球形标靶的固定式扫描大点云自动定向方法

doi:10.11947/j.AGCS.2015.20130357

测绘学报 ›› 2015, Vol. 44 ›› Issue (4): 431-437.doi: 10.11947/j.AGCS.2015.20130357

球形标靶的固定式扫描大点云自动定向方法

姚吉利¹, 马宁¹, 贾象阳¹, 徐广鹏¹, 谢建春²

1. 山东理工大学建筑工程学院, 山东淄博 255000;
2. 山东省地质测绘院, 山东济南 250014

收稿日期:2013-12-25 修回日期:2014-11-24 出版日期:2015-04-20 发布日期:2015-04-27
作者简介:姚吉利(1964—),男,教授,主要从事三维激光扫描数据处理方面的研究.E-mail:ysy_941123@sdut.edu.cn
基金资助:
国家自然科学基金(41074001)

An Approach for Automatic Orientation of Big Point Clouds from the Stationary Scanners Based on the Spherical Targets

YAO Jili¹, MA Ning¹, JIA Xiangyang¹, XU Guangpeng¹, XIE Jianchun²

1. School of Architectural Engineering, Shandong University of Technology, Zibo 255000, China;
2. Geological Surveying & Mapping Institute of Shandong Province, Jinan 250014, China

Received:2013-12-25 Revised:2014-11-24 Online:2015-04-20 Published:2015-04-27
Supported by:
The National Natural Science Foundation of China(No.41074001)

摘要/Abstract

摘要： 根据目前地面激光扫描数据获取速度快、数据量大、测量距离远、专用特殊材料制作的标靶识别距离近、点云定向数据处理相对滞后、自动化程度低、不能适应远距离地形测量的现状,提出了从大点云中(每站1亿点以上)自动探测远距离标靶的点云定向方法.该方法首先根据标靶控制点的工程测量坐标信息,搜索到标靶所在点云环,然后对各点云环进行扇形分区,快速探测标靶,获取标靶中心扫描坐标,最后平差计算扫描仪位置参数和姿态参数,实现点云坐标到工程测量坐标的转换.该方法在普通配置的计算机上得到实现,并成功用于远距离山区地形测量,其中定向标靶半径0.162m,标靶到扫描站距离在180～700m之间.

关键词: 大点云, 球形标靶, 扫描坐标, 工程测量坐标, 坐标转换, 地形测绘

Abstract: Terrestrial laser scanning (TLS) technology has high speed of data acquisition, large amount of point cloud, long distance of measuring. However, there are some disadvantages such as distance limitation in target detecting, hysteresis in point clouds processing, low automation and weaknesses of adapting long-distance topographic survey. In this case, we put forward a method on long-range targets detecting in big point clouds orientation. The method firstly searches point cloud rings that contain targets according to their engineering coordinate system. Then the detected rings are divided into sectors to detect targets in a very short time so as to obtain central coordinates of these targets. Finally, the position and orientation parameters of scanner are calculated and point clouds in scanner's own coordinate system(SOCS) are converted into engineering coordinate system. The method is able to be applied in ordinary computers for long distance topographic(the distance between scanner and targets ranges from 180 to 700 m) survey in mountainous areas with targets radius of 0.162m.

Key words: big point clouds, spherical targets, SOCS, engineering coordinate system, coordinate converting, topographic survey

中图分类号:

P232

姚吉利, 马宁, 贾象阳, 徐广鹏, 谢建春. 球形标靶的固定式扫描大点云自动定向方法[J]. 测绘学报, 2015, 44(4): 431-437.

YAO Jili, MA Ning, JIA Xiangyang, XU Guangpeng, XIE Jianchun. An Approach for Automatic Orientation of Big Point Clouds from the Stationary Scanners Based on the Spherical Targets[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(4): 431-437.

参考文献

[1] LEMMENS M. Terrestrial Laser Scanning[M]//LEMMENS M. Geo-information. Netherlands: Springer, 2011: 101-121.
[2] WANDA M, BERNER A, BOKELOH M, et al. Processing and Interactive Editing of Huge Point Clouds from 3D Scanners[J]. Computers & Graphics, 2008, 32(2): 204-220.
[3] ROHRSCHNEIDER K, BURK R O, VÖLCKER H E. Reproducibility of Topometric Data Acquisition in Normal and Glaucomatous Optic Nerve Heads with the Laser Tomographic Scanner[J]. Graefe's Archive for Clinical and Experimental Ophthalmology, 1993, 231(8): 457-464.
[4] CASULA G, MORA P, BIANCHI M. Detection of Terrain Morphologic Features Using GPS, TLS, and Land Surveys: “Tana Della Volpe” Blind Valley Case Study[J]. Journal of Surveying Engineering, 2010, 136(3): 132-138.
[5] BARNEA S, FILIN S. Key Point Based Autonomous Registration of Terrestrial Laser Point-clouds[J]. ISPRS Journal of Photogrammetry & Remote Sensing, 2008, 63(1): 19-35.)
[6] JEŽ O. 3D Mapping and Localization Using Leveled Map Accelerated ICP[C]//Bruyninckx H, Prieučil L, Kulich M. European Robotics Symposium 2008. Berlin Heidelberg: Springer, 2008: 343-353.
[7] MANDOW A, MARTÍNEZ J L, REINA A J, et al. Fast Range-Independent Spherical Subsampling of 3D Laser Scanner Points and Data Reduction Performance Evaluation for Scene Registration[J]. Pattern Recognition Letters, 2010, 31(11): 1239-1250.)
[8] KENNER R, PHILLIPS M, DANIOTH C, et al. Investigation of Rock and Ice Loss in a Recently Deglaciated Mountain Rock Wall Using Terrestrial Laser Scanning: Gemsstock, Swiss Alps[J]. Cold Regions Science and Technology, 2011, 67(3): 157-164.
[9] BRENNER C, DOLD C, RIPPERDA N. Coarse Orientation of Terrestrial Laser Scans in Urban Environments[J]. ISPRS Journal of Photogrammetry & Remote Sensing, 2008, 63: 4-18.
[10] ZHAO Xu, ZHOU Keqin, YAN Li, et al. 3D Reconstruction Method for Large Scale Relic Landscape from Laser Point Cloud[J]. Geomatics and Information Science of Wuhan University, 2008, 33(7): 684-687. (赵煦, 周克勤, 闫利, 等. 基于激光点云的大型文物景观三维重建方法[J]. 武汉大学学报: 信息科学版, 2008, 33(7): 684-687.)
[11] BESL P J, MCKAY N D. A Method for Registration of 3-D Shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(2): 239-256.
[12] BORNAZ L, LINGUA A, RINAUDO F. A New Software for the Automatic Registration of 3D Digital Models Acquired Using Laser Scanner Devices[C]//CIPA WG 6 International Workshop on Scanning for Cultural Heritage Recording, Corfu: [s.n.], 2002: 52-57.
[13] PARK S Y. A Fast Point-to-Tangent Plane Technique for Multi-view Registration[C]//Fourth International Conference on 3-D Digital Imaging and Modeling, 2003. 3DIM 2003, Banff, Alta: IEEE, 2003: 276-283.
[14] ZHENG Dehua, YUE Dongjie, YUE Jianping. Geometric Feature Constraint Based Algorithm for Building Scanning Point Cloud Registration[J]. Acta Geodaetica et Cartographica Sinica, 2008, 37(4): 464-468. (郑德华, 岳东杰, 岳建平. 基于几何特征约束的建筑物点云配准算法[J]. 测绘学报, 2008, 37(4): 464-468.)
[15] ZHANG Jianqing, ZHAI Ruifang, ZHENG Shunyi. Automatic Seamless Registration of 3D Multiple Range Views[J]. Geomatics and Information Science of Wuhan University, 2007, 32(2): 100-103. (张剑清, 翟瑞芳, 郑顺义. 激光扫描多三维视图的全自动无缝镶嵌[J]. 武汉大学学报: 信息科学版, 2007, 32(2): 100-103.)
[16] MECHELKE K, KERSTEN T P, LINDSTAEDT M. Comparative Investigations into the Accuracy Behaviour of the New Generation of Terrestrial Laser Scanning Systems[J]. Optical 3-D Measurement Techniques VIII, 2007, 1: 319-327.
[17] BOEHLER W, VICENT M B, MARBS A. Investigating Laser Scanner Accuracy[J]. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2003, 34(5): 696-701.
[18] HODGE R A. Using Simulated Terrestrial Laser Scanning to Analyse Errors in High-resolution Scan Data of Irregular Surfaces[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2010, 65(2): 227-240.
[19] JOCHEM A HÖFLE B, WICHMANN V, et al. Area-Wide Roof Plane Segmentation in Airborne LiDAR Point Clouds[J]. Computers, Environment and Urban Systems, 2012, 36(1): 54-64.)
[20] SANKARANARAYANAN J, SAMET H, VARSHNEY A. A Fast All Nearest Neighbor Algorithm for Applications Involving Large Point-Clouds[J]. Computers & Graphics, 2007, 31(2): 157-174.
[21] MA H C WANG Z Y. Distributed Data Organization and Parallel Data Retrieval Methods for Huge Laser Scanner Point Clouds[J]. Computers & Geosciences, 2011, 37(2): 193-201.
[22] FLÖRY S, HOFER M. Surface Fitting and Registration of Point Clouds Using Approximations of the Unsigned Distance Function[J]. Computer Aided Geometric Design, 2010, 27(1): 60-77.
[23] YAO Jili. SARC Model of Three-dimensional Coordinate Transformation[J]. Geomatics and Information Science of Wuhan University, 2005, 30(9): 825-828. (姚吉利. 三维坐标转换的静态滤波模型[J]. 武汉大学学报: 信息科学版, 2005, 30(9): 825-828.)
[24] YAO Jili. Rigorous Formula for Direct Calculating Parameter in 3D Transformation[J]. Bulletin of Surveying and Mapping, 2006(5): 7-10. (姚吉利. 3维坐标转换参数直接计算的严密公式[J]. 测绘通报, 2006(5): 7-10.)
[25] YAO Jili, HAN Baomin, YANG Yuanxi. Applications of Lodrigues Matrix in 3D Coordinate Transformation[J]. Geomatics and Information Science of Wuhan University, 2006, 31(12): 1094-1096. (姚吉利, 韩保民, 杨元喜. 罗德里格矩阵在三维坐标转换严密解算中的应用[J]. 武汉大学学报: 信息科学版, 2006, 31(12): 1094-1096.)
[26] PU Shi, LI Jingwei, GUO Siqing. Registration of Terrestrial Laser Point Clouds by Fusing Semantic Features and GPS Positions[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(5): 545-550. (浦石, 李京伟, 郭四清. 融合语义特征与GPS位置的地面激光点云拼接方法[J]. 测绘学报, 2014, 43(5): 545-550.)
[27] YAO Jili, JIA Xiangyang, MA Ning, et al. Auto-registration for Terrestrial Laser Scanning Multi-stations Point Clouds with Bundle Block Adjustment Method [J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(7): 711-716. (姚吉利, 贾象阳, 马宁, 等. 光束法区域网平差的地面激光扫描多站点云自动定向方法[J]. 测绘学报, 2014, 43(7): 711-716.)
[28] YAO Jili, JIA Xiangyang, MA Ning, et al. Auto-Orientation of Multi-stations TLS Point Clouds with Bundle Block Adjustment[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(8): 835-841.(姚吉利, 贾象阳, 马宁, 等. 地面激光扫描多站点云整体定向平差模型[J]. 测绘学报, 2014, 43(8): 835-841.)

球形标靶的固定式扫描大点云自动定向方法

An Approach for Automatic Orientation of Big Point Clouds from the Stationary Scanners Based on the Spherical Targets

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 10

编辑推荐

Metrics

本文评价

[1]	单杰, 田祥希, 李爽, 李韧菲. 星载激光测高技术进展[J]. 测绘学报, 2022, 51(6): 964-982.
[2]	郭迎钢, 李宗春, 何华, 王志颖. 三维坐标转换公共点最优权值的单纯形搜索算法[J]. 测绘学报, 2020, 49(8): 1004-1013.
[3]	苗润龙, 庞硕, 姜大鹏, 董早鹏. 海洋自主航行器多海湾区域完全遍历路径规划[J]. 测绘学报, 2019, 48(2): 256-264.
[4]	曾安敏, 明锋. 顾及框架点坐标误差的三维基准转换严密模型[J]. 测绘学报, 2017, 46(1): 16-25.
[5]	王乐洋, 余航, 陈晓勇. Partial EIV模型的解法[J]. 测绘学报, 2016, 45(1): 22-29.
[6]	姚吉利马宁韩保民. 地面激光扫描多站点云整体定向平差模型[J]. 测绘学报, 2014, 43(8): 835-841.
[7]	姚吉利马宁贾象阳韩保民. 光束法区域网平差的地面激光扫描多站点云自动定向方法[J]. 测绘学报, 2014, 43(7): 711-716.
[8]	方兴曾文宪刘经南姚宜斌. 三维坐标转换的通用整体最小二乘算法[J]. 测绘学报, 2014, 43(11): 1139-1143.
[9]	过家春赵秀侠吴艳兰. 空间直角坐标与大地坐标转换的拉格朗日反演方法[J]. 测绘学报, 2014, 43(10): 998-1004.
[10]	袁文,庄大方,袁武,唐志峰,邱冬生. 离散三角网格系统距离量测方法[J]. 测绘学报, 2011, 40(1): 59-65.