散乱点云的三角网格曲面重建算法  

An algorithm for restructing surface of triangulation based on scattered point-cloud

作　　者：张霞[1,2] 赵吉宾[1] 刘伟军[1] 

机构地区：[1]中国科学院沈阳自动化研究所,沈阳110016 [2]中国科学院研究生院,北京100049

出　　处：《机械设计与制造》2011年第12期31-33,共3页Machinery Design & Manufacture

摘　　要：在采用计算机视觉法获取物体三维重建数据的过程中,为了得到较完整的模型信息,所测得的曲面点通常带有大量冗余,而这些冗余数据的存在大大增加了曲面重建的难度。在此背景下,我们针对散乱无序、无任何几何拓扑信息的密集数据,提出了一种空间三角网格直接剖分算法。该算法能够节省存储空间,提高曲面重建效率,保证输出的曲面网格优质。算法首先对原始数据进行预处理,然后采用空间栅格法及Delaunay空球等准则,扩展动态三角网,最后统一法向量输出完整的三角网格模型。通过实例证明,算法重建速度快,曲面网格质量高。In order to obtain complete information oJ su^tace model tn computer vtston methoa,tnere are a lot of redundant measured points without any geometric topology,which will make the surface reconstruction more difficult.To solve the problem,an algorithm of triangulation in three dimensions is proposed, which can save data store spaces ,increase efficiency and enhance quality of triangulation.Thi~ algorithm includes three parts ：First,the raw data was preprocessed.Then it was triangulated by means of spatial grid partition according to delannay and Circumsphere criterion.Finally,the model will be completed after uniting normal vectors.The Experimental results demonstrate that the proposed method may restrict in rapid speed with high quality grid partition surface.

关 键 词：三角网格 曲面重建 点云 DELAUNAY三角剖分 

分 类 号：TH16[机械工程—机械制造及自动化] TP391[自动化与计算机技术—计算机应用技术]