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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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 7-8 (July - August 2017) . - pp 1652 - 1674 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 contraintes Résumé : (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 [article]

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