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...

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Bibliographic Details
Published in:Computational intelligence and neuroscience Vol. 2022; pp. 1 - 10
Main Authors: Zhang, Dengfeng, Li, Yupeng
Format: Journal Article
Language:English
Published: United States Hindawi 28.04.2022
John Wiley & Sons, Inc
Subjects:
ISSN:1687-5265, 1687-5273, 1687-5273
Online Access:Get full text
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Summary: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.
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Academic Editor: Kapil Sharma
ISSN:1687-5265
1687-5273
1687-5273
DOI:10.1155/2022/3814252