000127025 001__ 127025
000127025 005__ 20240731103410.0
000127025 0247_ $$2doi$$a10.5194/isprs-archives-XLVIII-M-2-2023-333-2023
000127025 0248_ $$2sideral$$a134289
000127025 037__ $$aART-2023-134289
000127025 041__ $$aeng
000127025 100__ $$aBuldo, M.
000127025 245__ $$aA SCAN-TO-BIM Workflow proposal for cultural heritage. Automatic point cloud segmentation and parametric-adaptive modelling of vaulted systems
000127025 260__ $$c2023
000127025 5060_ $$aAccess copy available to the general public$$fUnrestricted
000127025 5203_ $$aAbstract. Cultural Heritage has been significantly impacted by advancements in the Information and Communications Technology domains, which have inspired a strong multidisciplinary interest and enabled the development of innovative strategies for the preservation, management, and enhancement of the heritage itself. Notably, the digitisation process, which entails the acquisition of 3D data obtained through cutting-edge LiDAR and photogrammetric scanning techniques, is set up as an advantageous tool for producing an accurate representation of the historical buildings. In addition, point clouds and reliable HBIM models have caught the minds of the architectural community, and are now receiving huge backing from Artificial Intelligence. Such support is provided by procedures that link semantic features to structural and decorative elements. In this scenario, the following research is presented: the aim is to test an automated iterative process within a scan-to-BIM methodology, starting from automatic point cloud segmentation operations with open-source, model-fitting algorithms. This method will prove to be a solid support for the final phase of the 3D parametric/adaptive reconstruction that’s also compatible with BIM Authoring. The study focuses on various masonry vaulted systems. These types of structures are first examined using ideal models, which were perfectly discretised and set up by the user, and then employed as a starting point for validating the parameters of the RANSAC algorithm on point clouds acquired by laser scanners. These latter ones nevertheless have irregular geometries, making comprehension, analysis, and management far more challenging.
000127025 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000127025 592__ $$a0.282$$b2023
000127025 593__ $$aInformation Systems$$c2023
000127025 593__ $$aGeography, Planning and Development$$c2023
000127025 594__ $$a1.7$$b2023
000127025 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000127025 700__ $$0(orcid)0000-0002-0397-9766$$aAgustín-Hernández, L.$$uUniversidad de Zaragoza
000127025 700__ $$aVerdoscia, C.
000127025 700__ $$aTavolare, R.
000127025 7102_ $$15015$$2300$$aUniversidad de Zaragoza$$bDpto. Arquitectura$$cÁrea Expresión Gráfica Arquite
000127025 773__ $$g58-M-2-2023 (2023), 333-340$$pInt. arch. photogramm. remote sens. spat. inf. sci.$$tInternational archives of the photogrammetry, remote sensing and spatial information sciences$$x1682-1750
000127025 8564_ $$s2901524$$uhttps://zaguan.unizar.es/record/127025/files/texto_completo.pdf$$yVersión publicada
000127025 8564_ $$s3333600$$uhttps://zaguan.unizar.es/record/127025/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000127025 909CO $$ooai:zaguan.unizar.es:127025$$particulos$$pdriver
000127025 951__ $$a2024-07-31-10:03:20
000127025 980__ $$aARTICLE