非对称泳姿的无标记光学运动捕捉系统

IF 0.9 Q3 ENGINEERING, MULTIDISCIPLINARY
F. Ferryanto, A. Mahyuddin, M. Nakashima
{"title":"非对称泳姿的无标记光学运动捕捉系统","authors":"F. Ferryanto, A. Mahyuddin, M. Nakashima","doi":"10.5614/j.eng.technol.sci.2022.54.5.3","DOIUrl":null,"url":null,"abstract":"This work presents the development of a markerless optical motion capture system of the front-crawl swimming stroke. The system only uses one underwater camera to record swimming motion in the sagittal plane. The participant in this experiment was a swimmer who is active in the university’s swimming club. The recorded images were then segmented to obtain silhouettes of the participant by a Gaussian Mixture Model. One of the swimming images was employed to generate a human body model that consists of 15 segments. The silhouette and model of the participant were subjected to an image matching process. The shape of the body segment was used as the feature in the image matching. The model was transformed to estimate the pose of the participant. The intraclass correlation coefficient between the results of the developed system and references were evaluated. In general, all body segments, except head and trunk, had a correlation coefficient higher than 0.95. Then, dynamics analysis by SWUM was conducted based on the joint angle acquired by the present work. The simulation implied that the developed system was suitable for daily training of athletes and coaches due to its simplicity and accuracy.","PeriodicalId":15689,"journal":{"name":"Journal of Engineering and Technological Sciences","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Markerless Optical Motion Capture System for Asymmetrical Swimming Stroke\",\"authors\":\"F. Ferryanto, A. Mahyuddin, M. Nakashima\",\"doi\":\"10.5614/j.eng.technol.sci.2022.54.5.3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work presents the development of a markerless optical motion capture system of the front-crawl swimming stroke. The system only uses one underwater camera to record swimming motion in the sagittal plane. The participant in this experiment was a swimmer who is active in the university’s swimming club. The recorded images were then segmented to obtain silhouettes of the participant by a Gaussian Mixture Model. One of the swimming images was employed to generate a human body model that consists of 15 segments. The silhouette and model of the participant were subjected to an image matching process. The shape of the body segment was used as the feature in the image matching. The model was transformed to estimate the pose of the participant. The intraclass correlation coefficient between the results of the developed system and references were evaluated. In general, all body segments, except head and trunk, had a correlation coefficient higher than 0.95. Then, dynamics analysis by SWUM was conducted based on the joint angle acquired by the present work. The simulation implied that the developed system was suitable for daily training of athletes and coaches due to its simplicity and accuracy.\",\"PeriodicalId\":15689,\"journal\":{\"name\":\"Journal of Engineering and Technological Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2022-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Engineering and Technological Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5614/j.eng.technol.sci.2022.54.5.3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Engineering and Technological Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5614/j.eng.technol.sci.2022.54.5.3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

这项工作介绍了一种无标记的前爬行游泳动作光学捕捉系统的开发。该系统只使用一台水下摄像机来记录矢状面上的游泳运动。这个实验的参与者是一名活跃在大学游泳俱乐部的游泳运动员。然后通过高斯混合模型对记录的图像进行分割以获得参与者的轮廓。其中一个游泳图像被用于生成由15个片段组成的人体模型。参与者的轮廓和模型经过图像匹配过程。在图像匹配中使用身体片段的形状作为特征。对模型进行了转换,以估计参与者的姿势。评估了所开发系统的结果与参考文献之间的组内相关系数。一般来说,除头部和躯干外,所有身体节段的相关系数都高于0.95。然后,基于本工作获得的关节角度,利用SWUM进行了动力学分析。仿真结果表明,该系统简单、准确,适用于运动员和教练员的日常训练。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Markerless Optical Motion Capture System for Asymmetrical Swimming Stroke
This work presents the development of a markerless optical motion capture system of the front-crawl swimming stroke. The system only uses one underwater camera to record swimming motion in the sagittal plane. The participant in this experiment was a swimmer who is active in the university’s swimming club. The recorded images were then segmented to obtain silhouettes of the participant by a Gaussian Mixture Model. One of the swimming images was employed to generate a human body model that consists of 15 segments. The silhouette and model of the participant were subjected to an image matching process. The shape of the body segment was used as the feature in the image matching. The model was transformed to estimate the pose of the participant. The intraclass correlation coefficient between the results of the developed system and references were evaluated. In general, all body segments, except head and trunk, had a correlation coefficient higher than 0.95. Then, dynamics analysis by SWUM was conducted based on the joint angle acquired by the present work. The simulation implied that the developed system was suitable for daily training of athletes and coaches due to its simplicity and accuracy.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Engineering and Technological Sciences
Journal of Engineering and Technological Sciences ENGINEERING, MULTIDISCIPLINARY-
CiteScore
2.30
自引率
11.10%
发文量
77
审稿时长
24 weeks
期刊介绍: Journal of Engineering and Technological Sciences welcomes full research articles in the area of Engineering Sciences from the following subject areas: Aerospace Engineering, Biotechnology, Chemical Engineering, Civil Engineering, Electrical Engineering, Engineering Physics, Environmental Engineering, Industrial Engineering, Information Engineering, Mechanical Engineering, Material Science and Engineering, Manufacturing Processes, Microelectronics, Mining Engineering, Petroleum Engineering, and other application of physical, biological, chemical and mathematical sciences in engineering. Authors are invited to submit articles that have not been published previously and are not under consideration elsewhere.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信