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A hybrid multiview stereo algorithm for modeling urban scenes / Florent Lafarge in IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI, vol 35 n° 1 (January 2013)
[article]
Titre : A hybrid multiview stereo algorithm for modeling urban scenes Type de document : Article/Communication Auteurs : Florent Lafarge, Auteur ; Renaud Keriven, Auteur ; Mathieu Brédif , Auteur ; Hoang-Hiep Vu, Auteur Année de publication : 2013 Article en page(s) : pp 5 - 17 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] champ aléatoire de Markov
[Termes IGN] maillage
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modèle de Markov
[Termes IGN] primitive géométrique
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] scène urbaineMots-clés libres : hybrid representation Résumé : (auteur) We present an original multiview stereo reconstruction algorithm which allows the 3D-modeling of urban scenes as a combination of meshes and geometric primitives. The method provides a compact model while preserving details: Irregular elements such as statues and ornaments are described by meshes, whereas regular structures such as columns and walls are described by primitives (planes, spheres, cylinders, cones, and tori). We adopt a two-step strategy consisting first in segmenting the initial mesh-based surface using a multilabel Markov Random Field-based model and second in sampling primitive and mesh components simultaneously on the obtained partition by a Jump-Diffusion process. The quality of a reconstruction is measured by a multi-object energy model which takes into account both photo-consistency and semantic considerations (i.e., geometry and shape layout). The segmentation and sampling steps are embedded into an iterative refinement procedure which provides an increasingly accurate hybrid representation. Experimental results on complex urban structures and large scenes are presented and compared to state-of-the-art multiview stereo meshing algorithms. Numéro de notice : A2013-816 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TPAMI.2012.84 Date de publication en ligne : 10/04/2012 En ligne : https://doi.org/10.1109/TPAMI.2012.84 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80877
in IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI > vol 35 n° 1 (January 2013) . - pp 5 - 17[article]Documents numériques
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A hybrid multi-view stereo algorithm - version auteur HALAdobe Acrobat PDF Creating large-scale city models from 3D-Point clouds : a robust approach with hybrid representation / Florent Lafarge in International journal of computer vision, vol 99 n° 1 (August 2012)
[article]
Titre : Creating large-scale city models from 3D-Point clouds : a robust approach with hybrid representation Type de document : Article/Communication Auteurs : Florent Lafarge, Auteur ; Clément Mallet , Auteur Année de publication : 2012 Article en page(s) : pp 69 - 85 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] champ aléatoire de Markov
[Termes IGN] détection d'objet
[Termes IGN] données localisées 3D
[Termes IGN] méthode de réduction d'énergie
[Termes IGN] méthode robuste
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modèle numérique d'objet
[Termes IGN] scène urbaine
[Termes IGN] semis de pointsRésumé : (Auteur) We present a novel and robust method for modeling cities from 3D-point data. Our algorithm provides a more complete description than existing approaches by reconstructing simultaneously buildings, trees and topologically complex grounds. A major contribution of our work is the original way of modeling buildings which guarantees a high generalization level while having semantized and compact representations. Geometric 3D-primitives such as planes, cylinders, spheres or cones describe regular roof sections, and are combined with mesh-patches that represent irregular roof components. The various urban components interact through a non-convex energy minimization problem in which they are propagated under arrangement constraints over a planimetric map. Our approach is experimentally validated on complex buildings and large urban scenes of millions of points, and is compared to state-of-the-art methods. Numéro de notice : A2012-731 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11263-012-0517-8 Date de publication en ligne : 29/02/2012 En ligne : https://doi.org/10.1007/s11263-012-0517-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91109
in International journal of computer vision > vol 99 n° 1 (August 2012) . - pp 69 - 85[article]An automated approach for updating land cover maps based on integrated change detection and classification methods / X. Chen in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)
[article]
Titre : An automated approach for updating land cover maps based on integrated change detection and classification methods Type de document : Article/Communication Auteurs : X. Chen, Auteur ; J. Chen, Auteur ; Y. Shi, Auteur ; Yasushi Yamaguchi, Auteur Année de publication : 2012 Article en page(s) : pp 86 - 95 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'occupation du sol
[Termes IGN] champ aléatoire de Markov
[Termes IGN] Chensi (Chine)
[Termes IGN] détection de changement
[Termes IGN] image Landsat-ETM+
[Termes IGN] mise à jour de base de donnéesRésumé : (Auteur) Updating land cover maps from remotely sensed data in a timely manner is important for many areas of scientific research. Unfortunately, traditional classification procedures are very labor intensive and subjective because of the required human interaction. Based on the strategy of updating land cover data only for the changed area, we proposed an integrated, automated approach to update land cover maps without human interaction. The proposed method consists primarily of the following three parts: a change detection technique, a Markov Random Fields (MRFs) model, and an iterated training sample selecting procedure. In the proposed approach, remotely sensed data acquired in different seasons or from different remote sensors can be used. Meanwhile, the approach is completely unsupervised. Therefore, the methodology has a wide scope of application. A case study of Landsat data was conducted to test the performance of this method. The experimental results show that several sub-modules in this method work effectively and that reasonable classification accuracy can be achieved. Numéro de notice : A2012-350 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.05.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.05.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31796
in ISPRS Journal of photogrammetry and remote sensing > vol 71 (July 2012) . - pp 86 - 95[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012051 SL Revue Centre de documentation Revues en salle Disponible Evaluation of bayesian despeckling and texture extraction methods based on Gauss–Markov and auto-binomial gibbs random fields: Application to TerraSAR-X data / D. Espinoza Molina in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 2 (May 2012)
[article]
Titre : Evaluation of bayesian despeckling and texture extraction methods based on Gauss–Markov and auto-binomial gibbs random fields: Application to TerraSAR-X data Type de document : Article/Communication Auteurs : D. Espinoza Molina, Auteur ; D. Gleich, Auteur ; M. Dactu, Auteur Année de publication : 2012 Article en page(s) : pp 2001 - 2025 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse comparative
[Termes IGN] analyse texturale
[Termes IGN] champ aléatoire de Markov
[Termes IGN] échantillonnage de Gibbs
[Termes IGN] évaluation
[Termes IGN] filtre de déchatoiement
[Termes IGN] image radar moirée
[Termes IGN] image TerraSAR-X
[Termes IGN] inférence statistique
[Termes IGN] texture d'imageRésumé : (Auteur) Speckle hinders information in synthetic aperture radar (SAR) images and makes automatic information extraction very difficult. The Bayesian approach allows us to perform the despeckling of an image while preserving its texture and structures. This model-based approach relies on a prior model of the scene. This paper presents an evaluation of two despeckling and texture extraction model-based methods using the two levels of Bayesian inference. The first method uses a Gauss-Markov random field as prior, and the second is based on an auto-binomial model (ABM). Both methods calculate a maximum a posteriori and determine the best model using an evidence maximization algorithm. Our evaluation approach assesses the quality of the image by means of the despeckling and texture extraction qualities. The proposed objective measures are used to quantify the despeckling performances of these methods. The accuracy of modeling and characterization of texture were determined using both supervised and unsupervised classifications, and confusion matrices. Real and simulated SAR data were used during the validation procedure. The results show that both methods enhance the image during the despeckling process. The ABM is superior regarding texture extraction and despeckling for real SAR images. Numéro de notice : A2012-190 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2169679 En ligne : https://doi.org/10.1109/TGRS.2011.2169679 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31637
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 5 Tome 2 (May 2012) . - pp 2001 - 2025[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012051B RAB Revue Centre de documentation En réserve L003 Disponible Extraction of building roof contours from LiDAR data using a Markov-random-field-based approach / E. Dos Santos Galvanin in IEEE Transactions on geoscience and remote sensing, vol 50 n° 3 (March 2012)
[article]
Titre : Extraction of building roof contours from LiDAR data using a Markov-random-field-based approach Type de document : Article/Communication Auteurs : E. Dos Santos Galvanin, Auteur ; A. Dal Poz, Auteur Année de publication : 2012 Article en page(s) : pp 981 - 987 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme du recuit simulé
[Termes IGN] bati
[Termes IGN] champ aléatoire de Markov
[Termes IGN] détection de contours
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction automatique
[Termes IGN] toitRésumé : (Auteur) This paper proposes a method for the automatic extraction of building roof contours from a digital surface model (DSM) by regularizing light detection and ranging (LiDAR) data. The method uses two steps. First, to detect aboveground objects (buildings, trees, etc.), the DSM is segmented through a recursive splitting technique followed by a region-merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. The optimal configuration of building roof contours is found by minimizing the energy function using a simulated annealing algorithm. Experiments carried out with the LiDAR-based DSM show that the proposed method works properly, as it provides roof contour information with approximately 90% shape accuracy and no verified false positives. Numéro de notice : A2012-101 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2163823 Date de publication en ligne : 15/09/2011 En ligne : https://doi.org/10.1109/TGRS.2011.2163823 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31549
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 3 (March 2012) . - pp 981 - 987[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012031 RAB Revue Centre de documentation En réserve L003 Disponible PermalinkConditional random fields for urban scene : Classification with full waveform LiDAR Data / Joachim Niemeyer (2011)PermalinkUse Markov random fields for automatic cloud-shadow detection on high resolution / Sylvie Le Hégarat-Mascle in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 4 (July - August 2009)PermalinkTexture feature fusion with neighborhood oscillating tabu search for high resolution image classification / L. Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 3 (March 2008)PermalinkModélisation et statistique spatiales / Carlo Gaetan (2008)PermalinkA stochastic framework for the identification of building rooftops using a single remote sensing image / A. Katartzis in IEEE Transactions on geoscience and remote sensing, vol 46 n° 1 (January 2008)PermalinkDétection de feux de forêt par analyse statistique d'évènements rares à partir d'images infrarouges thermiques / Florent Lafarge in Traitement du signal, vol 24 n° 1 ([01/02/2007])PermalinkChamps de Markov sur graphes pour le traitement des images radar / Florence Tupin (2007)PermalinkPermalinkSuper-resolution land cover mapping using a Markov random field based approach / T. Kasetkasem in Remote sensing of environment, vol 96 n° 3 (30/06/2005)PermalinkA Bayesian approach to classification of multiresolution remote sensing data / G. Storvik in IEEE Transactions on geoscience and remote sensing, vol 43 n° 3 (March 2005)PermalinkUn premier pas vers l'extraction de MNS urbains en interférometrie RSO à haute résolution par fusion de détecteurs / C. Tison in Revue Française de Photogrammétrie et de Télédétection, n° 176 (Décembre 2004)PermalinkReconstruction of backscatter and extinction coefficients in Lidar: a stochastic filtering approach / José M. Bioucas-Dias in IEEE Transactions on geoscience and remote sensing, vol 42 n° 2 (February 2004)PermalinkComparing cooccurrence probabilities and Markov random fields for texture analysis of SAR sea ice imagery / D.A. Clausi in IEEE Transactions on geoscience and remote sensing, vol 42 n° 1 (January 2004)PermalinkEvaluation de la qualité du modèle de covariance d'un champ aléatoire / Hammadi Chaira (2004)PermalinkFast SAR image restoration, segmentation, and detection of high-reflectance regions / E. Bratsolis in IEEE Transactions on geoscience and remote sensing, vol 41 n° 12 (December 2003)PermalinkA Markov random field approach to spatio-temporal contextual image classification / F. Melgani in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)PermalinkA Markov random field-based approach to decision-level fusion for remote sensing image classification / Ryuei Nishii in IEEE Transactions on geoscience and remote sensing, vol 41 n° 10 (October 2003)PermalinkThe effect of modified Markov random fields on the local minima occurrence in microwave imaging / G. Ferraiuolo in IEEE Transactions on geoscience and remote sensing, vol 41 n° 5 (May 2003)PermalinkUnsupervised classification of radar images using hidden Markov chains and hidden Markov random fields / R. Fjortoft in IEEE Transactions on geoscience and remote sensing, vol 41 n° 3 (March 2003)Permalink