Authors:
David Jurado-Rodríguez
1
;
Alfonso López
1
;
J. Jiménez
1
;
Antonio Garrido
2
;
Francisco Feito
1
and
Juan Jurado
1
Affiliations:
1
Department of Computer Science, University of Jaén, Spain
;
2
Department of Cartographic, Geodetic and Photogrammetric Engineering, University of Jaén, Spain
Keyword(s):
3D Modeling, Artificial Intelligence, Cultural Heritage Protection, Drones.
Abstract:
The detection of structural defects and anomalies in cultural heritage emerges as an essential component to ensure the integrity and safety of buildings, plan preservation strategies, and promote the sustainability and durability of buildings over time. In the search to enhance the effectiveness and efficiency of structural health monitoring of cultural heritage, this work aims to develop an automated method focused on detecting unwanted materials and geometric anomalies on the 3D surfaces of ancient buildings. In this study, the proposed solution combines an AI-based technique for fast-forward image labeling and a fully automatic detection of target classes in 3D point clouds. As an advantage of our method, the use of spatial and geometric features in the 3D models enables the recognition of target materials in the whole point cloud from seed, resulting from partial detection in a few images. The results demonstrate the feasibility and utility of detecting self-healing materials, un
wanted vegetation, lichens, and encrusted elements in a real-world scenario.
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