3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds
3D models of indoor environments are increasingly gaining importance due to the wide range of applications to which they can be subjected: from redesign and visualization to monitoring and simulation. These models usually exist only for newly constructed buildings; therefore, the development of auto...
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doaj-7b82aab2b7a043da9e11e48fae89aaab2020-11-24T22:19:36ZengMDPI AGSensors1424-82202015-02-011523491351210.3390/s150203491s1502034913D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point CloudsLucía Díaz-Vilariño0Kourosh Khoshelham1Joaquín Martínez-Sánchez2Pedro Arias3Applied Geotechnologies Research Group, University of Vigo. Rúa Maxwell s/n, Campus Lagoas-Marcosende, Vigo 36310, SpainFaculty of Geo-Information Science and Earth Observation, University of Twente, P.O. Box 217, Enschede 7514 AE, The NetherlandsApplied Geotechnologies Research Group, University of Vigo. Rúa Maxwell s/n, Campus Lagoas-Marcosende, Vigo 36310, SpainApplied Geotechnologies Research Group, University of Vigo. Rúa Maxwell s/n, Campus Lagoas-Marcosende, Vigo 36310, Spain3D models of indoor environments are increasingly gaining importance due to the wide range of applications to which they can be subjected: from redesign and visualization to monitoring and simulation. These models usually exist only for newly constructed buildings; therefore, the development of automatic approaches for reconstructing 3D indoors from imagery and/or point clouds can make the process easier, faster and cheaper. Among the constructive elements defining a building interior, doors are very common elements and their detection can be very useful either for knowing the environment structure, to perform an efficient navigation or to plan appropriate evacuation routes. The fact that doors are topologically connected to walls by being coplanar, together with the unavoidable presence of clutter and occlusions indoors, increases the inherent complexity of the automation of the recognition process. In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors based on point clouds and images. The methodology analyses the visibility problem of indoor environments and goes in depth with door candidate detection. The presented approach is tested in real data sets showing its potential with a high door detection rate and applicability for robust and efficient envelope reconstruction.http://www.mdpi.com/1424-8220/15/2/34913D modelingfeature extractionopeningsimageryLiDAR dataBIM |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lucía Díaz-Vilariño Kourosh Khoshelham Joaquín Martínez-Sánchez Pedro Arias |
spellingShingle |
Lucía Díaz-Vilariño Kourosh Khoshelham Joaquín Martínez-Sánchez Pedro Arias 3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds Sensors 3D modeling feature extraction openings imagery LiDAR data BIM |
author_facet |
Lucía Díaz-Vilariño Kourosh Khoshelham Joaquín Martínez-Sánchez Pedro Arias |
author_sort |
Lucía Díaz-Vilariño |
title |
3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds |
title_short |
3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds |
title_full |
3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds |
title_fullStr |
3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds |
title_full_unstemmed |
3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds |
title_sort |
3d modeling of building indoor spaces and closed doors from imagery and point clouds |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2015-02-01 |
description |
3D models of indoor environments are increasingly gaining importance due to the wide range of applications to which they can be subjected: from redesign and visualization to monitoring and simulation. These models usually exist only for newly constructed buildings; therefore, the development of automatic approaches for reconstructing 3D indoors from imagery and/or point clouds can make the process easier, faster and cheaper. Among the constructive elements defining a building interior, doors are very common elements and their detection can be very useful either for knowing the environment structure, to perform an efficient navigation or to plan appropriate evacuation routes. The fact that doors are topologically connected to walls by being coplanar, together with the unavoidable presence of clutter and occlusions indoors, increases the inherent complexity of the automation of the recognition process. In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors based on point clouds and images. The methodology analyses the visibility problem of indoor environments and goes in depth with door candidate detection. The presented approach is tested in real data sets showing its potential with a high door detection rate and applicability for robust and efficient envelope reconstruction. |
topic |
3D modeling feature extraction openings imagery LiDAR data BIM |
url |
http://www.mdpi.com/1424-8220/15/2/3491 |
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