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.
关键词
三维重建/激光点云/影像点云/Delaunay三角剖分/Crust算法
Key words
3D reconstruction/laser point cloud/image point cloud/Delaunay triangulation/Crust algorithm
维普
万方数据