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...

Full description

Bibliographic Details
Main Authors: Lucía Díaz-Vilariño, Kourosh Khoshelham, Joaquín Martínez-Sánchez, Pedro Arias
Format: Article
Language:English
Published: MDPI AG 2015-02-01
Series:Sensors
Subjects:
BIM
Online Access:http://www.mdpi.com/1424-8220/15/2/3491
id doaj-7b82aab2b7a043da9e11e48fae89aaab
record_format Article
spelling 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
work_keys_str_mv AT luciadiazvilarino 3dmodelingofbuildingindoorspacesandcloseddoorsfromimageryandpointclouds
AT kouroshkhoshelham 3dmodelingofbuildingindoorspacesandcloseddoorsfromimageryandpointclouds
AT joaquinmartinezsanchez 3dmodelingofbuildingindoorspacesandcloseddoorsfromimageryandpointclouds
AT pedroarias 3dmodelingofbuildingindoorspacesandcloseddoorsfromimageryandpointclouds
_version_ 1725778417806213120