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. 2022 Jul 31:2022:4322597.
doi: 10.1155/2022/4322597. eCollection 2022.

Image Recognition of Sports Athletes' High-Intensity Sports Injuries Based on Binocular Stereo Vision

Dongdong Chen  1
Affiliations

Image Recognition of Sports Athletes' High-Intensity Sports Injuries Based on Binocular Stereo Vision

Dongdong Chen. Comput Intell Neurosci. .

Retraction in

Abstract

Sports athletes are prone to certain injuries during high-intensity exercise training. In the process of treating an injury, images of the injury site need to be collected and identified. However, the traditional recognition method cannot effectively extract the features of the image. At the same time, it ignores the optimization of the damage image recognition results, resulting in low recognition accuracy and poor efficiency. Binocular stereo vision technology can quickly and accurately detect moving objects. Therefore, in order to more accurately identify high-intensity sports injury images, this study takes the high-intensity sports injury images as the basic research object. Several processes of image processing based on binocular stereo vision are analyzed, and the vulnerable parts of the body in high-intensity sports are also studied. Finally, the method in this study is verified. The experimental results show that the method proposed in this study reduces the average error rate by 0.19% compared with the traditional recognition method. It can effectively identify and detect injury images, thereby improving the accuracy and stability of sports injury image identification. The identification time is also shortened accordingly, which has certain practicability and feasibility. In addition, the binocular camera used in this study has high accuracy, and the obtained images of sports injuries are of good quality, which lays a foundation for image detection and recognition.

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Conflict of interest statement

The author declares no conflicts of interest.

Figures

Figure 1
Figure 1
Functional modules of the binocular stereo vision system.
Figure 2
Figure 2
Basic principle of binocular stereo vision.
Figure 3
Figure 3
Basic flow chart of image recognition.
Figure 4
Figure 4
Structural framework of image recognition based on binocular stereo vision.
Figure 5
Figure 5
Comparison of 3D reconstruction coordinates and actual targets.
Figure 6
Figure 6
Comparison of recognition rates of different damage detection methods.
Figure 7
Figure 7
Time-consuming comparison of identification of different damage detection methods.
Figure 8
Figure 8
Comparison of error rates of different damage detection methods.
See this image and copyright information in PMC

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