3D MODELING OF GIRIFALCO FORTRESS

Despite photogrammetry has been longly used for 3D model production, the recent development of structure from motion based reconstructions and the spread of unmanned aerial vehicles (UAV) are increasing its usage even further. Actually, the combined use of nadir and oblique UAV photogrammetry allows...

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Bibliographic Details
Main Authors: A. Masiero, F. Chiabrando, A. M. Lingua, B. G. Marino, F. Fissore, A. Guarnieri, A. Vettore
Format: Article
Language:English
Published: Copernicus Publications 2019-01-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W9/473/2019/isprs-archives-XLII-2-W9-473-2019.pdf
Description
Summary:Despite photogrammetry has been longly used for 3D model production, the recent development of structure from motion based reconstructions and the spread of unmanned aerial vehicles (UAV) are increasing its usage even further. Actually, the combined use of nadir and oblique UAV photogrammetry allows to cross the bridge between close range and aerial photogrammetry, enabling the quick acquisition of images for detailed 3D model production. This paper assesses the accuracy of UAV photogrammetry in the reconstruction of a cultural heritage building, namely the Girifalco fortress (Cortona, Italy), and it evaluates advantages and issues of this kind of 3D model generation. Furthermore, this work aims also at investigating the possible use of the generated model in order to extract geometric information about the building. First, elementary geometric shapes are extracted from the photogrammetric point cloud: the results of this step can be exploited for enabling the automatic generation of compact models of the building, which can be useful for instance in 3D city modeling applications. Then, a proper analysis of the geometric information included in the extracted shapes can be used in order to extract semantic information (e.g. to classify windows and doors) and to detect damaged areas on the building walls.
ISSN:1682-1750
2194-9034