一种基于点云法向量的基准特征提取与倾斜分析方法

doi:10.13474/j.cnki.11-2246.2019.0100

测绘通报 ›› 2019, Vol. 0 ›› Issue (3): 155-158,162.doi: 10.13474/j.cnki.11-2246.2019.0100

• 测绘地理信息技术装备应用案例 • 上一篇下一篇

一种基于点云法向量的基准特征提取与倾斜分析方法

孙文潇¹, 王健¹, 靳奉祥^1,2, 梁周雁³

1. 山东科技大学, 山东青岛 266590;
2. 山东建筑大学, 山东济南 250101;
3. 山东省国土测绘院, 山东济南 250102

收稿日期:2019-01-20 出版日期:2019-03-25 发布日期:2019-04-02
通讯作者: 王健。E-mail:rainbowwj@126.com E-mail:rainbowwj@126.com
作者简介:孙文潇(1993-),女,博士生,研究方向为激光扫描数据处理。E-mail:1285649338@qq.com
基金资助:
国家自然科学基金（41471330）；山东科技大学研究生创新基金（SDKDYC180310）

A datum feature extraction and deformation analysis method based on normal vector of point cloud

SUN Wenxiao¹, WANG Jian¹, JIN Fengxiang^1,2, LIANG Zhouyan³

1. Shandong University of Science and Technology, Qingdao 266590, China;
2. Shandong Jianzhu University, Jinan 250101, China;
3. Shandong Provincial Institute of Land Surveying and Mapping, Jinan 250102, China

Received:2019-01-20 Online:2019-03-25 Published:2019-04-02

摘要/Abstract

摘要： 针对目前将三维激光扫描技术应用于变形监测领域存在基准特征难以提取、点云数据分析缺乏适用的方法等问题，本文提出了一种基于点云法向量的基准特征提取与形变分析方法。首先利用局部平面拟合方法获得点云的法向量，并沿点云法矢方向探测基准点；然后利用三次B样条曲线对探测的正确基准点进行拟合；最后根据拟合曲线计算基准高程和对径点倾斜角分析基准特征形变信息。对某化工厂的罐体点云数据进行基准特征提取结果表明，该方法可以快速、全面地获取监测对象的整体信息，且能够正确分析监测对象的基准形变。

关键词: 形变分析, 点云, 法向量, 基准特征, 三次B样条曲线

Abstract: In order to solve the problems of the existing difficulty of datum feature extraction and the lack of applicable analysis method of point cloud data in the application of three-dimensional laser scanning technology to the field of deformation monitoring,an efficient method for datum feature extraction and deformation analysis is proposed in this paper based on normal vector of point cloud.Firstly,owing to the local surface fitting obtains directly the geometric features by applying the point cloud model with low time complexity,this paper uses the local planar normal vector determined by the nearest neighbours of meet certain condition and follow the normal vector of the point cloud to detect the datum points.Then,the cubic B-spline curve fitting is performed on the datum points.To this end,elevation of the datum and the inclination angle of the radial point are calculated according to the fitted curve and then the deformation information is analyzed.The proposed approach is verified on real large-scale tank data set captured with terrestrial laser scanner in a chemical plant.The results show that the method could obtain the entire information of the monitor object quickly and comprehensively,and reflect the datum deformation accurately.

Key words: deformation analysis, point cloud, normal vector, datum feature, cubic B-spline curve fitting

中图分类号:

P258

孙文潇, 王健, 靳奉祥, 梁周雁. 一种基于点云法向量的基准特征提取与倾斜分析方法[J]. 测绘通报, 2019, 0(3): 155-158,162.

SUN Wenxiao, WANG Jian, JIN Fengxiang, LIANG Zhouyan. A datum feature extraction and deformation analysis method based on normal vector of point cloud[J]. 测绘通报, 2019, 0(3): 155-158,162.

参考文献

[1] WU B, YU B, WU Q, et al. A graph-based approach for 3D building model reconstruction from airborne LiDAR point clouds[J]. Remote Sensing, 2017, 9(1):92.
[2] PESCI A, TEZA G, BONALI E, et al. A laser scanning-based method for fast estimation of seismic-induced building deformations[J]. ISPRS Journal of Photogrammetry & Remote Sensing, 2013, 79:185-198.
[3] WEI Z,GUO H, LI Q, et al. Fine deformation monitoring of ancient building based on terrestrial laser scanning technologies[C]//IOP Conference Series:Earth and Environmental Science.[S.l.]:IOP Publishing, 2014:682-691.
[4] 蔡来良,吴侃,张舒.点云平面拟合在三维激光扫描仪变形监测中的应用[J].测绘科学,2010, 35(5):231-232.
[5] 王健,孙文潇,梁周雁,等.三维激光扫描的龙柱倾斜观测方法[J].测绘科学,2017,42(9):116-120.
[6] KIM H S, CHOI H K, LEE K H. Feature detection of triangular meshes based on tensor voting theory[J]. Computer-Aided Design, 2009, 41(1):47-58.
[7] 詹曦,张建生.点云边界提取及三角网格生成的集成算法研究[J].计算机仿真,2013,30(11):272275.
[8] SUN J, JIANG Y, JIANG J, et al. Triangular mesh construc-tion based on point cloud matrix and edge feature extraction[C]//IEEE Information Technology, Networking, Electronic and Automation Control Conference. Chongqing:IEEE, 2016:275-279.
[9] 安毅.三维点云数据的几何特性估算与特征识别[D].大连:大连理工大学, 2011.
[10] LIU X, JIN C. Feature line extraction from unorganized noisy point clouds[J]. Journal of Computational Information Systems, 2014, 10(8):3503-3510.
[11] LIN Y, WANG C, CHENG J, et al. Line segment extraction for large scale unorganized point clouds[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015, 102:172-183.
[12] 乐亚南. 基于曲线拟合理论的点云数据处理分析[D]. 成都:西南交通大学, 2015.
[13] 李雷. 三维激光扫描技术在立式罐容积测量中的应用研究[D]. 青岛:山东科技大学, 2012.
[14] 陈伟. 三维激光扫描式油罐容量计量方法研究[D].杭州:中国计量学院, 2015.

[1]	王艳军, 林云浩, 王书涵, 李少春, 王孟杰. OSM辅助车载LiDAR点云三维道路边界精细提取[J]. 测绘通报, 2022, 0(7): 18-25.
[2]	经皓然, 徐敬海. 异形建筑的无人机点云与地面三维激光扫描点云配准[J]. 测绘通报, 2022, 0(6): 32-39.
[3]	钟少忠, 周克军, 王留召, 毛明楷. 车载点云特征对应影像自动分割技术研究[J]. 测绘通报, 2022, 0(6): 45-48 ,97.
[4]	谢洪, 陈立波, 聂倩, 吴玮, 张沛. 利用点云配准的空地影像融合技术[J]. 测绘通报, 2022, 0(6): 82-87.
[5]	谢元, 董梦, 马新建. 多源数据在复杂场景建筑物三维重建的应用[J]. 测绘通报, 2022, 0(6): 143-147.
[6]	李旭. 三维激光扫描技术在地铁隧道竣工测量中的应用[J]. 测绘通报, 2022, 0(6): 166-169.
[7]	谭玉慧, 刘欣怡, 张永军. 超体素约束下的主动再学习LiDAR点云分类框架[J]. 测绘通报, 2022, 0(5): 79-83,100.
[8]	赵立都, 向中富, 周银, 马下平, 张双成, 司梦元, 陈茂霖, 胡川, 潘建平. 利用地面三维激光扫描进行桥梁挠度变形分析[J]. 测绘通报, 2022, 0(5): 95-100.
[9]	王道杰, 陈倍, 孙健辉. 机载LiDAR点云密度对DEM精度的影响[J]. 测绘通报, 2022, 0(5): 140-144,169.
[10]	徐福斌, 曲相屹, 王健, 刘秀涵. 基于LiDAR点云的复杂钢结构模型重建[J]. 测绘通报, 2022, 0(5): 170-173.
[11]	阮明浩, 卢永华, 刘玉贤, 汤圣君, 王伟玺, 张宇琦, 李游. 激光与倾斜点云精确配准与无缝融合[J]. 测绘通报, 2022, 0(4): 6-10.
[12]	张驰, 白志辉, 李亮, 陈冉丽, 吴侃. 利用三维激光扫描技术监测矿区桥梁结构形变[J]. 测绘通报, 2022, 0(4): 122-129.
[13]	许志华, 逯行政, 彭远航, 杨可明, 王宇敏. 依托航空模拟平台的激光雷达技术课程实践教学装备[J]. 测绘通报, 2022, 0(4): 162-166.
[14]	王贝, 叶险峰, 王军宁. 利用点云切片提取技术分析桥梁形变[J]. 测绘通报, 2022, 0(4): 167-171.
[15]	普东东, 丁海勇. 融合超体素与成对链接聚类的LiDAR点云分割算法[J]. 测绘通报, 2022, 0(3): 65-69.

一种基于点云法向量的基准特征提取与倾斜分析方法

A datum feature extraction and deformation analysis method based on normal vector of point cloud

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价