Mesh Simplification with Face Clustering

YAN Jing-qi; SHI Peng-fei

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Mesh Simplification with Face Clustering

更新时间：2025-07-16

- Mesh Simplification with Face Clustering
- Acta Electronica Sinica Vol. 30, Issue 1, Pages: 38-41(2002)
- 作者机构：
  
  上海交通大学图像处理与模式识别研究所,上海,200030
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391
- Published：2002
- 稿件说明：
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YAN Jing-qi, SHI Peng-fei. Mesh Simplification with Face Clustering[J]. Acta Electronica Sinica, 2002, 30(1): 38-41.
DOI：

YAN Jing-qi, SHI Peng-fei. Mesh Simplification with Face Clustering[J]. Acta Electronica Sinica, 2002, 30(1): 38-41. DOI：

摘要

三维物体表面重建广泛采用三角网格方法

密集的数据采样可以重建出精确的三维表面

但是庞大的数据量不利于多分辨率三维实时显示和三维物体网络传输

因此三维表面网格简化是迫切需要解决的问题之一.近年来表面简化问题得到了广泛地研究.本文提出基于面聚类的网格简化新算法

通过最小化最大类内距离算法进行面聚类实现区域划分

然后提取区域特征

进而根据特征点和边对区域进行受限三角剖分.实验说明本文提出的面聚类网格简化算法在保持三维表面几何拓扑特征的基础上取得了很好的简化效果.

Abstract

The need for an accurate simplification of surface meshes is becoming more and more urgent in many applications.It not only suits mulitiresolution/level-of-detailed representations and quick visualization

but also allows fast transmission of 3D models in network-based applications.Many different approaches and algorithms for mesh simplification have been proposed in the last few years.In this paper we present a new method

which partitions region by minimizing the maximum intercluster distance clustering algorithm

extracts features in every region and triangulates them by constrained delaunay triangulation.The results of examples illustrate our simplification method is effective.

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