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2Trax3: Raising Accessibility and Everyday Use of Automatic Motion Analysis in (Combat) Sports via ML Enhanced 2D to 3D Estimation Algorithms

Topics: Augmented Reality, Exergames and Virtual Sports; Coaching Support Technology; Machine Learning in Sports Performance Prediction; Multimedia and Information Technology; Signal Analysis & Device Engineering; Sport Biomechanics; Sports Statistics and Analyses; Training and Testing

Authors: Samir Duvelek 1 ; Dominik Hoelbling 1 ; René Baranyi 1 ; Roland Breiteneder 1 ; Karl Pinter 1 and Thomas Grechenig 1 ; 2

Affiliations: 1 Research Group for Industrial Software (INSO), Vienna University of Technology, Vienna, Austria ; 2 RISE Institute of Technology, Sri Sathya Sai District, Andhra Pradesh, India

Keyword(s): Motion Capturing, Video Analysis, Kinematic, Martial Arts, Kicking Techniques, Artificial Intelligence.

Abstract: A sound technique forms the fundamental basis for many sports, particularly Martial Arts, as it often distinguishes between successful hits and being hit. However, the process of improving one’s technique is highly intricate, often requiring expert feedback and expensive technology such as 3D motion capturing. The integration of automated technique analysis has the potential to streamline this process and make it more accessible. In this study, the aim is to democratize technique analysis by developing and evaluating a web application. This application allows users to upload 2D video recordings of themselves performing the double side kick technique and receive immediate feedback. To validate the analysis generated by the application, it was compared to a Vicon motion app 3D analysis of the same data from a preliminary study involving 44 participants. The results of Bland-Altman plot analysis demonstrated a highly significant agreement between the 3D and 2D performance indicato rs (Mean differences: relative phase duration: <0.04s; vector spreading angle: <15 degrees; relative body position <13%), indicating that the web application is a suitable tool for fast and effective motion analysis. (More)

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Paper citation in several formats:
Duvelek, S.; Hoelbling, D.; Baranyi, R.; Breiteneder, R.; Pinter, K. and Grechenig, T. (2023). 2Trax3: Raising Accessibility and Everyday Use of Automatic Motion Analysis in (Combat) Sports via ML Enhanced 2D to 3D Estimation Algorithms. In Proceedings of the 11th International Conference on Sport Sciences Research and Technology Support - icSPORTS; ISBN 978-989-758-673-6; ISSN 2184-3201, SciTePress, pages 128-135. DOI: 10.5220/0012165200003587

@conference{icsports23,
author={Samir Duvelek. and Dominik Hoelbling. and René Baranyi. and Roland Breiteneder. and Karl Pinter. and Thomas Grechenig.},
title={2Trax3: Raising Accessibility and Everyday Use of Automatic Motion Analysis in (Combat) Sports via ML Enhanced 2D to 3D Estimation Algorithms},
booktitle={Proceedings of the 11th International Conference on Sport Sciences Research and Technology Support - icSPORTS},
year={2023},
pages={128-135},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012165200003587},
isbn={978-989-758-673-6},
issn={2184-3201},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Sport Sciences Research and Technology Support - icSPORTS
TI - 2Trax3: Raising Accessibility and Everyday Use of Automatic Motion Analysis in (Combat) Sports via ML Enhanced 2D to 3D Estimation Algorithms
SN - 978-989-758-673-6
IS - 2184-3201
AU - Duvelek, S.
AU - Hoelbling, D.
AU - Baranyi, R.
AU - Breiteneder, R.
AU - Pinter, K.
AU - Grechenig, T.
PY - 2023
SP - 128
EP - 135
DO - 10.5220/0012165200003587
PB - SciTePress