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An automatic building reconstruction method : A structural approach using high resolution satellite images / Florent Lafarge (2006)
Titre : An automatic building reconstruction method : A structural approach using high resolution satellite images Type de document : Article/Communication Auteurs : Florent Lafarge, Auteur ; Xavier Descombes, Auteur ; Josiane Zerubia, Auteur ; Marc Pierrot-Deseilligny , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2006 Conférence : ICIP 2006, 13th IEEE International Conference on Image Processing 08/10/2006 11/10/2006 Atlanta Géorgie - Etats-Unis Proceedings IEEE Importance : pp 1205 - 1208 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] détection du bâti
[Termes IGN] modèle stéréoscopique
[Termes IGN] processus ponctuel marqué
[Termes IGN] reconstruction 3D du bâtiIndex. décimale : 33.60 Applications photogrammétriques - usage combiné de la photogrammétrie et de la lasergrammétrie Résumé : (auteur) We present an automatic 3D city model of dense urban areas from HR satellite data. The proposed method is developed using a structural approach: we construct complex buildings by merging simple parametric models with rectangular ground footprint. To do so, an automatic building extraction method based on marked point processes is used to provide rectangular building footprints. A collection of 3D parametric models is defined in order to be fixed onto these building footprints. A Bayesian framework including both prior knowledge of models and their interactions, and a likelihood fitting them to the digital elevation model, is then used. A simulated annealing scheme allows to find the configuration which maximizes the posterior density of the Bayesian expression. Numéro de notice : C2006-043 Affiliation des auteurs : MATIS+Ext (1993-2011) Autre URL associée : vers HAL Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICIP.2006.312541 Date de publication en ligne : 20/02/2007 En ligne : https://doi.org/10.1109/ICIP.2006.312541 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103317
Titre : A comparison and evaluation of multi-view stereo reconstruction algorithms Type de document : Article/Communication Auteurs : Steven M. Seitz, Auteur ; Brian Curless, Auteur ; et al., Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2006 Projets : 1-Pas de projet / Conférence : CVPR 2006, IEEE Computer Society Conference on Computer Vision and Pattern Recognition 17/06/2006 22/06/2006 New York New-York - Etats-Unis Proceedings IEEE Importance : pp 519 - 528 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] reconstruction d'imageRésumé : (auteur) This paper presents a quantitative comparison of several multi-view stereo reconstruction algorithms. Until now, the lack of suitable calibrated multi-view image datasets with known ground truth (3D shape models) has prevented such direct comparisons. In this paper, we first survey multi-view stereo algorithms and compare them qualitatively using a taxonomy that differentiates their key properties. We then describe our process for acquiring and calibrating multiview image datasets with high-accuracy ground truth and introduce our evaluation methodology. Finally, we present the results of our quantitative comparison of state-of-the-art multi-view stereo reconstruction algorithms on six benchmark datasets. The datasets, evaluation details, and instructions for submitting new models are available online at http://vision.middlebury.edu/mview. Numéro de notice : C2006-025 Affiliation des auteurs : non IGN Autre URL associée : IEEE Thématique : IMAGERIE/INFORMATIQUE Nature : Communication DOI : 10.1109/CVPR.2006.19 Date de publication en ligne : 05/07/2006 En ligne : https://vision.middlebury.edu/mview/seitz_mview_cvpr06.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96531 Recognition of Building Roof Facets by Merging Aerial Images and 3D Lidar Data in a Hierarchical Segmentation Framework / Frédéric Bretar (2006)
Titre : Recognition of Building Roof Facets by Merging Aerial Images and 3D Lidar Data in a Hierarchical Segmentation Framework Type de document : Article/Communication Auteurs : Frédéric Bretar, Auteur ; Marc Pierrot-Deseilligny , Auteur ; Michel Roux, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2006 Conférence : ICPR 2006, 18th International Conference on Pattern Recognition 20/08/2006 24/08/2006 Hong Kong Hong Kong Proceedings IEEE Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] fusion de données
[Termes IGN] image aérienne à axe vertical
[Termes IGN] segmentation hiérarchique
[Termes IGN] toitRésumé : (auteur) We investigate in this paper an original methodology for detecting roof facets through the fusion of aerial images and lidar data (3D point cloud). Based on a hierarchical segmentation of the image, we define a cost function that manages the merging order of regions. It depends on both radio-metric similarities of two neighbouring regions as well as on extracted information from lidar data. Considering that lidar data have been filtered into points belonging either to ground or non-ground classes, we define semantic and geometric rules in the binary merging process. Building roof facets are finally detected by selecting a level of generality for representing roof building components. Some remarks are given concerning the reliability of the integration of lidar and image data. Reconstructed roof facets are finally shown onto complex buildings. Numéro de notice : C2006-049 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICPR.2006.970 Date de publication en ligne : 18/09/2006 En ligne : https://doi.org/10.1109/ICPR.2006.970 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103381 Hybrid digital elevation model production guided by 3D-primitives: a global optimization algorithm using graph cuts / Nesrine Chehata (2005)
Titre : Hybrid digital elevation model production guided by 3D-primitives: a global optimization algorithm using graph cuts Type de document : Article/Communication Auteurs : Nesrine Chehata , Auteur ; Marc Pierrot-Deseilligny , Auteur ; Georges Stamon, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2005 Conférence : ICIP 2005, 11th IEEE International Conference on Image Processing 14/09/2005 15/09/2005 Gênes Italie Proceedings IEEE Note générale : bibliographie Langues : Anglais (eng) Résumé : (auteur) This research work is a part of a global project related to urban scene modeling from high resolution satellite images with focus on building production. The input data consist of a panchromatic stereo pair of satellite images, with a submetric resolution of 45-70 cm and a low base to height ratio B/H [0.05 - 0.2]. Data are provided by CNES. Since a detailed extraction and description of building rooves is complex in a satellital context, we propose to describe the scene by means of a 3D-surface which provides either raster or vector information using different level description. From extracted primitives and raw correlation information, an hybrid 3D surface will be obtained by an energy minimization process via graph cuts. The main contribution of our approach is the use of 3D-primitives such as 3D-segments and 3D-facets as well as the introduction of information from external database to guide the optimization process. The obtained product is an hybrid DEM (digital elevation model) which provides the highest level of reliable primitives for each scene region. Numéro de notice : C2005-051 Affiliation des auteurs : MATIS+Ext (1993-2011) Nature : Communication DOI : 10.1109/ICIP.2005.1530005 Date de publication en ligne : 14/11/2005 En ligne : https://doi.org/10.1109/ICIP.2005.1530005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103371 Intensity-driven-adaptive-neighbourhood technique for PolSAR parameters estimation / Gabriel Vasile (2005)
Titre : Intensity-driven-adaptive-neighbourhood technique for PolSAR parameters estimation Type de document : Article/Communication Auteurs : Gabriel Vasile, Auteur ; Emmanuel Trouvé, Auteur ; M. Ciuc, Auteur ; et al., Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2005 Conférence : IGARSS 2005, International Geoscience And Remote Sensing Symposium 29/07/2005 15/09/2005 Séoul Corée du Sud Proceedings IEEE Importance : 4 p. Format : 21 x 30 cm Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] cohérence des données
[Termes IGN] données polarimétriques
[Termes IGN] image radar moirée
[Termes IGN] polarimétrie radarRésumé : (Auteur) In this paper, a new method to estimate polarimetric coherency matrices and derive associated parameters is presented. For each pixel of the data set, an adaptive neighborhood is computed by a region growing technique driven exclusively by the intensity images. The three intensity images of the POLSAR acquisition are fused in the region growing process to ensure the stationarity hypothesis of the derived statistical population. Then, all pixels within the obtained adaptive neighborhood are, either complex averaged or estimated by the locally linear minimum mean{squared error (LLMMSE), to yield a feature preserving reliable estimate of the polarimetric coherency matrix. The target entropy{alpha{anisotropy decomposition is applied on the derived polarimetric coherency matrix. Using this decomposition, unsupervised classification for land applications by an iterative algorithm based on a complex Wishart density function is employed. The method has been tested on airborne polarimetric synthetic aperture radar images (Northumberland Strait costal area { Canadian Space Agency). Numéro de notice : 13578 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS.2005.1526020 Date de publication en ligne : 14/11/2005 En ligne : https://doi.org/10.1109/IGARSS.2005.1526020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=64264 A metric for evaluating and comparing hierarchical and multi-scale image segmentations / Roger Trias-Sanz (2005)PermalinkNon rigid registration of shapes via diffeomorphic point matching and clustering / Laurent Garcin (2005)PermalinkA region-based method for graph to image registration with an application to cadastre data / Roger Trias-Sanz (2005)PermalinkA texture orientation estimator for discriminating between forests, orchards, vineyards, and tilled fields / Roger Trias-Sanz (2005)PermalinkDetection of systematic error areas on a DTM by comparison with a high resolution LIDAR DTM / Frédéric Rousseaux (2004)PermalinkComparing RADARSAT-1 and IKONOS satellite images for urban features detection / Dan Johan Weydahl (2003)PermalinkPermalinkPermalinkIntegrating textural and geometric information for an automatic bridge detection system / Nicolas Lomenie (2003)PermalinkPermalink