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Appl. Sci. 2018, 8(9), 1529; https://doi.org/10.3390/app8091529

Indoor Building Reconstruction from Occluded Point Clouds Using Graph-Cut and Ray-Tracing

1
Politecnico di Milano, Department of Architecture, Built Environment and Construction Engineering, Via Ponzio 31, 20133 Milano, Italy
2
Department of Natural Resources and Environmental Engineering, University of Vigo, Campus Lagoas-Marcosende, CP 36310 Vigo, Spain
*
Author to whom correspondence should be addressed.
Received: 4 July 2018 / Revised: 9 August 2018 / Accepted: 16 August 2018 / Published: 1 September 2018
(This article belongs to the Special Issue Laser Scanning)
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Abstract

Despite the increasing demand of updated and detailed indoor models, indoor reconstruction from point clouds is still in an early stage in comparison with the reconstruction of outdoor scenes. Specific challenges are related to the complex building layouts and the high presence of elements such as pieces of furniture causing clutter and occlusions. This work proposes an automatic method for modelling Manhattan-World indoors acquired with a mobile laser scanner in the presence of highly occluded walls. The core of the methodology is the transformation of indoor reconstruction into a labelling problem of structural cells in a 2D floor plan. Assuming the prevalence of orthogonal intersections between walls, indoor completion is formulated as an energy minimization problem using graph cuts. Doors and windows are detected from occlusions by implementing a ray-tracing algorithm. The methodology is tested in a real case study. Except for one window partially covered by a curtain, all building elements were successfully reconstructed. View Full-Text
Keywords: indoor modelling; BIM; energy minimization; graph cut; regularization; terrestrial laser scanning indoor modelling; BIM; energy minimization; graph cut; regularization; terrestrial laser scanning
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Previtali, M.; Díaz-Vilariño, L.; Scaioni, M. Indoor Building Reconstruction from Occluded Point Clouds Using Graph-Cut and Ray-Tracing. Appl. Sci. 2018, 8, 1529.

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