摘要： 为保证虚拟手术系统中的网格质量，提出一种基于Loose r-sample理论的快速表面网格重建算法。记录满足Loose r-sample采样定理的点集，用以描述物体的轮廓。通过约束Delaunay方法对该点集进行三角化，标记顶点和Delaunay单元，重构新的网格。实验结果表明，该算法能够保证生成网格的质量，简化仿真复杂度。

关键词: 网格质量, 虚拟手术系统, Loose r-sample理论, Delaunay三角剖分, Voronoi图, 局部特征

Abstract: In order to maintain the quality of the surface meshes in virtual surgery system, this paper proposes a fast reconstruction algorithm for surface mesh based on Loose r-sample theory. It records the sampling point set which satisfies Loose r-sample theory to describe object contour. It makes the dynamic Delaunay triangulation of the set and the labels of the Delaunay cells, and reconstructs new network. Experimental results show that this algorithm can maintain the quality of the meshes, and simplifies the simulation complexity.

Key words: mesh quality, virtual surgery system, Loose r-sample theory, Delaunay triangulation, Voronoi diagram, local feature

中图分类号: 

• TP911.73