Hierarchical Registration Method for Airborne and Vehicle LiDAR Point Cloud

A new hierarchical method for the automatic registration of airborne and vehicle light detection and ranging (LiDAR) data is proposed, using three-dimensional (3D) road networks and 3D building contours. Firstly, 3D road networks are extracted from airborne LiDAR data and then registered with vehicle trajectory lines. During the registration of airborne road networks and vehicle trajectory lines, a network matching rate is introduced for the determination of reliable transformation matrix. Then, the RIMM (reversed iterative mathematic morphological) method and a height value accumulation method are employed to extract 3D building contours from airborne and vehicle LiDAR data, respectively. The Rodriguez matrix and collinearity equation are used for the determination of conjugate building contours. Based on this, a rule is defined to determine reliable conjugate contours, which are finally used for the fine registration of airborne and vehicle LiDAR data. The experiments show that the coarse registration method with 3D road networks can contribute to a reliable initial registration result, and the fine registration using 3D building contours obtains a final registration result with high reliability and geometric accuracy.

[1]  O. Sass,et al.  Combining airborne and terrestrial laser scanning for quantifying erosion and deposition by a debris flow event , 2012 .

[2]  Jianping Wu,et al.  A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data , 2013, Remote. Sens..

[3]  J. Gong,et al.  3D Building Model Reconstruction from Multi-view Aerial Imagery and Lidar Data , 2011 .

[4]  Zeming Lin,et al.  An automatic registration algorithm for the scattered point clouds based on the curvature feature , 2013 .

[5]  Teng Huang,et al.  Robust Algorithm for Registration of Building Point Clouds Using Planar Patches , 2012 .

[6]  Gaia Vaglio Laurin,et al.  Airborne LiDAR Detects Selectively Logged Tropical Forest Even in an Advanced Stage of Recovery , 2015, Remote. Sens..

[7]  Kiyun Yu,et al.  Adjustment of Discrepancies Between LIDAR Data Strips Using Linear Features , 2007, IEEE Geoscience and Remote Sensing Letters.

[8]  Yu Wang,et al.  Extraction of Urban Power Lines from Vehicle-Borne LiDAR Data , 2014, Remote. Sens..

[9]  E. G. Parmehr,et al.  Automatic registration of optical imagery with 3D LiDAR data using statistical similarity , 2014 .

[10]  Yang Dam Eo,et al.  Coregistration of terrestrial lidar points by adaptive scale-invariant feature transformation with constrained geometry , 2012 .

[11]  Kaiguang Zhao,et al.  Ground Filtering Algorithms for Airborne LiDAR Data: A Review of Critical Issues , 2010, Remote. Sens..

[12]  Jen-Jer Jaw,et al.  Registration of ground‐based LiDAR point clouds by means of 3D line features , 2008 .

[13]  Hangbin Wu,et al.  Feature-constrained registration of building point clouds acquired by terrestrial and airborne laser scanners , 2014 .

[14]  Stefan Hinz,et al.  Fast and automatic image-based registration of TLS data , 2011 .

[15]  Manchun Li,et al.  Semi-Automatic Registration of Airborne and Terrestrial Laser Scanning Data Using Building Corner Matching with Boundaries as Reliability Check , 2013, Remote. Sens..

[16]  Kourosh Khoshelham,et al.  Localized Registration of Point Clouds of Botanic Trees , 2013, IEEE Geoscience and Remote Sensing Letters.

[17]  Yanming Chen,et al.  Three-Dimensional Reconstruction of Large Multilayer Interchange Bridge Using Airborne LiDAR Data , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[18]  Michael Becht,et al.  From geotechnical analysis to quantification and modelling using LiDAR data: a study on rockfall in the Reintal catchment, Bavarian Alps, Germany , 2012 .

[19]  E. Zelniker,et al.  Detection and vectorization of roads from lidar data , 2007 .

[20]  Tee-Ann Teo,et al.  Surface-Based Registration of Airborne and Terrestrial Mobile LiDAR Point Clouds , 2014, Remote. Sens..

[21]  J. Hyyppä,et al.  Laser scanning applications in fluvial studies , 2011 .

[22]  Yanming Chen,et al.  Shiftable Leading Point Method for High Accuracy Registration of Airborne and Terrestrial LiDAR Data , 2015, Remote. Sens..

[23]  Qingquan Li,et al.  Automated extraction of street-scene objects from mobile lidar point clouds , 2012 .

[24]  Christian Früh,et al.  Constructing 3D City Models by Merging Aerial and Ground Views , 2003, IEEE Computer Graphics and Applications.

[25]  Hui Chen,et al.  3D free-form object recognition in range images using local surface patches , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[26]  Norbert Haala,et al.  Efficient integration of aerial and terrestrial laser data for virtual city modeling using LASERMAPs , 2005 .

[27]  Claus Brenner,et al.  Coarse orientation of terrestrial laser scans in urban environments , 2008 .

[28]  Liang Cheng,et al.  Building region derivation from LiDAR data using a reversed iterative mathematic morphological algorithm , 2013 .

[29]  Kostas Daniilidis,et al.  Fully Automatic Registration of 3D Point Clouds , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[30]  Peter Biber,et al.  The normal distributions transform: a new approach to laser scan matching , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[31]  A. Zakhor,et al.  Fast Surface Reconstruction and Segmentation with Ground-Based and Airborne LIDAR Range Data , 2009 .

[32]  Derek D. Lichti,et al.  A method for automated registration of unorganised point clouds , 2008 .

[33]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[34]  Wolfgang von Hansen.  ROBUST AUTOMATIC MARKER-FREE REGISTRATION OF TERRESTRIAL SCAN DATA , 2006 .

[35]  Suya You,et al.  Approaches to Large-Scale Urban Modeling , 2003, IEEE Computer Graphics and Applications.

[36]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[37]  Xianfeng Huang,et al.  Registration of Aerial Imagery and Lidar Data in Desert Areas Using the Centroids of Bushes as Control Information , 2013 .

[38]  S. Filin,et al.  Keypoint based autonomous registration of terrestrial laser point-clouds , 2008 .

[39]  Juha Hyyppä,et al.  Detection of Vertical Pole-Like Objects in a Road Environment Using Vehicle-Based Laser Scanning Data , 2010, Remote. Sens..