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Point Tracking Technology of Sports Image Sequence Marks Based on Fuzzy Clustering Algorithm
Fuzzy clustering algorithms have received widespread attention in various fields. Point tracking technology has significant application importance in sports image data analysis. In order to solve the problem of limited tracking performance caused by the fuzzy and rough division of moving image edges...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9071957/ https://www.ncbi.nlm.nih.gov/pubmed/35528353 http://dx.doi.org/10.1155/2022/3814252 |
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author | Zhang, Dengfeng Li, Yupeng |
author_facet | Zhang, Dengfeng Li, Yupeng |
author_sort | Zhang, Dengfeng |
collection | PubMed |
description | Fuzzy clustering algorithms have received widespread attention in various fields. Point tracking technology has significant application importance in sports image data analysis. In order to solve the problem of limited tracking performance caused by the fuzzy and rough division of moving image edges, this paper proposes a point tracking technology based on a fuzzy clustering algorithm, which is used for the point tracking of moving image sequence signs. This article analyzes the development status of sports image sequence analysis and processing technology and introduces some basic theories about fuzzy clustering algorithms. On the basis of the fuzzy clustering algorithm, the positioning and tracking of the marker points of the moving image sequence are studied. A series of experiments have proved that the fuzzy clustering algorithm can improve the recognition rate of the landmark points of the moving image. For the detection and tracking of moving targets, the fuzzy clustering algorithm can reach the limit faster under the same number of iterations, and the image noise can be reduced to 60% of the original by 5 iterations. This has excellent development value in application. |
format | Online Article Text |
id | pubmed-9071957 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-90719572022-05-06 Point Tracking Technology of Sports Image Sequence Marks Based on Fuzzy Clustering Algorithm Zhang, Dengfeng Li, Yupeng Comput Intell Neurosci Research Article Fuzzy clustering algorithms have received widespread attention in various fields. Point tracking technology has significant application importance in sports image data analysis. In order to solve the problem of limited tracking performance caused by the fuzzy and rough division of moving image edges, this paper proposes a point tracking technology based on a fuzzy clustering algorithm, which is used for the point tracking of moving image sequence signs. This article analyzes the development status of sports image sequence analysis and processing technology and introduces some basic theories about fuzzy clustering algorithms. On the basis of the fuzzy clustering algorithm, the positioning and tracking of the marker points of the moving image sequence are studied. A series of experiments have proved that the fuzzy clustering algorithm can improve the recognition rate of the landmark points of the moving image. For the detection and tracking of moving targets, the fuzzy clustering algorithm can reach the limit faster under the same number of iterations, and the image noise can be reduced to 60% of the original by 5 iterations. This has excellent development value in application. Hindawi 2022-04-28 /pmc/articles/PMC9071957/ /pubmed/35528353 http://dx.doi.org/10.1155/2022/3814252 Text en Copyright © 2022 Dengfeng Zhang and Yupeng Li. 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 Zhang, Dengfeng Li, Yupeng Point Tracking Technology of Sports Image Sequence Marks Based on Fuzzy Clustering Algorithm |
title | Point Tracking Technology of Sports Image Sequence Marks Based on Fuzzy Clustering Algorithm |
title_full | Point Tracking Technology of Sports Image Sequence Marks Based on Fuzzy Clustering Algorithm |
title_fullStr | Point Tracking Technology of Sports Image Sequence Marks Based on Fuzzy Clustering Algorithm |
title_full_unstemmed | Point Tracking Technology of Sports Image Sequence Marks Based on Fuzzy Clustering Algorithm |
title_short | Point Tracking Technology of Sports Image Sequence Marks Based on Fuzzy Clustering Algorithm |
title_sort | point tracking technology of sports image sequence marks based on fuzzy clustering algorithm |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9071957/ https://www.ncbi.nlm.nih.gov/pubmed/35528353 http://dx.doi.org/10.1155/2022/3814252 |
work_keys_str_mv | AT zhangdengfeng pointtrackingtechnologyofsportsimagesequencemarksbasedonfuzzyclusteringalgorithm AT liyupeng pointtrackingtechnologyofsportsimagesequencemarksbasedonfuzzyclusteringalgorithm |