Retracted: Martial Arts Routine Difficulty Action Technology VR Image Target Real-Time Extraction Simulation

With the gradual increase in the difficulty of competitive martial arts, athletes must complete fine, stable, high-quality and difficult movements in order to achieve excellent performance. The real-time extraction of martial arts movements is a topic that many martial arts enthusiasts care about. T...

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Main Authors: Nannan Sun, Ruiyang Sun, Shihong Li, Xiaolong Wu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Online Access:https://ieeexplore.ieee.org/document/9159578/
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author Nannan Sun
Ruiyang Sun
Shihong Li
Xiaolong Wu
author_facet Nannan Sun
Ruiyang Sun
Shihong Li
Xiaolong Wu
author_sort Nannan Sun
collection DOAJ
description With the gradual increase in the difficulty of competitive martial arts, athletes must complete fine, stable, high-quality and difficult movements in order to achieve excellent performance. The real-time extraction of martial arts movements is a topic that many martial arts enthusiasts care about. This study mainly discusses the real-time extraction and simulation of VR image target in the difficult movement technology of martial arts routine. Considering the complex characteristics of martial arts movements, this article will analyze the preprocessing content of existing images. This includes image enhancement and image filtering, and uses median filtering methods to enhance the characteristics of the collected images. In this way, the visual effect of the original image can be improved, and the processed image will contribute to the subsequent segmentation. A new image segmentation method is proposed for the color model of the image. According to the H component of the HSV model representing the characteristics of chromaticity, the color image is transformed into the HSV model, and the H component is extracted. The histogram concept applies to H components. Based on the histogram of the H component, the segmentation threshold is determined, and the cropping target in the image is detected. Because the model space is very sensitive to color, VR technology is used to automatically determine the segmentation target. Combined with the above division methods, the automatic extraction of objects in the image is completed. The method of using VR technology for image extraction processing has high precision, and the error value is 3.92%<5%. The research results show that the method has good segmentation results, and is suitable for image segmentation under complex background and automatic image extraction under complex background.
format Article
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spelling doaj-art-8356f8285f974becb985e3a0dbda28b42025-01-07T00:01:03ZengIEEEIEEE Access2169-35362020-01-01815581115581810.1109/ACCESS.2020.30144599159578Retracted: Martial Arts Routine Difficulty Action Technology VR Image Target Real-Time Extraction SimulationNannan Sun0Ruiyang Sun1Shihong Li2https://orcid.org/0000-0003-2399-0871Xiaolong Wu3Department of Physical Education, Suzhou University of Science and Technology, Suzhou, ChinaEthnic Traditional Sports College, Harbin Sport University, Harbin, ChinaEthnic Traditional Sports College, Harbin Sport University, Harbin, ChinaSports Training Management Center, Ningxia Sports Bureau, Yinchuan, ChinaWith the gradual increase in the difficulty of competitive martial arts, athletes must complete fine, stable, high-quality and difficult movements in order to achieve excellent performance. The real-time extraction of martial arts movements is a topic that many martial arts enthusiasts care about. This study mainly discusses the real-time extraction and simulation of VR image target in the difficult movement technology of martial arts routine. Considering the complex characteristics of martial arts movements, this article will analyze the preprocessing content of existing images. This includes image enhancement and image filtering, and uses median filtering methods to enhance the characteristics of the collected images. In this way, the visual effect of the original image can be improved, and the processed image will contribute to the subsequent segmentation. A new image segmentation method is proposed for the color model of the image. According to the H component of the HSV model representing the characteristics of chromaticity, the color image is transformed into the HSV model, and the H component is extracted. The histogram concept applies to H components. Based on the histogram of the H component, the segmentation threshold is determined, and the cropping target in the image is detected. Because the model space is very sensitive to color, VR technology is used to automatically determine the segmentation target. Combined with the above division methods, the automatic extraction of objects in the image is completed. The method of using VR technology for image extraction processing has high precision, and the error value is 3.92%<5%. The research results show that the method has good segmentation results, and is suitable for image segmentation under complex background and automatic image extraction under complex background.https://ieeexplore.ieee.org/document/9159578/
spellingShingle Nannan Sun
Ruiyang Sun
Shihong Li
Xiaolong Wu
Retracted: Martial Arts Routine Difficulty Action Technology VR Image Target Real-Time Extraction Simulation
IEEE Access
title Retracted: Martial Arts Routine Difficulty Action Technology VR Image Target Real-Time Extraction Simulation
title_full Retracted: Martial Arts Routine Difficulty Action Technology VR Image Target Real-Time Extraction Simulation
title_fullStr Retracted: Martial Arts Routine Difficulty Action Technology VR Image Target Real-Time Extraction Simulation
title_full_unstemmed Retracted: Martial Arts Routine Difficulty Action Technology VR Image Target Real-Time Extraction Simulation
title_short Retracted: Martial Arts Routine Difficulty Action Technology VR Image Target Real-Time Extraction Simulation
title_sort retracted martial arts routine difficulty action technology vr image target real time extraction simulation
url https://ieeexplore.ieee.org/document/9159578/
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AT ruiyangsun retractedmartialartsroutinedifficultyactiontechnologyvrimagetargetrealtimeextractionsimulation
AT shihongli retractedmartialartsroutinedifficultyactiontechnologyvrimagetargetrealtimeextractionsimulation
AT xiaolongwu retractedmartialartsroutinedifficultyactiontechnologyvrimagetargetrealtimeextractionsimulation