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Abstract
The thesis addresses the topic of rigorous reconstruction of an archaeological context, no longer existing, by using 3D models generated by a modern photogrammetric approach. The case of study is the ancient city of Karkemish, in Turkey. This beautiful city was forgotten for more than a thousand years. Then it was finally rediscovered more than a hundred years ago; unfortunately, many beautiful historical artifacts of the city scattered to London, Paris, Ankara, and many other places in the world.
In order to demonstrate original appearance of the Long Wall of the Sculpture, digital photogrammetry method is applied, with a Structure from Motion Multi-View approach derived from Computer Vision. Thank to these recent methodologies, digital photogrammetry is more and more a universal technique for 3D model generation, applied in a wide range of interdisciplinary fields and very useful in surveying archaeological sites.
During the thesis work, the 3D model of the Karkemish site was generated by ContextCapture software; the 3D model of the orthostats of the Long Wall of the Sculpture was instead created by PhotoScan software. After generation process, the models of the orthostats were modified by Blender software in order to create a realistic appearance. A similar process was applied for the 3D model of the city.
Georeferencing was performed thanks to topographical surveys carried out on the site and the Digital Elevation Model.
As the last step, all the orthostats have been imported one by one into their original positions, recreating the situation before their transfer in the Anatolian Civilizations Museum in Ankara.
Abstract
The thesis addresses the topic of rigorous reconstruction of an archaeological context, no longer existing, by using 3D models generated by a modern photogrammetric approach. The case of study is the ancient city of Karkemish, in Turkey. This beautiful city was forgotten for more than a thousand years. Then it was finally rediscovered more than a hundred years ago; unfortunately, many beautiful historical artifacts of the city scattered to London, Paris, Ankara, and many other places in the world.
In order to demonstrate original appearance of the Long Wall of the Sculpture, digital photogrammetry method is applied, with a Structure from Motion Multi-View approach derived from Computer Vision. Thank to these recent methodologies, digital photogrammetry is more and more a universal technique for 3D model generation, applied in a wide range of interdisciplinary fields and very useful in surveying archaeological sites.
During the thesis work, the 3D model of the Karkemish site was generated by ContextCapture software; the 3D model of the orthostats of the Long Wall of the Sculpture was instead created by PhotoScan software. After generation process, the models of the orthostats were modified by Blender software in order to create a realistic appearance. A similar process was applied for the 3D model of the city.
Georeferencing was performed thanks to topographical surveys carried out on the site and the Digital Elevation Model.
As the last step, all the orthostats have been imported one by one into their original positions, recreating the situation before their transfer in the Anatolian Civilizations Museum in Ankara.
Tipologia del documento
Tesi di laurea
(Laurea magistrale)
Autore della tesi
Arslaner, Ege Candeniz
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
Historic buildings rehabilitation
Ordinamento Cds
DM270
Parole chiave
photogrammetry, structure from motion, ancient city of Karkemish, long wall of the sculpture, orthostat, 3D model
Data di discussione della Tesi
21 Dicembre 2018
URI
Altri metadati
Tipologia del documento
Tesi di laurea
(NON SPECIFICATO)
Autore della tesi
Arslaner, Ege Candeniz
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Indirizzo
Historic buildings rehabilitation
Ordinamento Cds
DM270
Parole chiave
photogrammetry, structure from motion, ancient city of Karkemish, long wall of the sculpture, orthostat, 3D model
Data di discussione della Tesi
21 Dicembre 2018
URI
Gestione del documento: