Automatic classification of architectural and archaeological 3D Data

Grilli, Eleonora (2020) Automatic classification of architectural and archaeological 3D Data, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Architettura, 32 Ciclo. DOI 10.6092/unibo/amsdottorato/9347.
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In the cultural heritage field, the identification within point clouds or meshes of various architectural elements rather than the distinction of materials or states of preservation can become valuable tools for studying the objects with different purposes. However, if we consider the wide variety and complexity that heritage case studies feature, the application of automatic classification procedures becomes a really challenging task. Within this research landscape, the main goal of the PhD was to develop, test and validate reliable and automatic procedures for the classification of architectural and archaeological 3D data (point clouds or polygonal mesh models coming from photogrammetric processing or laser scanning surveying). To achieve this goal, two different approaches have been developed based on texture or geometric information. They allow to: • characterize different constructing techniques; • detect existing restoration evidence; • quantify different states of conservation and materials; • identify and distinguish structural and decorative architectural elements.

Tipologia del documento
Tesi di dottorato
Grilli, Eleonora
Dottorato di ricerca
Settore disciplinare
Settore concorsuale
Parole chiave
point cloud, classification, 3D, machine learning
Data di discussione
30 Marzo 2020

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