opposite directions. By visualizing the extracted data, our system conveys when and where players hit the shuttle in historical games. Since players tend to smash or drop shuttles under a specific location, we provide users with interactive tools to filter data and focus on the distributions conditioned by player positions. This strategy also reduces visual clutter. Besides, our system plots the shuttle hitting distributions side‐by‐side, enabling visual comparison and analysis of player behaviours under different conditions. The results and the use cases demonstrate the feasibility of our system.en_US
dc.description.number6
dc.description.sectionheadersORIGINAL ARTICLES
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume42
dc.identifier.doi10.1111/cgf.14786
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14786
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14786
dc.publisher© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.en_US
dc.subjectBadminton
dc.subjectplayer behaviour
dc.subjectvisual analytics
dc.titleExploration of Player Behaviours from Broadcast Badminton Videosen_US
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