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Simultaneous chain-forming and generalization of road networks / Susanne Wenzel in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)
[article]
Titre : Simultaneous chain-forming and generalization of road networks Type de document : Article/Communication Auteurs : Susanne Wenzel, Auteur ; Dimitri Bulatov, Auteur Année de publication : 2019 Article en page(s) : pp 19 - 28 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de Douglas-Peucker
[Termes IGN] analyse de groupement
[Termes IGN] Autriche
[Termes IGN] axe médian
[Termes IGN] classification bayesienne
[Termes IGN] extraction du réseau routier
[Termes IGN] itération
[Termes IGN] mise à jour automatique
[Termes IGN] Munich
[Termes IGN] objet géographique linéaire
[Termes IGN] orthoimage
[Termes IGN] polyligne
[Termes IGN] primitive géométrique
[Termes IGN] relation topologique
[Termes IGN] réseau routier
[Termes IGN] segmentation sémantique
[Termes IGN] squelettisation
[Termes IGN] zone urbaine
[Vedettes matières IGN] GénéralisationRésumé : (auteur) Streets are essential entities of urban terrain and their automatic extraction from airborne sensor data is cumbersome because of a complex interplay of geometric, topological, and semantic aspects. Given a binary image representing the road class, centerlines of road segments are extracted by means of skeletonization. The focus of this paper lies in a well-reasoned representation of these segments by means of geometric primitives, such as straight line segments as well as circle and ellipse arcs. Thereby, we aim at a fusion of raw segments to longer chains which better match to the intuitive perception of what a street is. We propose a two-step approach for simultaneous chain-forming and generalization. First, we obtain an over-segmentation of the raw polylines. Then, a model selection approach is applied to decide whether two neighboring segments should be fused to a new geometric entity. For this purpose, we propose an iterative greedy optimization procedure in order to find a strong minimum of a cost function based on a Bayesian information criterion. Starting at the given initial raw segments, we thus can obtain a set of chains describing long alleys and important roundabouts. Within the procedure, topological attributes, such as junctions and neighborhood structures, are consistently updated, in a way that for the greedy optimization procedure, accuracy, model complexity, and topology are considered simultaneously. The results on two challenging datasets indicate the benefits of the proposed procedure and provide ideas for future work. Numéro de notice : A2019-026 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.1.19 Date de publication en ligne : 01/01/2019 En ligne : https://doi.org/10.14358/PERS.85.1.19 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91962
in Photogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 1 (January 2019) . - pp 19 - 28[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 105-2019011 SL Revue Centre de documentation Revues en salle Disponible Automatic building rooftop extraction from aerial images via hierarchical RGB-D priors / Shibiao Xu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)
[article]
Titre : Automatic building rooftop extraction from aerial images via hierarchical RGB-D priors Type de document : Article/Communication Auteurs : Shibiao Xu, Auteur ; Xingjia Pan, Auteur ; Er Li, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 7369 - 7387 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] champ aléatoire conditionnel
[Termes IGN] détection du bâti
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image à haute résolution
[Termes IGN] image captée par drone
[Termes IGN] image RVB
[Termes IGN] itération
[Termes IGN] scène urbaine
[Termes IGN] segmentation d'image
[Termes IGN] segmentation hiérarchique
[Termes IGN] toit
[Termes IGN] zone saillante 3DRésumé : (auteur) Accurate building rooftop extraction from high-resolution aerial images is of crucial importance in a wide range of applications. Owing to the varying appearance and large-scale range of scene objects, especially for building rooftops in different scales and heights, single-scale or individual prior-based extraction technique is insufficient in pursuing efficient, generic, and accurate extraction results. The trend toward integrating multiscale or several cue techniques appears to be the best way; thus, such integration is the focus of this paper. We first propose a novel salient rooftop detector integrating four correlative RGB-D priors (depth cue, uniqueness prior, shape prior, and transition surface prior) for improved rooftop extraction to address the preceding complex issues mentioned. Then, these correlative cues are computed from image layers created by our multilevel segmentation and further fused into the state-of-the-art high-order conditional random field (CRF) framework to locate the rooftop. Finally, an iterative optimization strategy is applied for high-quality solving, which can robustly handle varying appearance of building rooftops. Performance evaluations in the SZTAKI-INRIA benchmark data sets show that our method outperforms the traditional color-based algorithm and the original high-order CRF algorithm and its variants. The proposed algorithm is also evaluated and found to produce consistently satisfactory results for various large-scale, real-world data sets. Numéro de notice : A2018-558 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2850972 Date de publication en ligne : 26/07/2018 En ligne : http://dx.doi.org/10.1109/TGRS.2018.2850972 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91664
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 7369 - 7387[article]Second iteration of photogrammetric processing to refine image orientation with improved tie-points / Truong Giang Nguyen in Sensors, vol 18 n° 7 (July 2018)
[article]
Titre : Second iteration of photogrammetric processing to refine image orientation with improved tie-points Type de document : Article/Communication Auteurs : Truong Giang Nguyen , Auteur ; Jean-Michaël Muller , Auteur ; Ewelina Rupnik , Auteur ; Christian Thom , Auteur ; Marc Pierrot-Deseilligny , Auteur Année de publication : 2018 Projets : 1-Pas de projet / Article en page(s) : n° 2150 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] compensation par faisceaux
[Termes IGN] données localisées 3D
[Termes IGN] étalonnage de chambre métrique
[Termes IGN] image captée par drone
[Termes IGN] itération
[Termes IGN] orientation d'image
[Termes IGN] points homologues
[Termes IGN] reconstruction 3D
[Termes IGN] semis de pointsRésumé : (auteur) Photogrammetric processing is available in various software solutions and can easily deliver 3D pointclouds as accurate as 1 pixel. Certain applications, e.g., very accurate shape reconstruction in industrial metrology or change detection for deformation studies in geosciences, require results of enhanced accuracy. The tie-point extraction step is the opening in the photogrammetric processing chain and therefore plays a key role in the quality of the subsequent image orientation, camera calibration and 3D reconstruction. Improving its precision will have an impact on the obtained 3D. In this research work we describe a method which aims at enhancing the accuracy of image orientation by adding a second iteration photogrammetric processing. The result from the classical processing is used as a priori information to guide the extraction of refined tie-points of better photogrammetric quality. Evaluated on indoor and UAV acquisitions, the proposed methodology shows a significant improvement on the obtained 3D point accuracy. Numéro de notice : A2018-390 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/s18072150 Date de publication en ligne : 04/07/2018 En ligne : https://doi.org/10.3390/s18072150 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90807
in Sensors > vol 18 n° 7 (July 2018) . - n° 2150[article]Documents numériques
en open access
Second iteration of photogrammetric processing ... - pdf éditeurAdobe Acrobat PDF A typification method for linear pattern in urban building generalisation / Xianyong Gong in Geocarto international, vol 33 n° 2 (February 2018)
[article]
Titre : A typification method for linear pattern in urban building generalisation Type de document : Article/Communication Auteurs : Xianyong Gong, Auteur ; Fang Wu, Auteur Année de publication : 2018 Article en page(s) : pp 189 - 207 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] généralisation cartographique automatisée
[Termes IGN] généralisation du bâti
[Termes IGN] itération
[Termes IGN] modèle linéaire
[Termes IGN] reconnaissance de formes
[Termes IGN] triangulation de Delaunay
[Termes IGN] typification
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) This paper presents a typification method for linear pattern in urban building generalization. The proposed method includes two processes. Firstly, structural knowledge in terms of linear pattern is detected using a two-step algorithm taking the advantages of Gestalt visual perception, computational geometry and graph theory. Spatial neighbourhood is captured using interpolated constrained Delaunay triangulation and the resulting proximity graph is pruned to be heterogeneous to get acceptable linear patterns with regard to Gestalt visual perception. Then, a typification strategy is proposed, in which typification is regarded as a progressive and iterative process consisting of elimination, exaggeration and displacement. The typification strategy iteratively executes eliminating the building with minimum overall effect, exaggerating remaining buildings considering key location and spatial characteristics and displacing them to preserve the linear pattern until elimination quantity is satisfied. Experiments show that this proposed strategy is effective and linear patterns are guaranteed with correctness and completeness. Numéro de notice : A2018-034 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1240718 En ligne : https://doi.org/10.1080/10106049.2016.1240718 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89207
in Geocarto international > vol 33 n° 2 (February 2018) . - pp 189 - 207[article]Deep learning based vehicular mobility models for intelligent transportation systems / Jian Zhang (2018)
Titre : Deep learning based vehicular mobility models for intelligent transportation systems Type de document : Thèse/HDR Auteurs : Jian Zhang, Auteur ; Abdelkader El Kamel, Directeur de thèse Editeur : Lille [France] : Ecole Centrale de Lille Année de publication : 2018 Importance : 175 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse présentée en vue d’obtenir le grade de Docteur, Spécialité : Automatique, génie informatique, traitement du signal et des images, Doctorat délivré par Centrale LilleLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] analyse spatiale
[Termes IGN] apprentissage profond
[Termes IGN] chaîne de Markov
[Termes IGN] classification par réseau neuronal
[Termes IGN] données de flux
[Termes IGN] itération
[Termes IGN] mobilité humaine
[Termes IGN] modèle de simulation
[Termes IGN] sécurité routière
[Termes IGN] système de transport intelligent
[Termes IGN] trafic routier
[Termes IGN] transport
[Termes IGN] UML
[Termes IGN] véhicule sans piloteIndex. décimale : THESE Thèses et HDR Résumé : (auteur) The intelligent transportation systems gain great research interests in recent years. Although the realistic traffic simulation plays an important role, it has not received enough attention. This thesis is devoted to studying the traffic simulation in microscopic level, and proposes corresponding vehicular mobility models. Using deep learning methods, these mobility models have been proven with a promising credibility to represent the vehicles in real-world. Firstly, a data-driven neural network based mobility model is proposed. This model comes from real-world trajectory data and allows mimicking local vehicle behaviors. By analyzing the performance of this basic learning based mobility model, we indicate that an improvement is possible and we propose its specification. An HMM is then introduced. The preparation of this integration is necessary, which includes an examination of traditional dynamics based mobility models and the adaptation method of “classical” models to our situation. At last, the enhanced model is presented, and a sophisticated scenario simulation is built with it to validate the theoretical results. The performance of our mobility model is promising and implementation issues have also been discussed. Note de contenu : 1- Introduction
2- Neural network based data-driven mobility model
3- Enhanced Mobility Model with HMM
4- Experiment platform and scenario simulation
Conclusions and PerspectivesNuméro de notice : 25873 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Thèse française Note de thèse : Thèse de Doctorat : Automatique, génie informatique, traitement du signal et des images : École Centrale Lille : 2018 Organisme de stage : CRIStAL (laboratoire) nature-HAL : Thèse DOI : sans En ligne : https://tel.archives-ouvertes.fr/tel-02136219/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95562 Efficient weighted total least-squares solution for partial errors-in-variables model / J. Zhao in Survey review, vol 49 n° 356 (November 2017)PermalinkAn iterative method for obtaining a mean 3D axis from a set of GNSS traces for use in positional controls / A. Mozas-Calvache in Survey review, vol 49 n° 355 (October 2017)PermalinkRecurrent neural networks to correct satellite image classification maps / Emmanuel Maggiori in IEEE Transactions on geoscience and remote sensing, vol 55 n° 9 (September 2017)PermalinkSemi-parametric segmentation of multiple series using a DP-Lasso strategy / Karine Bertin in Journal of Statistical Computation and Simulation, vol 87 n° 6 (2017)PermalinkUne deuxième itération du processus photogrammétrique pour améliorer la précision de mise en place des images / Truong Giang Nguyen (2017)PermalinkNew iterative learning strategy to improve classification systems by using outlier detection techniques / Charlotte Pelletier (2017)PermalinkSecond iteration of photogrammetric pipeline to enhance the accuracy of image pose estimation / Truong Giang Nguyen (2017)PermalinkAn iterative interpolation deconvolution algorithm for superresolution land cover mapping / Feng Ling in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)PermalinkSystematic effects in laser scanning and visualization by confidence regions / Karl Rudolf Koch in Journal of applied geodesy, vol 10 n° 4 (December 2016)PermalinkVegetation effects modeling in soil moisture retrieval using MSVI / Mina Moradizadeh in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 10 (October 2016)Permalink