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3D roof details by 3D aerial vision / Philip Meixner (2011)    

Public Titre : 3D roof details by 3D aerial vision Type de document : Article/Communication Auteurs : Philip Meixner, Auteur ; Franz W. Leberl, Auteur ; Mathieu Brédif , Auteur Editeur : New-York : IEEE Computer society Année de publication : 2011 Conférence : ICCVW 2011, IEEE International Conference on Computer Vision Workshops 06/11/2011 13/11/2011 Barcelone Espagne Proceedings IEEE Importance : pp 212 - 218 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] semis de points Résumé : (auteur) Virtual cities in a 3D GIS will not be complete without the details of roofs with chimneys, dormer windows, skylights. We contribute a method of extracting such details from digital large format aerial photography. The dense point clouds produced by a photogrammetric process produce major and minor plane surfaces of a roof and enter into a classification of its superstructures. In real city data with a total of 1312 superstructures the proposed automated process finds 1024, thus achieving success at a rate of 78%. Numéro de notice : C2011-060 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICCVW.2011.6130245 Date de publication en ligne : 16/01/2012 En ligne : https://doi.org/10.1109/ICCVW.2011.6130245 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101204

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Computer vision for the remote sensing of atmospheric visibility / Raouf Babari (2011)  

Public Titre : Computer vision for the remote sensing of atmospheric visibility Type de document : Article/Communication Auteurs : Raouf Babari, Auteur ; Nicolas Hautière, Auteur ; Eric Dumont, Auteur ; Jean-Pierre Papelard , Auteur ; Nicolas Paparoditis , Auteur Editeur : New-York : IEEE Computer society Année de publication : 2011 Conférence : ICCVW 2011, IEEE International Conference on Computer Vision Workshops 06/11/2011 13/11/2011 Barcelone Espagne Proceedings IEEE Importance : pp Note générale : bibliographie Langues : Anglais (eng) Résumé : (auteur) Atmospheric visibility distance is a property of the atmosphere, which can be remotely sensed by computer vision. In this aim, a non-linear mapping function between the atmospheric visibility distance and the contrast in images must be estimated. The function depends on the scene depth distribution as well as on the radiometry of the scene. In order to calibrate and deploy such camera-based atmospheric visibility estimations, we present two methods-which aim at computing the scene depth distribution and the radiometry of the scene beforehand. The scene depth is recovered by registering a full 3D model of the environment in the frame of the camera. The radiometry of the scene is partly recovered by looking at the temporal correlation between the variation of pixels intensity and the variation of the sky luminance estimated by a luminance meter oriented toward the North direction. Based on clear-sky models, it is demonstrated that such a process detects a set of pixels, which include pixels belonging to North-oriented Lambertian surfaces. This finding leads to a simplified way of detecting Lambertian surfaces without any additional luminance meter. Good results obtained experimentally prove that such techniques are relevant to estimate the atmospheric visibility distance. Numéro de notice : C2011-067 Affiliation des auteurs : MATIS+Ext (1993-2011) Autre URL associée : vers pdf auteur Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICCVW.2011.6130246 Date de publication en ligne : 16/01/2012 En ligne : https://doi.org/10.1109/ICCVW.2011.6130246 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101224