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Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping

Automated processing of the data provided by a laser-based mobile mapping system will be a necessity due to the huge amount of data produced. In the future, vehicle-based laser scanning, here called mobile mapping, should see considerable use for road environment modelling. Since the geometry of the...

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Detalles Bibliográficos
Autores principales: Jaakkola, Anttoni, Hyyppä, Juha, Hyyppä, Hannu, Kukko, Antero
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3705502/
https://www.ncbi.nlm.nih.gov/pubmed/27873812
http://dx.doi.org/10.3390/s8095238
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author Jaakkola, Anttoni
Hyyppä, Juha
Hyyppä, Hannu
Kukko, Antero
author_facet Jaakkola, Anttoni
Hyyppä, Juha
Hyyppä, Hannu
Kukko, Antero
author_sort Jaakkola, Anttoni
collection PubMed
description Automated processing of the data provided by a laser-based mobile mapping system will be a necessity due to the huge amount of data produced. In the future, vehicle-based laser scanning, here called mobile mapping, should see considerable use for road environment modelling. Since the geometry of the scanning and point density is different from airborne laser scanning, new algorithms are needed for information extraction. In this paper, we propose automatic methods for classifying the road marking and kerbstone points and modelling the road surface as a triangulated irregular network. On the basis of experimental tests, the mean classification accuracies obtained using automatic method for lines, zebra crossings and kerbstones were 80.6%, 92.3% and 79.7%, respectively.
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spelling pubmed-37055022013-07-09 Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping Jaakkola, Anttoni Hyyppä, Juha Hyyppä, Hannu Kukko, Antero Sensors (Basel) Article Automated processing of the data provided by a laser-based mobile mapping system will be a necessity due to the huge amount of data produced. In the future, vehicle-based laser scanning, here called mobile mapping, should see considerable use for road environment modelling. Since the geometry of the scanning and point density is different from airborne laser scanning, new algorithms are needed for information extraction. In this paper, we propose automatic methods for classifying the road marking and kerbstone points and modelling the road surface as a triangulated irregular network. On the basis of experimental tests, the mean classification accuracies obtained using automatic method for lines, zebra crossings and kerbstones were 80.6%, 92.3% and 79.7%, respectively. Molecular Diversity Preservation International (MDPI) 2008-09-01 /pmc/articles/PMC3705502/ /pubmed/27873812 http://dx.doi.org/10.3390/s8095238 Text en © 2008 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Jaakkola, Anttoni
Hyyppä, Juha
Hyyppä, Hannu
Kukko, Antero
Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping
title Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping
title_full Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping
title_fullStr Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping
title_full_unstemmed Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping
title_short Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping
title_sort retrieval algorithms for road surface modelling using laser-based mobile mapping
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3705502/
https://www.ncbi.nlm.nih.gov/pubmed/27873812
http://dx.doi.org/10.3390/s8095238
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