基于点云数据的主成分分析重构表面算法  

Principal component analysis reconstruction surface algorithm based on points cloud data

作　　者：张贺[1] 杨金玲[1] 曹先革[1] 

机构地区：[1]黑龙江工程学院测绘工程学院,黑龙江哈尔滨150050

出　　处：《黑龙江工程学院学报》2010年第1期39-42,共4页Journal of Heilongjiang Institute of Technology

摘　　要：提出一种基于三维点云数据的主成分分析重建三维表面模型的方法,该方法利用基于主成分分析的动态聚类方法对三维扫描数据进行聚类,进而对点云数据重构—点片,研究在局部利用二维三角网构网技术构建三角网,然后在考虑局部三角网边缘一致性的基础上组合成整体三维表面模型的算法。应用实例表明,该算法能有效地完成重建物体三维表面模型。A method of using principal component analysis to reconstruct three-dimensional surface model based on three-dimensional points cloud data is put forward. And it uses the dynamic clustering method of principal component analysis to cluster the three-dimensional scanning data, so that it reconstructs the points cloud data--points slice; studies construct the triangle network by the two-dimensional triangle technology in local area, and then it composes the algorithm of the whole three-dimensional surface model based on considering the local area triangle curved surface network edge consistence. The application example manifests that the algorithm can reconstruct the object three-dimensional surface model efficiently.

关 键 词：点云数据 主成分分析 三维表面重构 DELAUNAY 

分 类 号：P208[天文地球—地图制图学与地理信息工程]