Name
Abstract | ||
|---|---|---|
This paper presents a new reverse engineering method for creating 3D mesh models, which approximate an unorganized noisy point set without orientation information. The new method computes sample points by the extended moving least squares method in adaptive octree cell. The octree subdivision is decided by weighted covariance matrix. Then the points are connected by intersections of supported spheres. Further, the triangular meshes are refined to remove non-manifold parts and holes. The new algorithm allows us to construct mesh models from very large point set quickly |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/CSCWD.2006.253088 | CSCWD |
Keywords | Field | DocType |
triangular meshes,mesh generation,octrees,covariance matrices,adaptive octree cell,meshing,moving least squares method,moving least squares,reverse engineering,reverse engineering method,weighted covariance matrix,least squares approximations,mesh point cloud method,solid modelling,surface reconstruction,3d mesh model,covariance matrix,least squares approximation,image reconstruction,scattering,shape,triangular mesh,point cloud | Least squares,Mathematical optimization,Polygon mesh,Computer science,Reverse engineering,Algorithm,Moving least squares,Subdivision,Covariance matrix,Mesh generation,Octree,Distributed computing | Conference |
ISBN | Citations | PageRank |
1-4244-0165-8 | 0 | 0.34 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guiping Qian | 1 | 3 | 1.07 |
| Ruofeng Tong | 2 | 466 | 49.69 |
| Wen Peng | 3 | 9 | 1.95 |
| Jinxiang Dong | 4 | 311 | 65.36 |