Algorithm Reconstruction Based On Cloud Data

In recent years, with the fast, high precision of 3d digitizing scanning equipment constantly emerged; people obtain surface sampling data become relatively simple, cheap and accurate. The process that convert sampling data to geometric model called surface reconstruction, the technology can be widely applied to computer aided geometric design, computer graphics, medical image processing, computer vision, etc. This paper researched cloud data reconstruction methods based on data acquired from the 3d digitizing scanning equipment, and the specific work are as follows:Aiming at the surface reconstruction of point cloud, this paper analyzes the domestic and foreign point cloud reconstruction algorithm, and compares their advantages and disadvantages, absorbing the advantages of these algorithms, and puts forward a kind of boundary maintenance point cloud data reconstruction algorithm.According to the fitting error on the point cloud, this algorithm will be self-adaptive fitting by reducing the fitting times of the top node of octree, improving the efficiency of the algorithm, And correct the weight function of unit decomposition methods, join density weight function and weaken the surface rebuild influence created by the inconsistent point cloud density. In generating triangular mesh, and combining the original point cloud data, it will do the boundary constraint to gained grid. Experimental results show that the algorithm principle is simple, reconstruction speed is fast, rebuild effect is good and satisfy the 3d face plastic and beauty virtual surgery system for surface reconstruction requirements.