The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLIII-B2-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 177–184, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-177-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 177–184, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-177-2022
 
30 May 2022
30 May 2022

DETECTING OPENINGS FOR INDOOR/OUTDOOR REGISTRATION

R. Djahel1, B. Vallet2, and P. Monasse1 R. Djahel et al.
  • 1LIGM, Ecole des Ponts, Univ Gustave Eiffel, CNRS , F-77454 Marne-la-Vallée, France
  • 2LASTIG, Univ Gustave Eiffel, IGN-ENSG, F-94160 Saint-Mandé, France

Keywords: Openings, Registration, 3D segments, RANSAC, Ray Tracing

Abstract. Indoor/Outdoor modeling of buildings is an important issue in the field of building life cycle management. It is seen as a joint process where the two aspects collaborate to take advantage of their semantic and geometric complementary. This global approach will allow a more complete, correct, precise and coherent reconstruction of the buildings . The first issue of such modeling is thus to precisely register this data. The lack of overlap between indoor and outdoor data is the most encountered obstacle, more so when both data sets are acquired separately and using different types of sensors. As an opening in the façade is the unique common entity that can be seen from inside and outside, it can help the registration of indoor and outdoor point clouds. So it must be automatically, accurately and efficiently extracted. In this paper,we start by proposing a very efficient algorithm to detect openings with great precision in both indoor and outdoor scans. Afterwards, we integrate them in a registration framework. As an opening is defined by a rectangular shape composed of four segments, two horizontal and two vertical, we can write our registration problem as a minimization of a global robust distance between two segment sets and propose a robust approach to minimize this distance using the RANSAC paradigm.