Automated registration of dense terrestrial laser-scanning point clouds using curves

Wang, Jinhu; Zang, Yufu

doi:10.1016/j.isprsjprs.2014.05.012

Cited by 111 publications

(62 citation statements)

References 28 publications

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“…Large numbers of studies using line features to register point clouds have been reported. For instance, the intersection lines of neighboring planes (Stamos and Leordeanu, 2003), 3D straight-lines (Habib et al, 2005, Al-Durgham andHabib, 2013), and spatial curves (Yang and Zang, 2014) are used as matching primitives. Whereas, plane correspondences (Dold and Brenner, 2006, Von Hansen, 2006, Xiao et al, 2012 and surface correspondences (Ge and Wunderlich, 2016) are frequently used as geometric primitives for alignment as well.…”

Section: Related Workmentioning

confidence: 99%

Automated Coarse Registration of Point Clouds in 3d Urban Scenes Using Voxel Based Plane Constraint

Boerner

Yao

et al. 2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:For obtaining a full coverage of 3D scans in a large-scale urban area, the registration between point clouds acquired via terrestrial laser scanning (TLS) is normally mandatory. However, due to the complex urban environment, the automatic registration of different scans is still a challenging problem. In this work, we propose an automatic marker free method for fast and coarse registration between point clouds using the geometric constrains of planar patches under a voxel structure. Our proposed method consists of four major steps: the voxelization of the point cloud, the approximation of planar patches, the matching of corresponding patches, and the estimation of transformation parameters. In the voxelization step, the point cloud of each scan is organized with a 3D voxel structure, by which the entire point cloud is partitioned into small individual patches. In the following step, we represent points of each voxel with the approximated plane function, and select those patches resembling planar surfaces. Afterwards, for matching the corresponding patches, a RANSAC-based strategy is applied. Among all the planar patches of a scan, we randomly select a planar patches set of three planar surfaces, in order to build a coordinate frame via their normal vectors and their intersection points. The transformation parameters between scans are calculated from these two coordinate frames. The planar patches set with its transformation parameters owning the largest number of coplanar patches are identified as the optimal candidate set for estimating the correct transformation parameters. The experimental results using TLS datasets of different scenes reveal that our proposed method can be both effective and efficient for the coarse registration task. Especially, for the fast orientation between scans, our proposed method can achieve a registration error of less than around 2 degrees using the testing datasets, and much more efficient than the classical baseline methods.

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Section: Related Workmentioning

confidence: 99%

Automated Coarse Registration of Point Clouds in 3d Urban Scenes Using Voxel Based Plane Constraint

Boerner

Yao

et al. 2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…The local features can be any combination of points, lines, curves, and surfaces [49,64,79,106,126]. The approach proposed by Johnson and Hebert [66] computes Spin Image local features in a dense manner, avoiding the error-prone feature detection step.…”

Section: As-built Modelling With Ad Bimmentioning

confidence: 99%

State of research in automatic as-built modelling

Pătrăucean

Armeni

Nahangi

et al. 2015

Advanced Engineering Informatics

267

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“…Recently, curves have also been used for the process by Yang (Yang and Zang, 2014). The fine registration usually is performed using some variant of the iterative closest point algorithm (ICP) (Besl and McKay, 1992, Chetverikov et al, 2002, Minguez et al, 2006.…”

Section: Data Processingmentioning

confidence: 99%

Standalone Terrestrial Laser Scanning for Efficiently Capturing Aec Buildings for as-Built Bim

Bassier

Vergauwen

Genechten

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:With the increasing popularity of as-built building models for the architectural, engineering and construction (AEC) industry, the demand for highly accurate and dense point cloud data is rising. The current data acquisition methods are labour intensive and time consuming. In order to compete with indoor mobile mapping systems (IMMS), surveyors are now opting to use terrestrial laser scanning as a standalone solution. However, there is uncertainty about the accuracy of this approach. The emphasis of this paper is to determine the scope for which terrestrial laser scanners can be used without additional control. Multiple real life test cases are evaluated in order to identify the boundaries of this technique. Furthermore, this research presents a mathematical prediction model that provides an indication of the data accuracy given the project dimensions. This will enable surveyors to make informed discussions about the employability of terrestrial laser scanning without additional control in mid to large-scale projects.

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Automated registration of dense terrestrial laser-scanning point clouds using curves

Cited by 111 publications

References 28 publications

Automated Coarse Registration of Point Clouds in 3d Urban Scenes Using Voxel Based Plane Constraint

Automated Coarse Registration of Point Clouds in 3d Urban Scenes Using Voxel Based Plane Constraint

State of research in automatic as-built modelling

Standalone Terrestrial Laser Scanning for Efficiently Capturing Aec Buildings for as-Built Bim

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