Abstract
Abstract. 3D building modeling is becoming an important support in civil engineering, architecture and cultural heritage applications. Despite static laser scanning can be considered as the state-of-the-art in such kind of applications, mobile mapping techniques can be considered as a suitable alternative to quickly gather geospatial information. Outdoor mobile mapping can be considered as a mature technique, which takes into advantage of the Global Navigation Satellite System (GNSS)-laser scanning information fusion. Instead, indoor mobile mapping is typically more challenging: the unavailability of GNSS makes the mapping system rely either just on the inertial navigation system, or on some control points. A drift in the navigation solution, and consequently in the 3D reconstruction, is typically visible after a while in the former case, whereas the use of other surveying instruments is required in the latter.This work aims at exploiting geometric characteristics of the buildings, such as symmetries and regularities, to reduce the drift effect in indoor mobile mapping, in particular when dealing with affordable systems. The proposed approach is based on the segmentation of the point clouds acquired with a time of flight camera (ToF), detecting in particular vertical planar surfaces. It is well known that aligning planar surfaces can be a viable way for reducing the drift in this kind of applications. Nevertheless, this paper aims also at investigating the use of geometric symmetries to such aim.The proposed approach is tested on a case study, a building of the University of Padova, whose reconstruction was produced by an ad hoc affordable mobile mapping system, integrating low cost inertial sensors, RGB and ToF camera.
Highlights
Outdoor and indoor building 3D modeling is becoming a fundamental task in the construction, civil engineering and architecture sectors
BIM model generation starts from the acquisition of a 3D point cloud describing the building of interest, such point cloud is segmented in different parts, which are classified and semantic/geometric information is extracted and inserted in the BIM description of the detected objects (Bassier et al, 2019, LeCun et al, 2015, Matrone et al, 2019, Barazzetti et al, 2015, Pierdicca et al, 2020)
When the localization and mapping error increases the fit between the detected symmetry and the assessed platform positions becomes insufficient to exploit the new data for improve the symmetry assessment
Summary
Outdoor and indoor building 3D modeling is becoming a fundamental task in the construction, civil engineering and architecture sectors. The generation of a building model, for instance as building information model (BIM, (Tucci et al, 2019)), requires the segmentation and recognition of different parts of the buildings: clearly, both outdoors and indoors parts should be taken into consideration in such semantic segmentation process. BIM model generation starts from the acquisition of a 3D point cloud describing the building of interest, such point cloud is segmented in different parts, which are classified and semantic/geometric information is extracted and inserted in the BIM description of the detected objects (Bassier et al, 2019, LeCun et al, 2015, Matrone et al, 2019, Barazzetti et al, 2015, Pierdicca et al, 2020).
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