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3D building roof reconstruction from airborne LiDAR point clouds : a framework based on a spatial database / Rujun Cao in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)
[article]
Titre : 3D building roof reconstruction from airborne LiDAR point clouds : a framework based on a spatial database Type de document : Article/Communication Auteurs : Rujun Cao, Auteur ; Yongjun Zhang, Auteur ; Xinyi Liu, Auteur ; Zongze Zhao, Auteur Année de publication : 2017 Article en page(s) : pp 1359 - 1380 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] base de données localisées
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] niveau de détail
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] regroupement de données
[Termes IGN] semis de points
[Termes IGN] toitRésumé : (Auteur) Three-dimensional (3D) building models are essential for 3D Geographic Information Systems and play an important role in various urban management applications. Although several light detection and ranging (LiDAR) data-based reconstruction approaches have made significant advances toward the fully automatic generation of 3D building models, the process is still tedious and time-consuming, especially for massive point clouds. This paper introduces a new framework that utilizes a spatial database to achieve high performance via parallel computation for fully automatic 3D building roof reconstruction from airborne LiDAR data. The framework integrates data-driven and model-driven methods to produce building roof models of the primary structure with detailed features. The framework is composed of five major components: (1) a density-based clustering algorithm to segment individual buildings, (2) an improved boundary-tracing algorithm, (3) a hybrid method for segmenting planar patches that selects seed points in parameter space and grows the regions in spatial space, (4) a boundary regularization approach that considers outliers and (5) a method for reconstructing the topological and geometrical information of building roofs using the intersections of planar patches. The entire process is based on a spatial database, which has the following advantages: (a) managing and querying data efficiently, especially for millions of LiDAR points, (b) utilizing the spatial analysis functions provided by the system, reducing tedious and time-consuming computation, and (c) using parallel computing while reconstructing 3D building roof models, improving performance. Numéro de notice : A2017-305 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1301456 En ligne : http://dx.doi.org/10.1080/13658816.2017.1301456 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85352
in International journal of geographical information science IJGIS > vol 31 n° 7-8 (July - August 2017) . - pp 1359 - 1380[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2017041 RAB Revue Centre de documentation En réserve L003 Disponible 079-2017042 RAB Revue Centre de documentation En réserve L003 Disponible Data-driven estimation of building interior plans / Julian F. Rosser in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)
[article]
Titre : Data-driven estimation of building interior plans Type de document : Article/Communication Auteurs : Julian F. Rosser, Auteur ; Gavin Smith, Auteur ; Jeremy G. Morley, Auteur Année de publication : 2017 Article en page(s) : pp 1652 - 1674 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] bâtiment
[Termes IGN] carte d'intérieur
[Termes IGN] modèle de simulation
[Termes IGN] optimisation spatiale
[Termes IGN] plan
[Termes IGN] programmation par contraintesRésumé : (Auteur) This work investigates constructing plans of building interiors using learned building measurements. In particular, we address the problem of accurately estimating dimensions of rooms when measurements of the interior space have not been captured. Our approach focuses on learning the geometry, orientation and occurrence of rooms from a corpus of real-world building plan data to form a predictive model. The trained predictive model may then be queried to generate estimates of room dimensions and orientations. These estimates are then integrated with the overall building footprint and iteratively improved using a two-stage optimisation process to form complete interior plans.
The approach is presented as a semi-automatic method for constructing plans which can cope with a limited set of known information and constructs likely representations of building plans through modelling of soft and hard constraints. We evaluate the method in the context of estimating residential house plans and demonstrate that predictions can effectively be used for constructing plans given limited prior knowledge about the types of rooms and their topology.Numéro de notice : A2017-315 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1313980 En ligne : http://dx.doi.org/10.1080/13658816.2017.1313980 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85369
in International journal of geographical information science IJGIS > vol 31 n° 7-8 (July - August 2017) . - pp 1652 - 1674[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2017041 RAB Revue Centre de documentation En réserve L003 Disponible 079-2017042 RAB Revue Centre de documentation En réserve L003 Disponible Knowledge-based data enrichment for HBIM: Exploring high-quality models using the semantic-web / Ramona Quattrini in Journal of Cultural Heritage, vol 28 (November–December 2017)
[article]
Titre : Knowledge-based data enrichment for HBIM: Exploring high-quality models using the semantic-web Type de document : Article/Communication Auteurs : Ramona Quattrini, Auteur ; Roberto Pierdicca, Auteur ; Christian Morbidoni, Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] flux de travaux
[Termes IGN] interopérabilité
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] monument historique
[Termes IGN] ontologie
[Termes IGN] RDF
[Termes IGN] visualisation 3D
[Termes IGN] web sémantique
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) In the last decade, the paradigm Historical Building Information Modeling (HBIM) was investigated to exploit the possibilities offered by the application of BIM to historical buildings. In the Cultural Heritage domain, the BIM-oriented approach can produce 3D models that are data collector populated by both geometrical and non-geometrical information related to various themes: historical documents, monitoring data, structural information, conservation or restoration state and so on. The realization of a 3D model fully interoperable and rich in its informative content could represent a very important change towards a more efficient management of the historical real estate. The work presented in these pages outlines a novel approach to solve this interoperability issue, by developing and testing a workflow that exploits the advantages of BIM platforms and Semantic-Web technologies, enabling the user to query a repository composed of semantically structured and rich HBIM data. The presented pipeline follows four main steps: (i) the first step consists on modeling an ontology with the main information needs for the domain of interest, providing a data structure that can be leveraged to inform the data-enrichment phase and, later, to meaningfully query the data. (ii) Afterwards, the data enrichment was performed, by creating a set of shared parameters reflecting the properties in our domain ontology. (iii) To structure data in a machine-readable format, a data conversion was needed to represent the domain (ontology) and analyze data of specific buildings respectively; this step is mandatory to reuse the analysis data together with the 3D model, providing the end-user with a querying tool. (iv) As a final step in our workflow, we developed a demonstrative data exploration web application based on the faceted browsing paradigm and allowing to exploit both structured metadata and 3D visualization. This research demonstrates how is possible to represent a huge amount of specialized information models with appropriate LOD and Grade in BIM environment and then guarantee a complete interoperability with IFC/RDF format. Relying on semantically structured data (ontologies) and on the Linked Data stack appears a valid approach for addressing existing information system issues in the CH domain and constitutes a step forward in the management of repositories and web libraries devoted to historical buildings. Numéro de notice : A2017-231 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.culher.2017.05.004 En ligne : https://doi.org/10.1016/j.culher.2017.05.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85144
in Journal of Cultural Heritage > vol 28 (November–December 2017)[article]Urban 3D segmentation and modelling from street view images and LiDAR point clouds / Pouria Babahajiani in Machine Vision and Applications, sans n° ([01/06/2017])
[article]
Titre : Urban 3D segmentation and modelling from street view images and LiDAR point clouds Type de document : Article/Communication Auteurs : Pouria Babahajiani, Auteur ; Lixin Fan, Auteur ; Joni-Kristian Kämäräinen, Auteur ; Moncef Gabbouj, Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] base de données urbaines
[Termes IGN] cartographie urbaine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] façade
[Termes IGN] image terrestre
[Termes IGN] milieu urbain
[Termes IGN] segmentation sémantique
[Termes IGN] semis de pointsRésumé : (auteur) 3D urban maps with semantic labels and metric information are not only essential for the next generation robots such autonomous vehicles and city drones, but also help to visualize and augment local environment in mobile user applications. The machine vision challenge is to generate accurate urban maps from existing data with minimal manual annotation. In this work, we propose a novel methodology that takes GPS registered LiDAR (Light Detection And Ranging) point clouds and street view images as inputs and creates semantic labels for the 3D points clouds using a hybrid of rule-based parsing and learning-based labelling that combine point cloud and photometric features. The rule-based parsing boosts segmentation of simple and large structures such as street surfaces and building facades that span almost 75% of the point cloud data. For more complex structures, such as cars, trees and pedestrians, we adopt boosted decision trees that exploit both structure (LiDAR) and photometric (street view) features. We provide qualitative examples of our methodology in 3D visualization where we construct parametric graphical models from labelled data and in 2D image segmentation where 3D labels are back projected to the street view images. In quantitative evaluation we report classification accuracy and computing times and compare results to competing methods with three popular databases: NAVTEQ True, Paris-Rue-Madame and TLS (terrestrial laser scanned) Velodyne. Numéro de notice : A2017-255 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1007/s00138-017-0845-3 En ligne : https://doi.org/10.1007/s00138-017-0845-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85269
in Machine Vision and Applications > sans n° [01/06/2017][article]Semiautomatic detection and classification of materials in historic buildings with low-cost photogrammetric equipment / Javier Sanchez in Journal of Cultural Heritage, vol 25 (May - June 2017)
[article]
Titre : Semiautomatic detection and classification of materials in historic buildings with low-cost photogrammetric equipment Type de document : Article/Communication Auteurs : Javier Sanchez, Auteur ; Elia Quirós, Auteur Année de publication : 2017 Article en page(s) : pp 21 - 30 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] bande visible
[Termes IGN] détection d'objet
[Termes IGN] dommage matériel
[Termes IGN] façade
[Termes IGN] image multibande
[Termes IGN] image proche infrarouge
[Termes IGN] monument historique
[Termes IGN] restauration de bâtimentRésumé : (auteur) The detection of materials and damage in building facades by means of near-infrared digital images is not a widely explored field in architectural research, especially in rehabilitation and historic building surveys. The aim of this work is to study whether spectral classification image methods, which are frequently used in remote sensing land applications (non-contact geophysical techniques), could be applied in the architectural field to detect various construction materials in historic building facades by means of low-cost photogrammetric equipment. Several classification methodologies were applied to different image band combinations, which led to the conclusion that the highest accuracy is obtained with a multiband image composed of visible and near-infrared bands. We also performed a derived measurement of the real surface of the facing material, demonstrating that low-cost instrumentation could be useful in architectural interventions in cultural heritage to identify construction materials in a non-destructive way. Numéro de notice : A2017-230 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.culher.2016.11.017 En ligne : https://doi.org/10.1016/j.culher.2016.11.017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85142
in Journal of Cultural Heritage > vol 25 (May - June 2017) . - pp 21 - 30[article]Mapping fine-scale population distributions at the building level by integrating multisource geospatial big data / Yao Yao in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)PermalinkGeodetic monitoring of subrosion-induced subsidence processes in urban areas / Tobias Kersten in Journal of applied geodesy, vol 11 n° 1 (March 2017)PermalinkUsing vector building maps to aid in generating seams for low-attitude aerial orthoimage mosaicking: Advantages in avoiding the crossing of buildings / Dongliang Wang in ISPRS Journal of photogrammetry and remote sensing, vol 125 (March 2017)PermalinkA hierarchical methodology for urban facade parsing from TLS point clouds / Zhuqiang Li in ISPRS Journal of photogrammetry and remote sensing, vol 123 (January 2017)PermalinkHierarchically exploring the width of spectral bands for urban material classification / Arnaud Le Bris (2017)PermalinkPermalinkDu nuage de points à la maquette numérique de bâtiment : reconstruction 3D semi-automatique de bâtiments existants / Hélène Macher (2017)PermalinkClose-range photogrammetric tools for epigraphic surveys / Mariam Samaan in Journal on Computing and Cultural Heritage, JOCCH, vol 9 n° 3 (November 2016)PermalinkCulture for all / R. Scibetta in GEO: Geoconnexion international, vol 15 n° 10 (November - December 2016)PermalinkSlicing method for curved façade and window extraction from point clouds / S.M. Iman Zolanvari in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)Permalink