Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Automatic Recognition and Digital Documentation of Cultural Heritage Hemispherical Domes using Images
Advancements in optical metrology has enabled documentation of dense 3D point clouds of cultural heritage sites. For large scale and continuous digital documentation, processing of dense 3D point clouds becomes computationally cumbersome, and often requires additional hardware for data management, increasing the time cost, and complexity of projects. To this end, this manuscript presents an original approach to generate fast and reliable semantic digital models of heritage hemispherical domes using only two images. New closed formulations were derived to establish the relationships between spheres and their projected ellipses onto images, which fostered the development of a new automatic framework for as-built generation of spheres. The effectiveness of the proposed method was evaluated under both laboratory and real-world datasets. The results revealed that the proposed method achieved as-built modeling accuracy of around 6mm, while improving the computation time by a factor of 7, when compared to established point cloud processing methods.
Automatic Recognition and Digital Documentation of Cultural Heritage Hemispherical Domes using Images
Advancements in optical metrology has enabled documentation of dense 3D point clouds of cultural heritage sites. For large scale and continuous digital documentation, processing of dense 3D point clouds becomes computationally cumbersome, and often requires additional hardware for data management, increasing the time cost, and complexity of projects. To this end, this manuscript presents an original approach to generate fast and reliable semantic digital models of heritage hemispherical domes using only two images. New closed formulations were derived to establish the relationships between spheres and their projected ellipses onto images, which fostered the development of a new automatic framework for as-built generation of spheres. The effectiveness of the proposed method was evaluated under both laboratory and real-world datasets. The results revealed that the proposed method achieved as-built modeling accuracy of around 6mm, while improving the computation time by a factor of 7, when compared to established point cloud processing methods.
Automatic Recognition and Digital Documentation of Cultural Heritage Hemispherical Domes using Images
Maalek, Reza (Autor:in) / Maalek, Shahrokh (Autor:in)
14.09.2023
Buch
Elektronische Ressource
Englisch
Computing methodologies , Computer graphics , Image manipulation , Image processing , Applied , computing , Physical sciences and engineering , Engineering , Computer-aided design , Sphere detection , digital documentation of spheres , metric scale definition , spherical targets , sphere projection in images , hemispherical domes , ddc:690 , Buildings , info:eu-repo/classification/ddc/690
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