In order to improve the training level of Sanda movement, this article uses an image analysis method to reconstruct the detailed characteristics of the movement and apply them to the actual training process. Since the traditional wavelet reconstruction method is affected by the accuracy of the decomposition scale, this paper proposes an improved method of Sanda action based on 3D image reconstruction. First, the method relies on frame adjacent phase compensation and digital image stabilization techniques to perform digital frame operations on the image. Then, scanning and corner detection are used for image reconstruction, where adjacent phase compensation methods are used to match feature points and gray pixels. Image extraction is performed by extracting key feature points of the action 3D image, and a fast frame detection method is used to stabilize the image of the digital image, thereby improving the image quality of image reconstruction. The experimental results show that the method has good image output effect and has a high application value in Sanda guidance and optimization.

中文翻译：

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基于3D图像的散打动作重构模型设计

为了提高散打运动的训练水平，本文采用图像分析方法重建了运动的详细特征，并将其应用于实际训练过程中。由于传统的小波重构方法受分解尺度精度的影响，本文提出了一种基于3D图像重构的散打动作改进方法。首先，该方法依靠帧相邻相位补偿和数字图像稳定技术来对图像执行数字帧操作。然后，将扫描和角点检测用于图像重建，其中使用相邻的相位补偿方法来匹配特征点和灰度像素。通过提取动作3D图像的关键特征点来执行图像提取，快速帧检测方法用于稳定数字图像的图像，从而提高图像重建的图像质量。实验结果表明，该方法具有良好的图像输出效果，在散打指导和优化中具有较高的应用价值。