基于网格分割的自适应细分曲面算法研究

细分曲面中，随着对模型细分次数的增多，模型的面片数迅速增长，巨大的数据量加大了模型后处理的难度。为此，结合网格分割技术，提出了一种自适应细分曲面算法。该算法利用控制网格每个顶点与其对应的极限位置之间的欧氏距离不同、采用K-均值算法和区域合并技术对控制网格进行分割，随后对用户指定的网格区域或不满足精度的区域进行局部自适应细分。实验结果表明，该算法在给定精度范围内，有效地以相对较少的面片数获得了理想光滑的细分曲面，且大大提高了模型的后处理速度。

Adaptive refinements in subdivision surfaces based on mesh segmentation

One problem existing in subdivision surfaces is the number of facets growing exponentially with every subdivision step,and the number of the subdivision surface facets was usually huge and the scheme was difficult to manipulate in post processing.To solve this problem,an adaptive subdivision method based on mesh segmentation technique was presented.This method consisted of two parts,which were mesh segmentation and local refinements.In mesh segmentation,vertices of the mesh were classified into clusters according to its error distance and connected triangle regions were extracted by region adjacency graph algorithm.In local refinements,user-defined mesh regions or those regions,which were not satisfied with user-specified error tolerance,were subdivided.Examples showed that the method could achieve a desirable amount of surface quality by fewer facets in the approximation,and then significantly increase the post processing speed of model.