Review of mobile laser scanning target-free registration methods for urban areas using improved error metrics

Registration is one of the most important tasks in mobile laser scanning (MLS) point cloud processing. This paper firstly reviews existing target-free matching techniques as well as methods to evaluate the quality of the registration. Next, a new error metric is introduced that takes into account th...

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Main Authors: Nguyen, H.L., Belton, David, Helmholz, Petra
Format: Journal Article
Language:English
Published: WILEY 2019
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/83271
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author Nguyen, H.L.
Belton, David
Helmholz, Petra
author_facet Nguyen, H.L.
Belton, David
Helmholz, Petra
author_sort Nguyen, H.L.
building Curtin Institutional Repository
collection Online Access
description Registration is one of the most important tasks in mobile laser scanning (MLS) point cloud processing. This paper firstly reviews existing target-free matching techniques as well as methods to evaluate the quality of the registration. Next, a new error metric is introduced that takes into account the residuals of check planes as well as their orientation. Experiments using real datasets in combination with reference data were performed to evaluate the suitability of these metrics. The proposed error metric proved to be more suitable for evaluating the quality of point cloud registration than state-of-the-art equivalents. The results also indicate that least squares plane fitting is the best technique for MLS point cloud registration.
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institution Curtin University Malaysia
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language English
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spelling curtin-20.500.11937-832712021-07-15T05:54:14Z Review of mobile laser scanning target-free registration methods for urban areas using improved error metrics Nguyen, H.L. Belton, David Helmholz, Petra Science & Technology Physical Sciences Technology Geography, Physical Geosciences, Multidisciplinary Remote Sensing Imaging Science & Photographic Technology Physical Geography Geology error metric matching quality mobile laser scanning point cloud matching target-free registration SELF-CALIBRATION POINT Registration is one of the most important tasks in mobile laser scanning (MLS) point cloud processing. This paper firstly reviews existing target-free matching techniques as well as methods to evaluate the quality of the registration. Next, a new error metric is introduced that takes into account the residuals of check planes as well as their orientation. Experiments using real datasets in combination with reference data were performed to evaluate the suitability of these metrics. The proposed error metric proved to be more suitable for evaluating the quality of point cloud registration than state-of-the-art equivalents. The results also indicate that least squares plane fitting is the best technique for MLS point cloud registration. 2019 Journal Article http://hdl.handle.net/20.500.11937/83271 10.1111/phor.12293 English WILEY restricted
spellingShingle Science & Technology
Physical Sciences
Technology
Geography, Physical
Geosciences, Multidisciplinary
Remote Sensing
Imaging Science & Photographic Technology
Physical Geography
Geology
error metric
matching quality
mobile laser scanning
point cloud matching
target-free registration
SELF-CALIBRATION
POINT
Nguyen, H.L.
Belton, David
Helmholz, Petra
Review of mobile laser scanning target-free registration methods for urban areas using improved error metrics
title Review of mobile laser scanning target-free registration methods for urban areas using improved error metrics
title_full Review of mobile laser scanning target-free registration methods for urban areas using improved error metrics
title_fullStr Review of mobile laser scanning target-free registration methods for urban areas using improved error metrics
title_full_unstemmed Review of mobile laser scanning target-free registration methods for urban areas using improved error metrics
title_short Review of mobile laser scanning target-free registration methods for urban areas using improved error metrics
title_sort review of mobile laser scanning target-free registration methods for urban areas using improved error metrics
topic Science & Technology
Physical Sciences
Technology
Geography, Physical
Geosciences, Multidisciplinary
Remote Sensing
Imaging Science & Photographic Technology
Physical Geography
Geology
error metric
matching quality
mobile laser scanning
point cloud matching
target-free registration
SELF-CALIBRATION
POINT
url http://hdl.handle.net/20.500.11937/83271