3D Kinematic Analysis of Intelligent Vision Sensor Image in Football Training

With its advantages of high precision, noncontact, and high intelligence, intelligent visual sensor detection technology meets the requirements for online detection of motion status and intelligent recognition of motion images during sports activities, and its applications are becoming more and more...

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Autores principales:	Pengcheng Ni, Xi Luo
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Technology (General) T1-995
Acceso en línea:	https://doaj.org/article/40f2d174597f4adc973789e5159342eb
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spelling	oai:doaj.org-article:40f2d174597f4adc973789e5159342eb2021-11-22T01:09:41Z3D Kinematic Analysis of Intelligent Vision Sensor Image in Football Training1687-726810.1155/2021/3307902https://doaj.org/article/40f2d174597f4adc973789e5159342eb2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/3307902https://doaj.org/toc/1687-7268With its advantages of high precision, noncontact, and high intelligence, intelligent visual sensor detection technology meets the requirements for online detection of motion status and intelligent recognition of motion images during sports activities, and its applications are becoming more and more extensive. In order to deeply explore the feasibility of using intelligent vision sensor technology to analyze the three-dimensional action of football, this article uses algorithm analysis method, technology summary method, and physical assembly method, collects samples, analyzes the motion model, streamlines the algorithm, and then creates a model based on intelligent visual sensor technology that can analyze the three-dimensional movement in football training. After the experimental objects are selected, the model is established in the ADM environment. All athletes do a uniform motion, the standard input motion speed is 5 m/s, they all move in the opposite direction relative to their respective coordinate axes, and the motion time is 6 seconds. The results show that the movement curves of the athletes in the three coordinate axis directions are basically the same. When the exercise time is 6 seconds, the coordinate values of the athletes on the three coordinate axes are all 0.992 m. We set six intensities in the experiment: 5%, 15%, 25%, 35%, 45%, and 55%. It can be found that as the noise intensity increases from 5% to 45%, the estimation error gradually increases, but as a whole, it is still at a relatively small level. It shows that the algorithm in this paper still has practical significance. It is basically realized that under the guidance of intelligent vision sensor technology, a model can be designed to successfully and efficiently analyze the three-dimensional movement pattern in training.Pengcheng NiXi LuoHindawi LimitedarticleTechnology (General)T1-995ENJournal of Sensors, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology (General) T1-995
spellingShingle	Technology (General) T1-995 Pengcheng Ni Xi Luo 3D Kinematic Analysis of Intelligent Vision Sensor Image in Football Training
description	With its advantages of high precision, noncontact, and high intelligence, intelligent visual sensor detection technology meets the requirements for online detection of motion status and intelligent recognition of motion images during sports activities, and its applications are becoming more and more extensive. In order to deeply explore the feasibility of using intelligent vision sensor technology to analyze the three-dimensional action of football, this article uses algorithm analysis method, technology summary method, and physical assembly method, collects samples, analyzes the motion model, streamlines the algorithm, and then creates a model based on intelligent visual sensor technology that can analyze the three-dimensional movement in football training. After the experimental objects are selected, the model is established in the ADM environment. All athletes do a uniform motion, the standard input motion speed is 5 m/s, they all move in the opposite direction relative to their respective coordinate axes, and the motion time is 6 seconds. The results show that the movement curves of the athletes in the three coordinate axis directions are basically the same. When the exercise time is 6 seconds, the coordinate values of the athletes on the three coordinate axes are all 0.992 m. We set six intensities in the experiment: 5%, 15%, 25%, 35%, 45%, and 55%. It can be found that as the noise intensity increases from 5% to 45%, the estimation error gradually increases, but as a whole, it is still at a relatively small level. It shows that the algorithm in this paper still has practical significance. It is basically realized that under the guidance of intelligent vision sensor technology, a model can be designed to successfully and efficiently analyze the three-dimensional movement pattern in training.
format	article
author	Pengcheng Ni Xi Luo
author_facet	Pengcheng Ni Xi Luo
author_sort	Pengcheng Ni
title	3D Kinematic Analysis of Intelligent Vision Sensor Image in Football Training
title_short	3D Kinematic Analysis of Intelligent Vision Sensor Image in Football Training
title_full	3D Kinematic Analysis of Intelligent Vision Sensor Image in Football Training
title_fullStr	3D Kinematic Analysis of Intelligent Vision Sensor Image in Football Training
title_full_unstemmed	3D Kinematic Analysis of Intelligent Vision Sensor Image in Football Training
title_sort	3d kinematic analysis of intelligent vision sensor image in football training
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/40f2d174597f4adc973789e5159342eb
work_keys_str_mv	AT pengchengni 3dkinematicanalysisofintelligentvisionsensorimageinfootballtraining AT xiluo 3dkinematicanalysisofintelligentvisionsensorimageinfootballtraining
_version_	1718418394967965696

3D Kinematic Analysis of Intelligent Vision Sensor Image in Football Training

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