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Authors: Ayaka Shimazu 1 ; Chun Xie 2 ; Satoru Tanigawa 3 and Itaru Kitahara 2

Affiliations: 1 Master’s and Doctoral Program in Intelligent Mechanical Interaction Systems, University of Tsukuba, Ibaraki, Japan ; 2 Center for Computational Sciences, University of Tsukuba, Ibaraki, Japan ; 3 Faculty of Health and Sport Sciences, University of Tsukuba, Ibaraki, Japan

Keyword(s): 3D Human Pose Estimation, Performance Analysis, Pseudo-Binocular Filming, Time-Warping.

Abstract: Motion analysis utilizing human pose estimation has garnered increasing attention within sports science, serving both preventive medicine and skill enhancement purposes. While techniques using 3D trackers and RGB-D cameras to estimate human poses are gaining attention, the widespread adoption is hindered by the requirement for extensive space and specialized equipment. This paper introduces a novel method to estimate the 3D human pose using RGB video data captured from 'pseudo' two-viewpoints. This approach involves performing the same motion in different directions and recording with a single camera. We confirm that the accuracy of 3D human pose estimation from video taken by a single camera is improved by the pseudo-two-viewpoints recording compared to existing methods using a single monocular RGB camera.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Shimazu, A., Xie, C., Tanigawa, S. and Kitahara, I. (2024). A Human Pose Estimation Method from Pseudo-Captured Two-Viewpoints Video. In Proceedings of the 12th International Conference on Sport Sciences Research and Technology Support - icSPORTS; ISBN 978-989-758-719-1; ISSN 2184-3201, SciTePress, pages 148-154. DOI: 10.5220/0012921400003828

@conference{icsports24,
author={Ayaka Shimazu and Chun Xie and Satoru Tanigawa and Itaru Kitahara},
title={A Human Pose Estimation Method from Pseudo-Captured Two-Viewpoints Video},
booktitle={Proceedings of the 12th International Conference on Sport Sciences Research and Technology Support - icSPORTS},
year={2024},
pages={148-154},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012921400003828},
isbn={978-989-758-719-1},
issn={2184-3201},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Sport Sciences Research and Technology Support - icSPORTS
TI - A Human Pose Estimation Method from Pseudo-Captured Two-Viewpoints Video
SN - 978-989-758-719-1
IS - 2184-3201
AU - Shimazu, A.
AU - Xie, C.
AU - Tanigawa, S.
AU - Kitahara, I.
PY - 2024
SP - 148
EP - 154
DO - 10.5220/0012921400003828
PB - SciTePress

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