Fast and Accurate Registration of Terrestrial Point Clouds Using a Planar Approximation of Roof Features

3D reconstructed models are becoming more diffused daily, especially in the Cultural Heritage field. These geometric models are typically obtained from elaborating a 3D point cloud. A significant limit in using these methods is the realignment of different point clouds acquired from different acquis...

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Bibliographic Details
Published inRemote sensing (Basel, Switzerland) Vol. 14; no. 13; p. 2986
Main Authors Alicandro, Maria, Di Angelo, Luca, Di Stefano, Paolo, Dominici, Donatella, Guardiani, Emanuele, Zollini, Sara
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.07.2022
Subjects
Alignment
Archaeology
Clouds
Cultural resources
Efficiency
Iterative methods
Methods
multi-UAV scanning registration
Optimization
particle swarm optimization
Photogrammetry
point cloud registration
Realignment
Registration
Remote sensing
Roofing
Roofs
shape features recognition
Three dimensional models
Unmanned aerial vehicles
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Summary:3D reconstructed models are becoming more diffused daily, especially in the Cultural Heritage field. These geometric models are typically obtained from elaborating a 3D point cloud. A significant limit in using these methods is the realignment of different point clouds acquired from different acquisitions, particularly for those whose dimensions are millions of points. Although several methodologies have tried to propose a solution for this necessity, none of these seems to solve definitively the problems related to the realignment of large point clouds. This paper presents a new and innovative procedure for the fine registration of large point clouds. The method performs an alignment by using planar approximations of roof features, taking the roof’s extension into account. It looks particularly suitable for the alignment of large point clouds acquired in urban and archaeological environments. The proposed methodology is compared in terms of accuracy and time with a standard photogrammetric reconstruction based on Ground Control Points (GCPs) and other ones, aligned by the Iterative Closest Point method (ICP) and markers. The results evidence the excellent performance of the methodology, which could represent an alternative for aligning extensive photogrammetric reconstructions without the use of GCPs.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs14132986