SkillVis: a visualization tool for boxing skill assessment

Shum, H.P.H., Wang, H., Ho, E.S.L. and Komura, T. (2016) SkillVis: a visualization tool for boxing skill assessment. In: MiG '16: Motion In Games, 10 - 12 October 2016, Burlingame, CA, USA, pp. 145-153. ISBN 9781450345927 (doi: 10.1145/2994258.2994266)

Abstract

Motion 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.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Ho, Dr Edmond S. L
• Authors: Shum, H.P.H., Wang, H., Ho, E.S.L., and Komura, T.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: Proceedings - Motion in Games 2016: 9th International Conference on Motion in Games, MIG 2016
• ISBN: 9781450345927
• Copyright Holders: Copyright © 2016 Copyright held by the owner/author(s)
• First Published: First published in MIG '16: Proceedings of the 9th International Conference on Motion in Games
• Publisher Policy: Reproduced under a Creative Commons licence