Automatic Registration of Terrestrial Laser Scanning Point Clouds using Panoramic Reflectance ImagesReport as inadecuate




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1

Faculty of Aerospace Engineering, Delft University of Technology - Kluyverweg 1, 2629 HS Delft, The Netherlands

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School of Land Science and Technology, China University of Geosciences - Beijing 100083, China

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Department of Geography and Environmental Management, University of Waterloo - Waterloo, Ontario N2L 3G1, Canada

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Research Centre for Remote Sensing and GIS, School of Geography, Beijing Normal University - Beijing 100875, P.R. China

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GNSS Research Centre, Wuhan University - Wuhan 430079, Hubei Province, P.R. China

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OTB Research Institute for Housing, Urban and Mobility Studies, Delft University of Technology - Jaffalaan 9, 2628 BX Delft, The Netherlands





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Abstract This paper presents a new approach to the automatic registration of terrestrial laser scanning TLS point clouds using panoramic reflectance images. The approach follows a two-step procedure that includes both pair-wise registration and global registration. The pair-wise registration consists of image matching pixel-to-pixel correspondence and point cloud registration point-to-point correspondence, as the correspondence between the image and the point cloud pixel-to-point is inherent to the reflectance images. False correspondences are removed by a geometric invariance check. The pixel-to-point correspondence and the computation of the rigid transformation parameters RTPs are integrated into an iterative process that allows for the pair-wise registration to be optimised. The global registration of all point clouds is obtained by a bundle adjustment using a circular self-closure constraint. Our approach is tested with both indoor and outdoor scenes acquired by a FARO LS 880 laser scanner with an angular resolution of 0.036° and 0.045°, respectively. The results show that the pair-wise and global registration accuracies are of millimetre and centimetre orders, respectively, and that the process is fully automatic and converges quickly. View Full-Text

Keywords: Point cloud; Registration; LIDAR; Terrestrial laser scanning; Automation; Image Matching Point cloud; Registration; LIDAR; Terrestrial laser scanning; Automation; Image Matching





Author: Zhizhong Kang 1, 2,* , Jonathan Li 3, Liqiang Zhang 4, Qile Zhao 5 and Sisi Zlatanova 6

Source: http://mdpi.com/



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