@article{ART002927622},
author={Jonghyuk Park},
title={The Methodology of the Golf Swing Similarity Measurement Using Deep Learning-Based 2D Pose Estimation},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2023},
volume={28},
number={1},
pages={39-47},
doi={10.9708/jksci.2023.28.01.039}

TY - JOUR
AU - Jonghyuk Park
TI - The Methodology of the Golf Swing Similarity Measurement Using Deep Learning-Based 2D Pose Estimation
JO - Journal of The Korea Society of Computer and Information
PY - 2023
VL - 28
IS - 1
PB - The Korean Society Of Computer And Information
SP - 39
EP - 47
SN - 1598-849X
AB - In this paper, we propose a method to measure the similarity between golf swings in videos. As it is known that deep learning-based artificial intelligence technology is effective in the field of computer vision, attempts to utilize artificial intelligence in video-based sports data analysis are increasing. In this study, the joint coordinates of a person in a golf swing video were obtained using a deep learning-based pose estimation model, and based on this, the similarity of each swing segment was measured. For the evaluation of the proposed method, driver swing videos from the GolfDB dataset were used. As a result of measuring swing similarity by pairing swing videos of a total of 36 players, 26 players evaluated that their other swing sequence was the most similar, and the average ranking of similarity was confirmed to be about 5th. This ensured that the similarity could be measured in detail even when the motion was performed similarly.
KW - Motion similarity;Motion analysis;Golf;Sports;Deep learning;Artificial intelligence
DO - 10.9708/jksci.2023.28.01.039
ER -

Jonghyuk Park. (2023). The Methodology of the Golf Swing Similarity Measurement Using Deep Learning-Based 2D Pose Estimation. Journal of The Korea Society of Computer and Information, 28(1), 39-47.

Jonghyuk Park. 2023, "The Methodology of the Golf Swing Similarity Measurement Using Deep Learning-Based 2D Pose Estimation", Journal of The Korea Society of Computer and Information, vol.28, no.1 pp.39-47. Available from: doi:10.9708/jksci.2023.28.01.039

Jonghyuk Park "The Methodology of the Golf Swing Similarity Measurement Using Deep Learning-Based 2D Pose Estimation" Journal of The Korea Society of Computer and Information 28.1 pp.39-47 (2023) : 39.

Jonghyuk Park. The Methodology of the Golf Swing Similarity Measurement Using Deep Learning-Based 2D Pose Estimation. 2023; 28(1), 39-47. Available from: doi:10.9708/jksci.2023.28.01.039

Jonghyuk Park. "The Methodology of the Golf Swing Similarity Measurement Using Deep Learning-Based 2D Pose Estimation" Journal of The Korea Society of Computer and Information 28, no.1 (2023) : 39-47.doi: 10.9708/jksci.2023.28.01.039

Jonghyuk Park. The Methodology of the Golf Swing Similarity Measurement Using Deep Learning-Based 2D Pose Estimation. Journal of The Korea Society of Computer and Information, 28(1), 39-47. doi: 10.9708/jksci.2023.28.01.039

Jonghyuk Park. The Methodology of the Golf Swing Similarity Measurement Using Deep Learning-Based 2D Pose Estimation. Journal of The Korea Society of Computer and Information. 2023; 28(1) 39-47. doi: 10.9708/jksci.2023.28.01.039

Jonghyuk Park. The Methodology of the Golf Swing Similarity Measurement Using Deep Learning-Based 2D Pose Estimation. 2023; 28(1), 39-47. Available from: doi:10.9708/jksci.2023.28.01.039

Jonghyuk Park. "The Methodology of the Golf Swing Similarity Measurement Using Deep Learning-Based 2D Pose Estimation" Journal of The Korea Society of Computer and Information 28, no.1 (2023) : 39-47.doi: 10.9708/jksci.2023.28.01.039