SCANLINE NORMALIZATION FOR MMS DATA MEASURED UNDER DIFFERENT CONDITIONS

Mobile Mapping System (MMS) equipped with a high-density LiDAR scanner is widely used for mapping. Various automatic mapping methods have been proposed for point clouds measured by the high-density LiDAR scanner on the MMS. However, careful parameter tuning is often required according to measurement...

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Main Authors: G. Takahashi, H. Masuda
Format: Article
Language:English
Published: Copernicus Publications 2020-08-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/325/2020/isprs-archives-XLIII-B2-2020-325-2020.pdf
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spelling doaj-adcde390ab154ff9a9d1a600fa847bd52020-11-25T03:39:14ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-08-01XLIII-B2-202032533110.5194/isprs-archives-XLIII-B2-2020-325-2020SCANLINE NORMALIZATION FOR MMS DATA MEASURED UNDER DIFFERENT CONDITIONSG. Takahashi0G. Takahashi1H. Masuda2Dept. of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo, JapanDept. of R&D, KOKUSAI KOGYO CO., LTD., 2-24-1 Harumi-cho, Fuchu-shi, Tokyo, 183-0057, JapanDept. of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo, JapanMobile Mapping System (MMS) equipped with a high-density LiDAR scanner is widely used for mapping. Various automatic mapping methods have been proposed for point clouds measured by the high-density LiDAR scanner on the MMS. However, careful parameter tuning is often required according to measurement conditions. In this paper, we propose a method to generate normalized scanlines from point clouds captured using the MMS. Normalized scanlines are useful to avoid parameter tuning depending on the measurement conditions. In order to evaluate the validity of our method, we extracted road boundaries with the same parameters from two point clouds measured under different conditions. In our evaluation, our method could detect almost the same road boundaries from the two point clouds using the same parameter settings.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/325/2020/isprs-archives-XLIII-B2-2020-325-2020.pdf
collection DOAJ
language English
format Article
sources DOAJ
author G. Takahashi
G. Takahashi
H. Masuda
spellingShingle G. Takahashi
G. Takahashi
H. Masuda
SCANLINE NORMALIZATION FOR MMS DATA MEASURED UNDER DIFFERENT CONDITIONS
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet G. Takahashi
G. Takahashi
H. Masuda
author_sort G. Takahashi
title SCANLINE NORMALIZATION FOR MMS DATA MEASURED UNDER DIFFERENT CONDITIONS
title_short SCANLINE NORMALIZATION FOR MMS DATA MEASURED UNDER DIFFERENT CONDITIONS
title_full SCANLINE NORMALIZATION FOR MMS DATA MEASURED UNDER DIFFERENT CONDITIONS
title_fullStr SCANLINE NORMALIZATION FOR MMS DATA MEASURED UNDER DIFFERENT CONDITIONS
title_full_unstemmed SCANLINE NORMALIZATION FOR MMS DATA MEASURED UNDER DIFFERENT CONDITIONS
title_sort scanline normalization for mms data measured under different conditions
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2020-08-01
description Mobile Mapping System (MMS) equipped with a high-density LiDAR scanner is widely used for mapping. Various automatic mapping methods have been proposed for point clouds measured by the high-density LiDAR scanner on the MMS. However, careful parameter tuning is often required according to measurement conditions. In this paper, we propose a method to generate normalized scanlines from point clouds captured using the MMS. Normalized scanlines are useful to avoid parameter tuning depending on the measurement conditions. In order to evaluate the validity of our method, we extracted road boundaries with the same parameters from two point clouds measured under different conditions. In our evaluation, our method could detect almost the same road boundaries from the two point clouds using the same parameter settings.
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/325/2020/isprs-archives-XLIII-B2-2020-325-2020.pdf
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