基于三角形不规则网模型的快速体素化方法

计算机应用 ›› 2010, Vol. 30 ›› Issue (12): 3281-3283.

基于三角形不规则网模型的快速体素化方法

陈学工¹,邱华²,付金华²,马金金³

1. 中南大学信息科学与技术学院
2. 中南大学
3. 湖南省长沙市中南大学信息科学与工程学院

收稿日期:2010-05-10 修回日期:2010-07-26 发布日期:2010-12-22 出版日期:2010-12-01
通讯作者: 邱华
基金资助:
国家“863“高技术研究发展计划资助项目

Fast voxelization based on triangulated irregular network model

Received:2010-05-10 Revised:2010-07-26 Online:2010-12-22 Published:2010-12-01

摘要/Abstract

摘要： 为了改善在大数据量时体素化效率不高的缺点，针对三角形不规则网（TIN）模型的三角网特性，提出了一种快速简单的体素化算法。首先通过细划三角面片，将面体素化转换为简单的点体素化生成体表面模型，然后利用深度缓存原理快速寻找初始种子体素进行体内填充。实验结果表明，对于精细复杂的大规模TIN模型，算法能确实有效地生成逼近原模型的26-连通的体素模型，且具有高效的时间效率。

关键词: 表面体素化, 实体体素化, 三角形不规则网模型, 种子填充, 三角形细划

Abstract: In order to improve the voxelization efficiency of large data, a fast and simple voxelization algorithm was proposed for the Triangulated Irregular Network (TIN) model. The surface voxelization was realized by dividing triangular facets, which could convert surface voxelization to points voxelization. Then, the solid voxelization was realized by using the theory of depth buffer to quickly search initial seed. The experimental results show that for the complex and precise TIN model, a voxel model of 26-connected which is approached to original model can be efficiently generated, and it has a high time efficiency.

Key words: surface voxelization, solid voxelization, Triangulated Irregular Network (TIN) model, seed filling, triangular division

陈学工邱华付金华马金金. 基于三角形不规则网模型的快速体素化方法[J]. 计算机应用, 2010, 30(12): 3281-3283.