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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2020-08-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
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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 |
work_keys_str_mv |
AT gtakahashi scanlinenormalizationformmsdatameasuredunderdifferentconditions AT gtakahashi scanlinenormalizationformmsdatameasuredunderdifferentconditions AT hmasuda scanlinenormalizationformmsdatameasuredunderdifferentconditions |
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1724540096759201792 |