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Key technology of point cloud data texture reconstruction based on 3D acquisition

With the continuous development of science and technology, 3D acquisition and reconstruction technology based on point cloud data (PCD) texture can quickly recreate a very realistic 3D model from discrete points on the surface of the object. This technology has become the main technology in the field of 3D model reconstruction. The purpose of this paper is to study the key technology of texture reconstruction based on 3D collected PCD. This article first introduces three typical algorithms based on Delaunay triangulation in detail, and compares their advantages and disadvantages, and proposes a Delaunay triangle mesh reconstruction algorithm based on spatial adaptive circumscribed sphere. This paper proposes a new mesh smoothing algorithm that maintains the characteristics of the model in order to solve the problem of the convex edges and corners of the reconstructed mesh model. By combining the advantages of the Laplace operator and the average curvature method, the regularity of the triangle surface is improved, and the area of the second-order neighborhood triangle is used as the weight to improve the bilateral filter. Experiments on the 3D meshing of the Bunny monkey point cloud show that the simplification rate of the algorithm proposed in this study is 80.78%, and the simplification rate of the point cloud feature point detection method based on point signature is 48.51%. It shows that the feature point extraction of this algorithm is more accurate, and the simplification efficiency is relatively high.