辛群荣;姚吉利;徐广鹏;

• 1:山东理工大学

摘要(Abstract)：

针对激光点云数据进行建筑物建模或矢量信息提取中快速识别建筑物面和棱线信息的要求,该文提出基于共享近邻聚类算法进行建筑物面和棱线的快速提取方法。首先,计算点云中每个数据点的单位法向量和点到基准面的距离,利用基于网格的共享近邻聚类算法对点云进行分类确定建筑物面点云;然后,自动判别相交平面,提取建筑物棱线,并与RANSAC算法对某建筑物面的提取结果进行比较。结果证明,该方法自动化程度高,建筑物面和棱线提取快速、准确,提取结果能够应用于三维建筑物自动建模和测绘出图。

关键词(KeyWords)： 地面三维激光扫描;共享近邻聚类;建筑物平面分割;棱线提取

Abstract:

Keywords:

基金项目(Foundation): 山东省高等学校科技计划项目(J15LN32)

作者(Authors): 辛群荣;姚吉利;徐广鹏;

DOI: 10.16251/j.cnki.1009-2307.2018.01.020

参考文献(References)：

• [1]LERMA J L,BIOSCA J M.Unsupervised robust planar segmentation of terrestrial laser scanner point clouds based on fuzzy clustering methods[J].Isprs Journal of Photogrammetry&Remote Sensing,2008,63(1):84-98.
• [2]胡怀宇,崔汉国,代星.基于区域生长法的散乱点云分区方法[J].计算机应用,2009,29(10):2716-2718.(HU Huaiyu,CUI Hanguo,DAI Xing.Segmentation of scattered point data based on region growing method[J].Journal of Computer Applications,2009,29(10):2716-2718.)
• [3]LEE I,SCHENK T.3D perceptual organization of laser altimetry data[J].International Archives of Photogrammetry and Remote Sensing,2001,34(3):57-65.
• [4]李娜,马一薇,杨洋,等.利用RANSAC算法对建筑物立面进行点云分割[J].测绘科学,2011,36(5):144-145.(LI Na,MA Yiwei,YANG Yang,et al.Segmentation of building facade point clouds using RANSAC[J].Science of Surveying and Mapping,2011,36(5):144-145.)
• [5]胡伟,卢小平,李珵,等.基于改进RANSAC算法的屋顶激光点云面片分割方法[J].测绘通报,2012(11):31-34.(HU Wei,LU Xiaoping,LI Cheng,et al.Extended RANSAC algorithm for building roof segmentation from LiDAR data[J].Bulletin of Surveying and Mapping,2012(11):31-34.)
• [6]BRENNER C.Towards fully automatic generation of city models[J].The International Archives of Photogrammetry and Remote Sensing,2000,32(3):85-92.
• [7]FORLANI G,NARDINOCCHI C,SCAIONI M,et al.Complete classification of raw LiDAR data and 3Dreconstruction of buildings[J].Pattern Analysis Application,2006(8):357-374.
• [8]WANG M,TSENG Y H.Automatic segmentation of LiDAR data into coplanar point clusters using an octree-based split-and-merge algorithm[J].Photogrammetric Engineering and Remote Sensing,2010,76(4):407-420.
• [9]GUMHOLD S,WANG Xinlong,MACLEOD R.Feature extraction from point clouds[C]//Proceedings of International Meshing Roundtable,Newpoort Bech:CA,USA,2001:293-305.
• [10]PAULY M,KEISER R,GROSS M.Multi-scale feature extraction on point-sampled surfaces[J].Computer Graphics Forum,2003,22(3):281-289.
• [11]王丽辉,袁保宗.三维散乱点云模型的特征点检测[J].信号处理,2011,27(6):932-938.(WANG Lihui,YUAN Baozong.Feature point detection for 3Dscattered point cloud model[J].Signal Processing,2011,27(6):932-938.)
• [12]庞旭芳,庞明勇,肖春霞.点云模型谷脊特征的提取与增强算法[J].自动化学报,2010,36(8):1073-1083.(PANG Xufang,PANG Mingyong,XIAO Chunxia.An algorithm for extracting and enhancing valley-ridge features from point sets[J].Acta Automatic Sinica,2010,36(8):1073-1083.)
• [13]林祥国,黄择祥.利用KD-树剔除机载雷达点云粗差的方法研究[J].测绘科学,2015,40(11):79-84.(LIN Xiangguo,HUANG Zexiang.An outlier eliminating method for airborne LiDAR point cloud data using KDtree[J].Science of Surveying and Mapping,2015,40(11):79-84.)
• [14]刘敏娟,柴玉梅.基于网格的共享近邻聚类算法[J].计算机应用,2006,26(7):1673-1675.(LIU Minjuan,CHAI Yumei.Grid-based shared nearest neighbor clustering algorithm[J].Computer Applications,2006,26(7):1673-1675.)
• [15]HOPPE H.Surface reconstruction from unorganized points[J].Acm Siggraph Computer Graphics,1999,26(2):71-78.
• [16]PETERNELL M.Developable surface fitting to point clouds[J].Computer Aided Geometric Design,2004,21(8):785-803.