基于散乱点云数据的曲面重构方法

Surface Reconstruction from Scattered Cloud Data

散乱点云的三维重构有广阔的应用前景,通用高效的重构算法是研究重点之一,目前大多采用三角面片重构,与通用CAD/CAM系统中的四边域重构不兼容。本文提出一种在三角域上对散乱点云数据进行NURBS曲面重构的方法,结合了三角面片重构的灵活性与NURBS曲面重构的通用性。首先对测量点云数据进行Delaunay三角剖分,然后针对三角网格模型的数据组织特点采用基于特征的块边界扩展生长数据分块方法进行网格分块,最后通过构造Coons基曲面进行曲面插值,得到了G1连续的NURBS曲面。

3D surface reconstruction from scattered cloud data has numerous applications, and the general and highefficiency algorithm for reconstruction is widely studied. The algorithm of triangle meshes recovery is popularly used, but it can not applied in the general CAD/CAM system. A method of NURBS surface reconstruction from scattered cloud data according to triangle meshes is presented in this paper. It makes use of both the flexibility of triangle meshes recovery and the versatility of NURBS reconstruction. The measure points are triangulated firstly. Then triangle meshes are divided into grids through partition＇s border expanding based on the character of data structure. Finally the geometric continuous NURBS surface is obtained through building up Coons base surface and interpolating the grid points.