Volume XLII-4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 507–514, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-507-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 507–514, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-507-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Sep 2018

19 Sep 2018

TOWARDS AUTOMATIC RECONSTRUCTION OF INDOOR SCENES FROM INCOMPLETE POINT CLOUDS: DOOR AND WINDOW DETECTION AND REGULARIZATION

M. Previtali1, L. Díaz-Vilariño2, and M. Scaioni1 M. Previtali et al.
  • 1Politecnico di Milano, Department of Architecture, Built Environment and Construction Engineering (DABC), Via Ponzio 31, 20133 Milano, Italy
  • 2University of Vigo, Department of Natural Resources and Environmental Engineering, Campus Lagoas-Marcosende, CP 36310 Vigo, Spain

Keywords: Automation, Building Information Model (BIM), Building reconstruction, Graph cut, Indoor Mobile Mapping System (IMMS), Indoor modelling

Abstract. In the last years, point clouds have become the main source of information for building modelling. Although a considerable amount of methodologies addressing the automated generation of 3D models from point clouds have been developed, indoor modelling is still a challenging task due to complex building layouts and the high presence of severe clutters and occlusions. Most of methodologies are highly dependent on data quality, often producing irregular and non-consistent models. Although manmade environments generally exhibit some regularities, they are not commonly considered. This paper presents an optimization-based approach for detecting regularities (i.e., same shape, same alignment and same spacing) in building indoor features. The methodology starts from the detection of openings based on a voxel-based visibility analysis to distinguish ‘occluded’ from ‘empty’ regions in wall surfaces. The extraction of regular patterns in windows is addressed from studying the point cloud from an outdoor perspective. The layout is regularized by minimizing deformations while respecting the detected constraints. The methodology applies for elements placed in the same plane.