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Conference Paper: SkillVis: A visualization tool for boxing skill assessment

TitleSkillVis: A visualization tool for boxing skill assessment
Authors
KeywordsDimensionality reduction
Information visualization
Motion graph
Issue Date2016
Citation
9th International Conference on Motion in Games (MIG 2016), San Francisco, CA, 10-12 October 2016. In MIG '16: Proceedings of the 9th International Conference on Motion in Games, 2016, p. 145-153 How to Cite?
AbstractMotion analysis and visualization are crucial in sports science for sports training and performance evaluation. While primitive computational methods have been proposed for simple analysis such as postures and movements, few can evaluate the high-level quality of sports players such as their skill levels and strategies. We propose a visualization tool to help visualizing boxers' motions and assess their skill levels. Our system automatically builds a graph-based representation from motion capture data and reduces the dimension of the graph onto a 3D space so that it can be easily visualized and understood. In particular, our system allows easy understanding of the boxer's boxing behaviours, preferred actions, potential strength and weakness. We demonstrate the effectiveness of our system on different boxers' motions. Our system not only serves as a tool for visualization, it also provides intuitive motion analysis that can be further used beyond sports science.
Persistent Identifierhttp://hdl.handle.net/10722/288723
ISBN

 

DC FieldValueLanguage
dc.contributor.authorShum, Hubert P.H.-
dc.contributor.authorWang, He-
dc.contributor.authorHo, Edmond S.L.-
dc.contributor.authorKomura, Taku-
dc.date.accessioned2020-10-12T08:05:42Z-
dc.date.available2020-10-12T08:05:42Z-
dc.date.issued2016-
dc.identifier.citation9th International Conference on Motion in Games (MIG 2016), San Francisco, CA, 10-12 October 2016. In MIG '16: Proceedings of the 9th International Conference on Motion in Games, 2016, p. 145-153-
dc.identifier.isbn9781450345927-
dc.identifier.urihttp://hdl.handle.net/10722/288723-
dc.description.abstractMotion analysis and visualization are crucial in sports science for sports training and performance evaluation. While primitive computational methods have been proposed for simple analysis such as postures and movements, few can evaluate the high-level quality of sports players such as their skill levels and strategies. We propose a visualization tool to help visualizing boxers' motions and assess their skill levels. Our system automatically builds a graph-based representation from motion capture data and reduces the dimension of the graph onto a 3D space so that it can be easily visualized and understood. In particular, our system allows easy understanding of the boxer's boxing behaviours, preferred actions, potential strength and weakness. We demonstrate the effectiveness of our system on different boxers' motions. Our system not only serves as a tool for visualization, it also provides intuitive motion analysis that can be further used beyond sports science.-
dc.languageeng-
dc.relation.ispartofMIG '16: Proceedings of the 9th International Conference on Motion in Games-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectDimensionality reduction-
dc.subjectInformation visualization-
dc.subjectMotion graph-
dc.titleSkillVis: A visualization tool for boxing skill assessment-
dc.typeConference_Paper-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1145/2994258.2994266-
dc.identifier.scopuseid_2-s2.0-84994893811-
dc.identifier.spage145-
dc.identifier.epage153-

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