Abstract
With the rapid development of computer vision technology, human action recognition technology has occupied an important position in this field. The basic human action recognition system is mainly composed of three parts: moving target detection, feature extraction, and human action recognition. In order to understand the action signs of gymnastics, this article uses network communication and contour feature extraction to extract different morphological features during gymnastics. Then, the finite difference algorithm of edge curvature is used to classify different gymnastic actions and analyze and discuss the Gaussian background. A modular method, an improved hybrid Gaussian modeling method, is proposed, which adaptively selects the number of Gaussian distributions. The research results show that, compared with traditional contour extraction, the resolution of gymnastic motion features extracted through network communication and body contour features is clearer, and the increase rate is more than 30%. Moreover, the method proposed in this paper removes noise in the image extraction process, the effect is good, and the athlete’s action marks are very clear, which can achieve the research goal.
Highlights
Contour extraction refers to the process of accurately marking the contour of a target object in an image
Moving Target Detection. is article gives a comprehensive overview of human action recognition, analyzes the status quo of relevant research at home and abroad, and conducts corresponding research on moving target detection, human action feature selection and extraction, and human action classification and recognition
It introduces the background and significance of motion recognition of moving human body and the development status at home and abroad, and summarizes the process of human motion recognition system in general, and summarizes the research content of this article and the content arrangement of each chapter. e video image preprocessing part is the basis of the human body action recognition system. is part mainly introduces the basic image preprocessing grayscale, binarization technology and noise removal methods, as well as mathematical morphology calculation methods [24]
Summary
Contour extraction refers to the process of accurately marking the contour of a target object in an image. With the rapid development of computer vision technology, human action recognition technology has occupied an important position in this field. On the basis of natural gymnastics, it incorporates music, dance, light equipment, and other elements and uses a combination of sports and art It can be used in a certain space and time. A sports event that perfectly expresses the beauty of women’s physical and mental beauty was temperament It is a highly difficult and high-level competitive sports project with broad innovation space. When the color of the human body is close to the background color, the outline boundary may be unclear when extracting, or the human body may be judged as the background to cause missed detection; at the same time, the tree stumps, mailboxes, and other objects that are close to the shape of the human body in the background are often mistaken. Many scholars have conducted research on the problem of occlusion, but they have not yet come up with a very effective solution
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