A Holistic Solution for Supporting the Diagnosis of Historic Constructions from 3D Point Clouds

This paper presents Segmentation for Diagnose (Seg4D), a holistic tool for processing 3D point clouds in the field of historical constructions. This tool incorporates state-of-the-art algorithms for the segmentation and analysis of construction systems and damage. Seg4D applies both supervised and u...

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Main Authors: Luis Javier Sánchez-Aparicio, Rubén Santamaría-Maestro, Pablo Sanz-Honrado, Paula Villanueva-Llauradó, Jose Ramón Aira-Zunzunegui, Diego González-Aguilera
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Remote Sensing
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Online Access:https://www.mdpi.com/2072-4292/17/12/2018
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author Luis Javier Sánchez-Aparicio
Rubén Santamaría-Maestro
Pablo Sanz-Honrado
Paula Villanueva-Llauradó
Jose Ramón Aira-Zunzunegui
Diego González-Aguilera
author_facet Luis Javier Sánchez-Aparicio
Rubén Santamaría-Maestro
Pablo Sanz-Honrado
Paula Villanueva-Llauradó
Jose Ramón Aira-Zunzunegui
Diego González-Aguilera
author_sort Luis Javier Sánchez-Aparicio
collection DOAJ
description This paper presents Segmentation for Diagnose (Seg4D), a holistic tool for processing 3D point clouds in the field of historical constructions. This tool incorporates state-of-the-art algorithms for the segmentation and analysis of construction systems and damage. Seg4D applies both supervised and unsupervised machine learning and deep learning methods, including the Point Transformer Neural Network for point cloud segmentation. Additionally, it facilitates the extraction of geometrical and statistical features, colour-scale conversion, noise reduction with anisotropic filters and the use of custom scripts for analysing deflections in slabs or out-of-plane movements in arches and vaults, among others. The Seg4D installer and source code are are publicly available in a GitHub repository.
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institution Kabale University
issn 2072-4292
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publishDate 2025-06-01
publisher MDPI AG
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series Remote Sensing
spelling doaj-art-2f5ac3f0187c47a68eb2da56828e1a4e2025-08-20T03:27:25ZengMDPI AGRemote Sensing2072-42922025-06-011712201810.3390/rs17122018A Holistic Solution for Supporting the Diagnosis of Historic Constructions from 3D Point CloudsLuis Javier Sánchez-Aparicio0Rubén Santamaría-Maestro1Pablo Sanz-Honrado2Paula Villanueva-Llauradó3Jose Ramón Aira-Zunzunegui4Diego González-Aguilera5Department of Construction and Technology in Architecture (DCTA), Escuela Técnica Superior de Arquitectura de Madrid (ETSAM), Universidad Politécnica de Madrid, Av. Juan de Herrera, 4, 28040 Madrid, SpainDepartment of Construction and Technology in Architecture (DCTA), Escuela Técnica Superior de Arquitectura de Madrid (ETSAM), Universidad Politécnica de Madrid, Av. Juan de Herrera, 4, 28040 Madrid, SpainDepartment of Construction and Technology in Architecture (DCTA), Escuela Técnica Superior de Arquitectura de Madrid (ETSAM), Universidad Politécnica de Madrid, Av. Juan de Herrera, 4, 28040 Madrid, SpainDepartment of Building Structures and Physics, Escuela Técnica Superior de Arquitectura (ETSAM), Universidad Politécnica de Madrid, Avda. Juan de Herrera, 4, 28040 Madrid, SpainDepartment of Construction and Technology in Architecture (DCTA), Escuela Técnica Superior de Arquitectura de Madrid (ETSAM), Universidad Politécnica de Madrid, Av. Juan de Herrera, 4, 28040 Madrid, SpainDepartment of Cartographic and Land Engineering, Escuela Politécnica Superior de Ávila, Universidad de Salamanca, Hornos Caleros, 50, 05003 Ávila, SpainThis paper presents Segmentation for Diagnose (Seg4D), a holistic tool for processing 3D point clouds in the field of historical constructions. This tool incorporates state-of-the-art algorithms for the segmentation and analysis of construction systems and damage. Seg4D applies both supervised and unsupervised machine learning and deep learning methods, including the Point Transformer Neural Network for point cloud segmentation. Additionally, it facilitates the extraction of geometrical and statistical features, colour-scale conversion, noise reduction with anisotropic filters and the use of custom scripts for analysing deflections in slabs or out-of-plane movements in arches and vaults, among others. The Seg4D installer and source code are are publicly available in a GitHub repository.https://www.mdpi.com/2072-4292/17/12/20183D point cloudscultural heritagehistorical constructionsdiagnosisartificial intelligenceCloudCompare
spellingShingle Luis Javier Sánchez-Aparicio
Rubén Santamaría-Maestro
Pablo Sanz-Honrado
Paula Villanueva-Llauradó
Jose Ramón Aira-Zunzunegui
Diego González-Aguilera
A Holistic Solution for Supporting the Diagnosis of Historic Constructions from 3D Point Clouds
Remote Sensing
3D point clouds
cultural heritage
historical constructions
diagnosis
artificial intelligence
CloudCompare
title A Holistic Solution for Supporting the Diagnosis of Historic Constructions from 3D Point Clouds
title_full A Holistic Solution for Supporting the Diagnosis of Historic Constructions from 3D Point Clouds
title_fullStr A Holistic Solution for Supporting the Diagnosis of Historic Constructions from 3D Point Clouds
title_full_unstemmed A Holistic Solution for Supporting the Diagnosis of Historic Constructions from 3D Point Clouds
title_short A Holistic Solution for Supporting the Diagnosis of Historic Constructions from 3D Point Clouds
title_sort holistic solution for supporting the diagnosis of historic constructions from 3d point clouds
topic 3D point clouds
cultural heritage
historical constructions
diagnosis
artificial intelligence
CloudCompare
url https://www.mdpi.com/2072-4292/17/12/2018
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