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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 Revues en salle 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)
[article]
Titre : Mapping fine-scale population distributions at the building level by integrating multisource geospatial big data Type de document : Article/Communication Auteurs : Yao Yao, Auteur ; Xiaoping Liu, Auteur ; Xia Li, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 1220 - 1244 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] bâtiment
[Termes IGN] Canton (Kouangtoung)
[Termes IGN] cartographie statistique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] densité de population
[Termes IGN] données localisées des bénévoles
[Termes IGN] données massives
[Termes IGN] données statistiques
[Termes IGN] habitat collectif
[Termes IGN] habitat urbain
[Termes IGN] intégration de données
[Termes IGN] point d'intérêt
[Termes IGN] population urbaine
[Termes IGN] répartition géographiqueRésumé : (auteur) Fine-scale population distribution data at the building level play an essential role in numerous fields, for example urban planning and disaster prevention. The rapid technological development of remote sensing (RS) and geographical information system (GIS) in recent decades has benefited numerous population distribution mapping studies. However, most of these studies focused on global population and environmental changes; few considered fine-scale population mapping at the local scale, largely because of a lack of reliable data and models. As geospatial big data booms, Internet-collected volunteered geographic information (VGI) can now be used to solve this problem. This article establishes a novel framework to map urban population distributions at the building scale by integrating multisource geospatial big data, which is essential for the fine-scale mapping of population distributions. First, Baidu points-of-interest (POIs) and real-time Tencent user densities (RTUD) are analyzed by using a random forest algorithm to down-scale the street-level population distribution to the grid level. Then, we design an effective iterative building-population gravity model to map population distributions at the building level. Meanwhile, we introduce a densely inhabited index (DII), generated by the proposed gravity model, which can be used to estimate the degree of residential crowding. According to a comparison with official community-level census data and the results of previous population mapping methods, our method exhibits the best accuracy (Pearson R = .8615, RMSE = 663.3250, p Numéro de notice : A2017-245 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1290252 En ligne : http://dx.doi.org/10.1080/13658816.2017.1290252 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85188
in International journal of geographical information science IJGIS > vol 31 n° 5-6 (May-June 2017) . - pp 1220 - 1244[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2017031 RAB Revue Centre de documentation En réserve L003 Disponible Geodetic 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)PermalinkBuilding Information Modeling (BIM) in higher education based on pedagogical concepts and standardised methods / Eilif Hjelseth in International journal of 3-D information modeling, vol 6 n° 1 (January - March 2017)PermalinkClient and user involvement through BIM-related technologies / Silvia Mastrolembo Ventura in International journal of 3-D information modeling, vol 6 n° 1 (January - 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)PermalinkPotentialités de l’outil LiDAR pour cartographier les vestiges de la Grande Guerre en milieu intra-forestier (bois des Caures, forêt domaniale de Verdun, Meuse) / Rémi de Matos Machado in EchoGeo, n° 38 (octobre - décembre 2016)PermalinkClose-range photogrammetric tools for epigraphic surveys / Mariam Samaan in Journal on Computing and Cultural Heritage (JOCCH), vol 9 n° 3 (November 2016)Permalink