Luminance-Corrected 3D Point Clouds for Road and Street Environments
A novel approach to evaluating night-time road and street environment lighting conditions through 3D point clouds is presented. The combination of luminance imaging and 3D point cloud acquired with a terrestrial laser scanner was used for analyzing 3D luminance on the road surface. A calculation of...
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doaj-6fd685e92a234b72bc2da1cbb381007b2020-11-24T23:23:08ZengMDPI AGRemote Sensing2072-42922015-09-0179113891140210.3390/rs70911389rs70911389Luminance-Corrected 3D Point Clouds for Road and Street EnvironmentsMatti T. Vaaja0Matti Kurkela1Juho-Pekka Virtanen2Mikko Maksimainen3Hannu Hyyppä4Juha Hyyppä5Eino Tetri6Department of Real Estate, Planning and Geoinformatics, Centre of Excellence in Laser Scanning Research (CoE-LaSR), Aalto University, FI-00076 Aalto, FinlandDepartment of Real Estate, Planning and Geoinformatics, Centre of Excellence in Laser Scanning Research (CoE-LaSR), Aalto University, FI-00076 Aalto, FinlandDepartment of Real Estate, Planning and Geoinformatics, Centre of Excellence in Laser Scanning Research (CoE-LaSR), Aalto University, FI-00076 Aalto, FinlandDepartment of Electrical Engineering and Automation, Lighting Unit, Aalto University, FI-00076 Aalto, FinlandDepartment of Real Estate, Planning and Geoinformatics, Centre of Excellence in Laser Scanning Research (CoE-LaSR), Aalto University, FI-00076 Aalto, FinlandFinnish Geospatial Research Institute (FGI), Centre of Excellence in Laser Scanning Research (CoE-LaSR), Geodeetinrinne 2, FI-02430 Masala, FinlandDepartment of Electrical Engineering and Automation, Lighting Unit, Aalto University, FI-00076 Aalto, FinlandA novel approach to evaluating night-time road and street environment lighting conditions through 3D point clouds is presented. The combination of luminance imaging and 3D point cloud acquired with a terrestrial laser scanner was used for analyzing 3D luminance on the road surface. A calculation of the luminance (cd/m2) was based on the RGB output values of a Nikon D800E digital still camera. The camera was calibrated with a reference luminance source. The relative orientation between the luminance images and intensity image of the 3D point cloud was solved in order to integrate the data sets into the same coordinate system. As a result, the 3D model of road environment luminance is illustrated and the ability to exploit the method for evaluating the luminance distribution on the road surface is presented. Furthermore, the limitations and future prospects of the methodology are addressed. The method provides promising results for studying road lighting conditions in future lighting optimizations. The paper presents the methodology and its experimental application on a road section which consists of five luminaires installed on one side of a two-lane road in Otaniemi, Espoo, Finland.http://www.mdpi.com/2072-4292/7/9/11389road environmentlighting3Dpoint cloudsluminanceterrestrial laser scanning |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Matti T. Vaaja Matti Kurkela Juho-Pekka Virtanen Mikko Maksimainen Hannu Hyyppä Juha Hyyppä Eino Tetri |
spellingShingle |
Matti T. Vaaja Matti Kurkela Juho-Pekka Virtanen Mikko Maksimainen Hannu Hyyppä Juha Hyyppä Eino Tetri Luminance-Corrected 3D Point Clouds for Road and Street Environments Remote Sensing road environment lighting 3D point clouds luminance terrestrial laser scanning |
author_facet |
Matti T. Vaaja Matti Kurkela Juho-Pekka Virtanen Mikko Maksimainen Hannu Hyyppä Juha Hyyppä Eino Tetri |
author_sort |
Matti T. Vaaja |
title |
Luminance-Corrected 3D Point Clouds for Road and Street Environments |
title_short |
Luminance-Corrected 3D Point Clouds for Road and Street Environments |
title_full |
Luminance-Corrected 3D Point Clouds for Road and Street Environments |
title_fullStr |
Luminance-Corrected 3D Point Clouds for Road and Street Environments |
title_full_unstemmed |
Luminance-Corrected 3D Point Clouds for Road and Street Environments |
title_sort |
luminance-corrected 3d point clouds for road and street environments |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2015-09-01 |
description |
A novel approach to evaluating night-time road and street environment lighting conditions through 3D point clouds is presented. The combination of luminance imaging and 3D point cloud acquired with a terrestrial laser scanner was used for analyzing 3D luminance on the road surface. A calculation of the luminance (cd/m2) was based on the RGB output values of a Nikon D800E digital still camera. The camera was calibrated with a reference luminance source. The relative orientation between the luminance images and intensity image of the 3D point cloud was solved in order to integrate the data sets into the same coordinate system. As a result, the 3D model of road environment luminance is illustrated and the ability to exploit the method for evaluating the luminance distribution on the road surface is presented. Furthermore, the limitations and future prospects of the methodology are addressed. The method provides promising results for studying road lighting conditions in future lighting optimizations. The paper presents the methodology and its experimental application on a road section which consists of five luminaires installed on one side of a two-lane road in Otaniemi, Espoo, Finland. |
topic |
road environment lighting 3D point clouds luminance terrestrial laser scanning |
url |
http://www.mdpi.com/2072-4292/7/9/11389 |
work_keys_str_mv |
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