Posture-Based and Action-Based Graphs for Boxing Skill Visualization

Yijun Shen, He Wang, Edmond S. L. Ho, Longzhi Yang and Hubert P. H. Shum
Computers and Graphics (C&G), 2017

 Impact Factor: 2.5 Citation: 18#

Posture-Based and Action-Based Graphs for Boxing Skill Visualization
# According to Google Scholar 2023"

Abstract

Automatic evaluation of sports skills has been an active research area. However, most of the existing research focuses on low-level features such as movement speed and strength. In this work, we propose a framework for automatic motion analysis and visualization, which allows us to evaluate high-level skills such as the richness of actions, the flexibility of transitions and the unpredictability of action patterns. The core of our framework is the construction and visualization of the posture-based graph that focuses on the standard postures for launching and ending actions, as well as the action-based graph that focuses on the preference of actions and their transition probability. We further propose two numerical indices, the Connectivity Index and the Action Strategy Index, to assess skill level according to the graph. We demonstrate our framework with motions captured from different boxers. Experimental results demonstrate that our system can effectively visualize the strengths and weaknesses of the boxers.

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BibTeX

@article{shen17posture,
 author={Shen, Yijun and Wang, He and Ho, Edmond S. L. and Yang, Longzhi and Shum, Hubert P. H.},
 journal={Computers and Graphics},
 title={Posture-Based and Action-Based Graphs for Boxing Skill Visualization},
 year={2017},
 volume={69},
 number={Supplement C},
 pages={104--115},
 numpages={13},
 doi={10.1016/j.cag.2017.09.007},
 issn={0097-8493},
 publisher={Elsevier},
}

RIS

TY  - JOUR
AU  - Shen, Yijun
AU  - Wang, He
AU  - Ho, Edmond S. L.
AU  - Yang, Longzhi
AU  - Shum, Hubert P. H.
T2  - Computers and Graphics
TI  - Posture-Based and Action-Based Graphs for Boxing Skill Visualization
PY  - 2017
VL  - 69
IS  - Supplement C
SP  - 104
EP  - 115
DO  - 10.1016/j.cag.2017.09.007
SN  - 0097-8493
PB  - Elsevier
ER  - 

Plain Text

Yijun Shen, He Wang, Edmond S. L. Ho, Longzhi Yang and Hubert P. H. Shum, "Posture-Based and Action-Based Graphs for Boxing Skill Visualization," Computers and Graphics, vol. 69, no. Supplement C, pp. 104-115, Elsevier, 2017.

Supporting Grants

Northumbria University

Postgraduate Research Scholarship (Ref: ): £65,000, Principal Investigator ()
Received from Faculty of Engineering and Environment, Northumbria University, UK, 2015-2018
Project Page

Similar Research

Hubert P. H. Shum, He Wang, Edmond S. L. Ho and Taku Komura, "SkillVis: A Visualization Tool for Boxing Skill Assessment", Proceedings of the 2016 ACM International Conference on Motion in Games (MIG), 2016
Hubert P. H. Shum, Taku Komura and Akinori Nagano, "Automatic Evaluation of Boxing Techniques from Captured Shadow Boxing Data", Proceedings of the 2007 Congress of International Society of Biomechanics (ISB), 2007
Jake Hall, Jacky C. P. Chan, Hubert P. H. Shum and Edmond S. L. Ho, "An Interactive Motion Analysis Framework for Diagnosing and Rectifying Potential Injuries Caused Through Resistance Training", Proceedings of the 2019 ACM SIGGRAPH Conference on Motion, Interaction and Games (MIG) Posters, 2019
Pierre Plantard, Hubert P. H. Shum and Franck Multon, "Motion Analysis of Work Conditions using Commercial Depth Cameras in Real Industrial Conditions", DHM and Posturography, 2019
Kanglei Zhou, Yue Ma, Hubert P. H. Shum and Xiaohui Liang, "Hierarchical Graph Convolutional Networks for Action Quality Assessment", IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2023

 

 

Last updated on 4 June 2024
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