Three-dimensional face reconstruction of static images and computer standardization issues

Three-dimensional (3D) face reconstruction technology is a key issue in the field of computer vision and computer graphics. The image-based 3D face reconstruction method is the mainstream technology of 3D face reconstruction. This paper uses the 3D face reconstruction algorithm to analyze the 3D reconstruction of a static image face and the structure and realization of the computer standardized management system. In the process of high-resolution two-channel matching, combined with multilevel reconstruction technology, a better initial disparity map is obtained by comparison. Then, the improved disparity map optimization algorithm is used to optimize the initial value, so that the result of the cloud point is smoother on the model surface while maintaining good detail accuracy. The AdaBoost face detection algorithm based on embedded images is used to obtain the image representing the region, and grayscale conversion and normalization processing are performed. Finally, the Poisson surface reconstruction algorithm is used to reconstruct a 3D high-precision face model. The experimental results in this paper show that the AdaBoost face detection algorithm can effectively separate and express face features, reduce the feature dimensions to compactly represent the data and correctly classify expressions. The 3D face reconstruction technology based on static images can increase the recognition rate of a face by 24% and can also increase the texture mapping effect of the local area of the face by 13%.