Refined 3D reconstruction of point cloud complex surface with improved Crust algorithm
Aiming at the problems that the Crust algorithm based on Delaunay triangulation is not smooth enough,time-con-suming,and has low accuracy when reconstructing complex surfaces from laser and image point clouds,an improved 3D point cloud reconstruction method is proposed.Firstly,the voxel barycentric near feature point algorithm is used for down-sampling.After that,the moving least squares algorithm is used to fit the function and determine the quadratic basis function and Gaussian weight function to complete the data smoothing and optimization.Then,the Crust algorithm based on the adap-tive extrinsic circle Delaunay triangulation method is used to reconstruct the coarse triangular mesh.Finally,the ratio of the outer radius of the tetrahedron to the shortest side length of the tetrahedron is used to eliminate the unqualified tetrahedron and complete the reconstruction and optimization of the model.The experimental results show that this method can reduce the time of holes and reconstruction,and build a smooth 3D model with more accurate topology of point cloud.
3D reconstructionlaser point cloudimage point cloudDelaunay triangulationCrust algorithm
万方数据
维普
