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Recognition Method of Wushu Human Complex Movement Based on Bone Point Feature

The existing recognition methods of complex human movements in Wushu have the problem of imperfect kinetic energy model, which leads to low recognition accuracy. A complex human motion recognition method based on bone point features is designed. Identify martial arts movement posture, combine the up...

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Detalles Bibliográficos
Autores principales: Li, Anping, Zhang, Ruijie, Tao, Lingrong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050278/
https://www.ncbi.nlm.nih.gov/pubmed/35495885
http://dx.doi.org/10.1155/2022/2287991
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author Li, Anping
Zhang, Ruijie
Tao, Lingrong
author_facet Li, Anping
Zhang, Ruijie
Tao, Lingrong
author_sort Li, Anping
collection PubMed
description The existing recognition methods of complex human movements in Wushu have the problem of imperfect kinetic energy model, which leads to low recognition accuracy. A complex human motion recognition method based on bone point features is designed. Identify martial arts movement posture, combine the upward movement of human center of gravity trajectory, establish the kinetic energy model of joints according to the positioning results of extremity points, set the threshold of local spatial differences of human bones with the central node of hip joint as the center point, avoid overcalculation, and optimize the complex motion identification process by combining the characteristics of bone points. Experimental Results. The correct rate of different types of actions identified by this method is 90.1% and 92.7%, and the identification time is 1.2 s and 1.41 s, which shows that this method can identify actions quickly and effectively by combining the feature information of bone points.
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spelling pubmed-90502782022-04-29 Recognition Method of Wushu Human Complex Movement Based on Bone Point Feature Li, Anping Zhang, Ruijie Tao, Lingrong Comput Math Methods Med Research Article The existing recognition methods of complex human movements in Wushu have the problem of imperfect kinetic energy model, which leads to low recognition accuracy. A complex human motion recognition method based on bone point features is designed. Identify martial arts movement posture, combine the upward movement of human center of gravity trajectory, establish the kinetic energy model of joints according to the positioning results of extremity points, set the threshold of local spatial differences of human bones with the central node of hip joint as the center point, avoid overcalculation, and optimize the complex motion identification process by combining the characteristics of bone points. Experimental Results. The correct rate of different types of actions identified by this method is 90.1% and 92.7%, and the identification time is 1.2 s and 1.41 s, which shows that this method can identify actions quickly and effectively by combining the feature information of bone points. Hindawi 2022-04-21 /pmc/articles/PMC9050278/ /pubmed/35495885 http://dx.doi.org/10.1155/2022/2287991 Text en Copyright © 2022 Anping Li et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Li, Anping
Zhang, Ruijie
Tao, Lingrong
Recognition Method of Wushu Human Complex Movement Based on Bone Point Feature
title Recognition Method of Wushu Human Complex Movement Based on Bone Point Feature
title_full Recognition Method of Wushu Human Complex Movement Based on Bone Point Feature
title_fullStr Recognition Method of Wushu Human Complex Movement Based on Bone Point Feature
title_full_unstemmed Recognition Method of Wushu Human Complex Movement Based on Bone Point Feature
title_short Recognition Method of Wushu Human Complex Movement Based on Bone Point Feature
title_sort recognition method of wushu human complex movement based on bone point feature
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050278/
https://www.ncbi.nlm.nih.gov/pubmed/35495885
http://dx.doi.org/10.1155/2022/2287991
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