Importance of Biomechanical Pose Analysis of Young Players Using Mobile Videos and Comparing the Efficiency with Classical Biomechanics
Keywords:
Tennis biomechanics, Player pose analysis, Joint accuracy, Spatial Resolution Kinetic Energy Transfer EfficiencyAbstract
Biomechanical analysis in tennis has become a critical area of research, enhancing performance optimization, injury prevention, and technique refinement. This paper explores the significance of biomechanical studies in tennis, highlighting key techniques such as motion capture, force plate analysis, electromyography (EMG), and computational modelling. We analyse how biomechanics influences stroke mechanics, footwork, energy efficiency, and injury mitigation. Furthermore, we compare and discuss recent advancements in deep learning and AI-driven pose estimation for real-time player analysis, comparing them with traditional camera-based techniques.
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Karen Simonyan_ & Andrew Zisserman. Very deep convolutional networks for large-scale image recognition. Published as a conference paper at ICLR 2015. arXiv:1409.1556v6 [cs.CV] 10 Apr 2015
M. Paluri, D. Tran, L. Bourdev, R. Fergus, and L. Torresani, “Learning spatiotemporal features with 3d convolutional networks”, Computer Vision and Pattern Recognition, 2015. arXiv:1412.0767v4 [cs.CV].
Zhe Cao, Tomas Simon, Shih-En Wei, Yaser Sheikh. Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, pp. 7291-7299
Ryunosuke Kurose, Masaki Hayashi, Takeo Ishii "Player Pose Analysis in Tennis Video based on Pose Estimation", International Workshop on Advanced Image Technology (IWAIT) 2018
N. Elliott, S. Choppin, S. R. Goodwill, T. Allen. “Markerless tracking of tennis racket motion using a camera,” Procedia Engineering, Volume 72, 2014, pp. 344-3
Rafael Martínez, ITF Coaching and Sport Science Review 2018; 74 (26) https://www.researchgate.net/publication/324601508
Hughes, M Computerised notation of racket sports. In: Reilly, T, Hughes, M, Lees, A (eds). Science and racket sports, London: E & FN Spon, 1995, pp. 249–256.
Tom Polk, Dominik Jackle, Johannes H ¨ außler, and Jing Yang "CourtTime: Generating Actionable Insights into Tennis Matches Using Visual Analytics", IEEE Transactions on visualization and computer graphics, vol. 26, no. 1, January 2020.
Jiang Wu* Ziyang Guo* Zuobin Wang* Qingyang Xu* Yingcai Wu "Visual Analytics of Multivariate Event Sequence Datain Racquet Sports", 2020 IEEE Conference on Visual Analytics Science and Technology (VAST)
Kovalchik, SA . Searching for the GOAT of tennis win prediction. J Quant Anal Sports 2016; 12: 127–138.
Kovalchik, SA, Reid, M. Comparing matchplay characteristics and physical demands of junior and professional tennis athletes in the era of big data. J Sport Sci Med 2017; 16: 489–497.
Kovalchik, SA, Reid, M. A shot taxonomy in the era of tracking data in professional tennis. J Sport Sci 2018; 36: 2096–2104.
Rajdeep Chatterjee, Soham Roy, SK Hafizul Islam, Debabrata Samanta, "An AI Approach to Pose-based Sports Activity Classification" 2021 8th International Conference on Signal Processing and Integrated Networks (SPIN) | 978-1-6654-3564-2/21/$31.00 ©2021 IEEE | DOI: 10.1109/SPIN52536.2021.9565996.
O’Donoghue, Research Methods for Sports Performance Analysis, ISBN 9780415496230, Published December 14, 2009 by Routledge
Rafael Martín Nieto, José María Martínez Sánchez, "An automatic system for sports analytics in multi-camera tennis videos", Workshop on Activity Monitoring by Multiple Distributed Sensing (AMMDS) in conjunction with 2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance.
Ryota Mukai, Toshio Asano and Hajime Hara, "Analysis and Evaluation of Tennis Plays by Computer Vision", Proceedings of the 2011 IEEE International Conference on Mechatronics and Automation August 7 - 10, Beijing, China
Satoshi Ochi and Mary Jo Campbell. The Progressive Physical Development of a High-Performance Tennis Player Strength and Conditioning Journal 2009. www.nsca-lift.org. pages 59-68.
3D Human Pose Construction Algorithm Based on 2D Node to 3D Model. Meixia Dong; Hongjuan He; Weichuan Ni. 2024 6th International Conference on Data-driven Optimization of Complex Systems (DOCS). Electronic ISBN:979-8-3503-7784-2
Maria Skublewska-Paszkowska, Paweł Karczmarek, Edyta Lukasik, "Tennis Multivariate Time Series Clustering", 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) | 978-1-6654-4407-1/21/$31.00 ©2021 IEEE | DOI: 0.1109/FUZZ45933.2021.9494420
Jhen-Min Hung, Jinn-Yen Chiang and Kerwin Wang. Tennis Player Pose Classification using YOLO and MLP Neural Networks, International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) | 978-1-6654-1951-2/21/$31.00 ©2021 IEEE | DOI: 10.1109/ISPACS51563.2021.9650925
Kevin Schlegel, Lei Jiang , Hao Ni. Using joint angles based on the international biomechanical standards for human action recognition and related tasks. arXiv preprint arXiv:2406.17443, 2024 - arxiv.org
Bruce C Elliott University of Western Australia. Biomechanics and tennis British Journal of Sports Medicine 40(5):392-6. DOI:10.1136/bjsm.2005.023150 June 2006
Biomedical Engineering Principles in Sports (pp.153-181) Chapter: 7. Publisher: Kluwer Editors: Hung, G.K. and Pallis, J.M.
Duane Victor Knudson, Texas State University. Bruce C Elliott, University of Western Australia Biomechanics of Tennis Strokes. DOI:10.1007/978-1-4419-8887-4_7
Modelling of the qualification & improvement of tennis stance for player performance improvement using 2d analysis of videos taken from a mobile camera (part a), Journal of Basic sciences and Engineering. Abhilash Manu et al. DOI: https://doie.org/10.0118/Jbse.2025328537
Mathematical Modelling & Simulation for the Qualification of Tennis Stances Improvement for Sports Player using 2D video analysis using DIP, J. Electrical Systems 20-11s (2024): 2571-2592, Abhilash Manu et al. journal.esrgroups.org
Applications of Computer Vision for Analysing Player Performance in Tennis Sports, European Chemical Bulletin. Abhilash Manu et al. Eur. Chem. Bull. 2023,12(Special Issue 4), 14639-14656
Examining the Effectiveness of K-Means Clustering Using Minkowski Distances on Spatial Data of Tennis Serve Pose for sports players to maintain good health. Abhilash Manu et al. SEEJPH Volume XXV, 2024, ISSN: 2197-5248; Posted:24-10-2024 3143
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