Classification of Taekwondo Techniques using Deep Learning Methods: First Insights
Paulo Barbosa, Pedro Cunha, Pedro Cunha, Vítor Carvalho, Vítor Carvalho, Filomena Soares
2021
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.
DownloadPaper Citation
in EndNote Style
TY - CONF
JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 1: BIODEVICES
TI - Classification of Taekwondo Techniques using Deep Learning Methods: First Insights
SN - 978-989-758-490-9
AU - Barbosa P.
AU - Cunha P.
AU - Carvalho V.
AU - Soares F.
PY - 2021
SP - 201
EP - 208
DO - 10.5220/0010412400002865
PB - SciTePress
in Harvard Style
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) - Volume 1: BIODEVICES; ISBN 978-989-758-490-9, SciTePress, pages 201-208. DOI: 10.5220/0010412400002865
in Bibtex Style
@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) - Volume 1: BIODEVICES},
year={2021},
pages={201-208},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010412400002865},
isbn={978-989-758-490-9},
}