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High-Resolution Representation for Mobile Mapping Data in Curved Regular Grid Model

As mobile mapping systems become a mature technology, there are many applications for the process of the measured data. One interesting application is the use of driving simulators that can be used to analyze the data of tire vibration or vehicle simulations. In previous research, we presented our p...

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Autores principales: Su, Jingxin, Miyazaki, Ryuji, Tamaki, Toru, Kaneda, Kazufumi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6960753/
https://www.ncbi.nlm.nih.gov/pubmed/31817491
http://dx.doi.org/10.3390/s19245373
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author Su, Jingxin
Miyazaki, Ryuji
Tamaki, Toru
Kaneda, Kazufumi
author_facet Su, Jingxin
Miyazaki, Ryuji
Tamaki, Toru
Kaneda, Kazufumi
author_sort Su, Jingxin
collection PubMed
description As mobile mapping systems become a mature technology, there are many applications for the process of the measured data. One interesting application is the use of driving simulators that can be used to analyze the data of tire vibration or vehicle simulations. In previous research, we presented our proposed method that can create a precise three-dimensional point cloud model of road surface regions and trajectory points. Our data sets were obtained by a vehicle-mounted mobile mapping system (MMS). The collected data were converted into point cloud data and color images. In this paper, we utilize the previous results as input data and present a solution that can generate an elevation grid for building an OpenCRG model. The OpenCRG project was originally developed to describe road surface elevation data, and also defined an open file format. As it can be difficult to generate a regular grid from point cloud directly, the road surface is first divided into straight lines, circular arcs, and and clothoids. Secondly, a non-regular grid which contains the elevation of road surface points is created for each road surface segment. Then, a regular grid is generated by accurately interpolating the elevation values from the non-regular grid. Finally, the curved regular grid (CRG) model files are created based on the above procedures, and can be visualized by OpenCRG tools. The experimental results on real-world data show that the proposed approach provided a very-high-resolution road surface elevation model.
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spelling pubmed-69607532020-01-23 High-Resolution Representation for Mobile Mapping Data in Curved Regular Grid Model Su, Jingxin Miyazaki, Ryuji Tamaki, Toru Kaneda, Kazufumi Sensors (Basel) Article As mobile mapping systems become a mature technology, there are many applications for the process of the measured data. One interesting application is the use of driving simulators that can be used to analyze the data of tire vibration or vehicle simulations. In previous research, we presented our proposed method that can create a precise three-dimensional point cloud model of road surface regions and trajectory points. Our data sets were obtained by a vehicle-mounted mobile mapping system (MMS). The collected data were converted into point cloud data and color images. In this paper, we utilize the previous results as input data and present a solution that can generate an elevation grid for building an OpenCRG model. The OpenCRG project was originally developed to describe road surface elevation data, and also defined an open file format. As it can be difficult to generate a regular grid from point cloud directly, the road surface is first divided into straight lines, circular arcs, and and clothoids. Secondly, a non-regular grid which contains the elevation of road surface points is created for each road surface segment. Then, a regular grid is generated by accurately interpolating the elevation values from the non-regular grid. Finally, the curved regular grid (CRG) model files are created based on the above procedures, and can be visualized by OpenCRG tools. The experimental results on real-world data show that the proposed approach provided a very-high-resolution road surface elevation model. MDPI 2019-12-05 /pmc/articles/PMC6960753/ /pubmed/31817491 http://dx.doi.org/10.3390/s19245373 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Su, Jingxin
Miyazaki, Ryuji
Tamaki, Toru
Kaneda, Kazufumi
High-Resolution Representation for Mobile Mapping Data in Curved Regular Grid Model
title High-Resolution Representation for Mobile Mapping Data in Curved Regular Grid Model
title_full High-Resolution Representation for Mobile Mapping Data in Curved Regular Grid Model
title_fullStr High-Resolution Representation for Mobile Mapping Data in Curved Regular Grid Model
title_full_unstemmed High-Resolution Representation for Mobile Mapping Data in Curved Regular Grid Model
title_short High-Resolution Representation for Mobile Mapping Data in Curved Regular Grid Model
title_sort high-resolution representation for mobile mapping data in curved regular grid model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6960753/
https://www.ncbi.nlm.nih.gov/pubmed/31817491
http://dx.doi.org/10.3390/s19245373
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AT tamakitoru highresolutionrepresentationformobilemappingdataincurvedregulargridmodel
AT kanedakazufumi highresolutionrepresentationformobilemappingdataincurvedregulargridmodel