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Authors: Paulo Barbosa 1 ; Pedro Cunha 1 ; 2 ; Vítor Carvalho 1 ; 2 and Filomena Soares 2

Affiliations: 1 12Ai - School of Technology, IPCA, Barcelos, Portugal ; 2 Algoritmi Research Centre, University of Minho, Guimarães, Portugal

Keyword(s): Deep Learning, Human Action Recognition, Neural Networks, Computer Vision, Taekwondo.

Abstract: Research in motion analysis area has enabled the development of affordable and easy to access technological solutions. The study presented aims to identify and quantify the movements performed by a taekwondo athlete during training sessions using deep learning techniques applied to the data collected in real time. For this purpose, several approaches and methodologies were tested along with a dataset previously developed in order to define which one presents the best results. Considering the specificities of the movements, usually fast and mostly with a high incidence on the legs, it was concluded that the best results were obtained with convolution layers models, such as, Convolutional Neural Networks (CNN) plus Long Short-Term Memory (LSTM) and Convolutional Long Short-Term Memory (ConvLSTM) deep learning models, with more than 90% in terms of accuracy validation.

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Paper citation in several formats:
Barbosa, P.; Cunha, P.; Carvalho, V. and Soares, F. (2021). Classification of Taekwondo Techniques using Deep Learning Methods: First Insights. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - BIODEVICES; ISBN 978-989-758-490-9; ISSN 2184-4305, SciTePress, pages 201-208. DOI: 10.5220/0010412400002865

@conference{biodevices21,
author={Paulo Barbosa. and Pedro Cunha. and Vítor Carvalho. and Filomena Soares.},
title={Classification of Taekwondo Techniques using Deep Learning Methods: First Insights},
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - BIODEVICES},
year={2021},
pages={201-208},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010412400002865},
isbn={978-989-758-490-9},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - BIODEVICES
TI - Classification of Taekwondo Techniques using Deep Learning Methods: First Insights
SN - 978-989-758-490-9
IS - 2184-4305
AU - Barbosa, P.
AU - Cunha, P.
AU - Carvalho, V.
AU - Soares, F.
PY - 2021
SP - 201
EP - 208
DO - 10.5220/0010412400002865
PB - SciTePress