Abstract
Current methods of human body movement recognition neglect the depth denoising and edge restoration of movement image, which leads to great error in athletes’ wrong movement recognition and poor application intelligence. Therefore, an intelligent recognition method based on image vision for sports athletes’ wrong actions is proposed. The basic principle, structure, and 3D application of computer image vision technology are defined. Capturing the human body image and point cloud data, the three-dimensional dynamic model of sports athletes action is constructed. The color camera including CCD sensor and CMOS sensor is selected to collect the wrong movement image of athlete and provide image data for the recognition of wrong movement. Wavelet transform coefficient and quantization matrix threshold are introduced to denoise the wrong motion images of athletes. Based on this, the feature of sports athlete’s motion contour image is extracted in spatial frequency domain, and the edge of the image is further recovered by Canny operator. Experimental results show that the proposed method can accurately identify the wrong movements of athletes, and there is no redundancy in the recognition results. Image denoising effect is good and less time-consuming and can provide a reliable basis for related fields.
Highlights
With the increasing importance attached to sports events, athletes need to train according to various standard movements in the training process
With the development of computer vision technology, it is widely used in the analysis of human body structure
Computer vision technology is one of the key researches in the field of graphics and computer vision because there are many sports items and there are some differences in recognizing athletes’ wrong actions. ere are a variety of organs and tissues in the human body
Summary
With the increasing importance attached to sports events, athletes need to train according to various standard movements in the training process. In order to realize the intelligent recognition of athlete’s wrong action, computer vision technology is applied. Chen [4] proposed a moving image contour feature extraction method based on multithreshold optimization. Aiming at the above problems, this paper proposes a new intelligent recognition method of sports athletes’ wrong actions based on image vision. 2. Intelligent Recognition Method of Sports Athletes’ Wrong Actions Based on Image Vision. E main principle of computer vision system is to obtain the target image first, extract the feature, and analyze, process, and calculate the feature, in order to make a reasonable decision. Erefore, based on the above captured and processed motion images and point cloud data, a 3D dynamic model of sports motion is built, in which the former builds the skeleton model of the sportsman and the latter adds the display appearance to the skeleton model to make the virtual human model more realistic High realistic 3D dynamic model requires the deformation of skeletal joints, and the movement of the associated skin driven by the joints, so as to produce reasonable movement. erefore, based on the above captured and processed motion images and point cloud data, a 3D dynamic model of sports motion is built, in which the former builds the skeleton model of the sportsman and the latter adds the display appearance to the skeleton model to make the virtual human model more realistic
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