基于最小化最大类内距离的面聚类网格分割算法

介绍了一种简单、有效的三维网格分割算法．该算法是基于最小化最大类内误差的聚类方法．先将表面网格转换成连接图,通过最短路径定义任意两个三角形之间的“距离”,然后利用新的距离度量将传统的聚类算法应用到网格表面分割问题．提出的算法不仅确保使最大类内距离实现最小,而且可以确保每个类别的所有三角形都构成网格表面上单独的一片．提出了一种受限边界直化算法,极大改善了分割后的区域形状．实验表明,这种两步(最小化最大类内距离聚类和受限边界直化)的网格分割算法在区域平面性和区域形状方面都表现出了良好效果．

A New Mesh Segmentation Algorithm Based on Face Clustering

A simple but effective algorithm which is based on minimizing the maximum discrepancy clustering was presented. Two new metrics of "distance" between any two triangles is developed. By the new distance metrics, the clustering method is easily extended to divide the input mesh into several connected regions. Furthermore, a post-processing algorithm, constrained boundary straightening, was proposed to regularize the shapes of partitioned regions. The experiments show that this two-step solution for mesh segmentation performs well in both region planarity and region shape.