AUTOMATED COARSE REGISTRATION OF POINT CLOUDS IN 3D URBAN SCENES USING VOXEL BASED PLANE CONSTRAINT
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 prob...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-09-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-2-W4/185/2017/isprs-annals-IV-2-W4-185-2017.pdf |
| Summary: | 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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| ISSN: | 2194-9042 2194-9050 |