Automatic detection technology of sports athletes based on image recognition technology

Abstract In order to improve the motion recognition effect of sports athletes based on image recognition technology, this study takes the current common diving athletes as the research material in the actual research, and combines the research status of image recognition to study the athlete’s motio...

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Main Authors: Guangjing Li, Cuiping Zhang
Format: Article
Language:English
Published: SpringerOpen 2019-01-01
Series:EURASIP Journal on Image and Video Processing
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13640-019-0415-x
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spelling doaj-aae6715cfe384b8e8df3ec7ab64c65e42020-11-25T01:31:26ZengSpringerOpenEURASIP Journal on Image and Video Processing1687-52812019-01-01201911910.1186/s13640-019-0415-xAutomatic detection technology of sports athletes based on image recognition technologyGuangjing Li0Cuiping Zhang1Department of Physical Education, Tianjin University of CommerceTianjin Huaxin Zhiyuan Technology Co., Ltd.Abstract In order to improve the motion recognition effect of sports athletes based on image recognition technology, this study takes the current common diving athletes as the research material in the actual research, and combines the research status of image recognition to study the athlete’s motion recognition from image processing. Simultaneously, in this study, the gradient segmentation method is used to segment the image, the research object is segmented from the video image, the traditional image grayscale method is improved, and the image segmentation algorithm adapted to the diving motion is obtained. On this basis, this study combines Gaussian mixture background modeling and background subtraction to achieve the detection and extraction of target human body regions, and uses morphological operators to deal with noise and void phenomena in foreground images. The example analysis shows that the proposed method has certain practicality and can provide theoretical reference for subsequent related research.http://link.springer.com/article/10.1186/s13640-019-0415-xImage recognitionSportsAthletesDetectionVideo image
collection DOAJ
language English
format Article
sources DOAJ
author Guangjing Li
Cuiping Zhang
spellingShingle Guangjing Li
Cuiping Zhang
Automatic detection technology of sports athletes based on image recognition technology
EURASIP Journal on Image and Video Processing
Image recognition
Sports
Athletes
Detection
Video image
author_facet Guangjing Li
Cuiping Zhang
author_sort Guangjing Li
title Automatic detection technology of sports athletes based on image recognition technology
title_short Automatic detection technology of sports athletes based on image recognition technology
title_full Automatic detection technology of sports athletes based on image recognition technology
title_fullStr Automatic detection technology of sports athletes based on image recognition technology
title_full_unstemmed Automatic detection technology of sports athletes based on image recognition technology
title_sort automatic detection technology of sports athletes based on image recognition technology
publisher SpringerOpen
series EURASIP Journal on Image and Video Processing
issn 1687-5281
publishDate 2019-01-01
description Abstract In order to improve the motion recognition effect of sports athletes based on image recognition technology, this study takes the current common diving athletes as the research material in the actual research, and combines the research status of image recognition to study the athlete’s motion recognition from image processing. Simultaneously, in this study, the gradient segmentation method is used to segment the image, the research object is segmented from the video image, the traditional image grayscale method is improved, and the image segmentation algorithm adapted to the diving motion is obtained. On this basis, this study combines Gaussian mixture background modeling and background subtraction to achieve the detection and extraction of target human body regions, and uses morphological operators to deal with noise and void phenomena in foreground images. The example analysis shows that the proposed method has certain practicality and can provide theoretical reference for subsequent related research.
topic Image recognition
Sports
Athletes
Detection
Video image
url http://link.springer.com/article/10.1186/s13640-019-0415-x
work_keys_str_mv AT guangjingli automaticdetectiontechnologyofsportsathletesbasedonimagerecognitiontechnology
AT cuipingzhang automaticdetectiontechnologyofsportsathletesbasedonimagerecognitiontechnology
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