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Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers / Martin Weinmann in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)
[article]
Titre : Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers Type de document : Article/Communication Auteurs : Martin Weinmann, Auteur ; Stefan Hinz, Auteur ; Clément Mallet , Auteur Année de publication : 2015 Article en page(s) : pp 286 - 304 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification barycentrique
[Termes IGN] compréhension de l'image
[Termes IGN] données localisées 3D
[Termes IGN] environnement de développement
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] opérateur sémantique
[Termes IGN] scène
[Termes IGN] semis de points
[Termes IGN] voisinage (relation topologique)Mots-clés libres : Point cloud Neighborhood selection Feature extraction Feature selection Classification 3D scene analysis Résumé : (auteur) 3D scene analysis in terms of automatically assigning 3D points a respective semantic label has become a topic of great importance in photogrammetry, remote sensing, computer vision and robotics. In this paper, we address the issue of how to increase the distinctiveness of geometric features and select the most relevant ones among these for 3D scene analysis. We present a new, fully automated and versatile framework composed of four components: (i) neighborhood selection, (ii) feature extraction, (iii) feature selection and (iv) classification. For each component, we consider a variety of approaches which allow applicability in terms of simplicity, efficiency and reproducibility, so that end-users can easily apply the different components and do not require expert knowledge in the respective domains. In a detailed evaluation involving 7 neighborhood definitions, 21 geometric features, 7 approaches for feature selection, 10 classifiers and 2 benchmark datasets, we demonstrate that the selection of optimal neighborhoods for individual 3D points significantly improves the results of 3D scene analysis. Additionally, we show that the selection of adequate feature subsets may even further increase the quality of the derived results while significantly reducing both processing time and memory consumption. Numéro de notice : A2015-704 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.01.016 Date de publication en ligne : 27/02/2015 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.01.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78340
in ISPRS Journal of photogrammetry and remote sensing > vol 105 (July 2015) . - pp 286 - 304[article]Distinctive 2D and 3D features for automated large-scale scene analysis in urban areas / Martin Weinmann in Computers and graphics, vol 49 (June 2015)
[article]
Titre : Distinctive 2D and 3D features for automated large-scale scene analysis in urban areas Type de document : Article/Communication Auteurs : Martin Weinmann, Auteur ; Steffen Urban, Auteur ; Stefan Hinz, Auteur ; Boris Jutzi, Auteur ; Clément Mallet , Auteur Année de publication : 2015 Article en page(s) : pp 47 - 57 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] classification automatique d'objets
[Termes IGN] compréhension de l'image
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] grande échelle
[Termes IGN] partition des données
[Termes IGN] scène urbaine
[Termes IGN] semis de pointsRésumé : (auteur) We propose a new methodology for large-scale urban 3D scene analysis in terms of automatically assigning 3D points the respective semantic labels. The methodology focuses on simplicity and reproducibility of the involved components as well as performance in terms of accuracy and computational efficiency. Exploiting a variety of low-level 2D and 3D geometric features, we further improve their distinctiveness by involving individual neighborhoods of optimal size. Due to the use of individual neighborhoods, the methodology is not tailored to a specific dataset, but in principle designed to process point clouds with a few millions of 3D points. Consequently, an extension has to be introduced for analyzing huge 3D point clouds with possibly billions of points for a whole city. For this purpose, we propose an extension which is based on an appropriate partitioning of the scene and thus allows a successive processing in a reasonable time without affecting the quality of the classification results. We demonstrate the performance of our methodology on two labeled benchmark datasets with respect to robustness, efficiency, and scalability. Numéro de notice : A2015--061 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.cag.2015.01.006 Date de publication en ligne : 07/02/2015 En ligne : https://doi.org/10.1016/j.cag.2015.01.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83512
in Computers and graphics > vol 49 (June 2015) . - pp 47 - 57[article]TerraMobilita/iQmulus urban point cloud analysis benchmark / Bruno Vallet in Computers and graphics, vol 49 (June 2015)
[article]
Titre : TerraMobilita/iQmulus urban point cloud analysis benchmark Type de document : Article/Communication Auteurs : Bruno Vallet , Auteur ; Mathieu Brédif , Auteur ; Andrès Serna, Auteur ; Beatriz Marcotegui, Auteur ; Nicolas Paparoditis , Auteur Année de publication : 2015 Projets : IQmulus / Métral, Claudine, Terra Mobilita / Métral, Claudine Article en page(s) : pp 126 - 133 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre de décision
[Termes IGN] classification
[Termes IGN] compréhension de l'image
[Termes IGN] détection
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] réalité de terrain
[Termes IGN] scène urbaine
[Termes IGN] semis de pointsRésumé : (Auteur) The objective of the TerraMobilita/iQmulus 3D urban analysis benchmark is to evaluate the current state of the art in urban scene analysis from mobile laser scanning (MLS) at large scale. A very detailed semantic tree for urban scenes is proposed. We call analysis the capacity of a method to separate the points of the scene into these categories (classification), and to separate the different objects of the same type for object classes (detection). A very large ground truth is produced manually in two steps using advanced editing tools developed especially for this benchmark. Based on this ground truth, the benchmark aims at evaluating the classification, detection and segmentation quality of the submitted results. Numéro de notice : A2015--111 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.cag.2015.03.004 Date de publication en ligne : 11/03/2015 En ligne : https://doi.org/10.1016/j.cag.2015.03.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90633
in Computers and graphics > vol 49 (June 2015) . - pp 126 - 133[article]Contextual classification of point cloud data by exploiting individual 3d neigbourhoods / Martin Weinmann in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W4 (March 2015)
[article]
Titre : Contextual classification of point cloud data by exploiting individual 3d neigbourhoods Type de document : Article/Communication Auteurs : Martin Weinmann, Auteur ; A. Schmidt, Auteur ; Clément Mallet , Auteur ; Stefan Hinz, Auteur ; Franz Rottensteiner, Auteur ; Boris Jutzi, Auteur Année de publication : 2015 Conférence : ISPRS 2015, PIA 2015 - HRIGI 2015 Joint ISPRS conference 25/03/2015 27/03/2015 Munich Allemagne ISPRS OA Annals Article en page(s) : pp 271 - 278 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse d'image orientée objet
[Termes IGN] classification contextuelle
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] scène urbaine
[Termes IGN] semis de points
[Termes IGN] voisinage (relation topologique)
[Termes IGN] zone urbaineRésumé : (auteur) The fully automated analysis of 3D point clouds is of great importance in photogrammetry, remote sensing and computer vision. For reliably extracting objects such as buildings, road inventory or vegetation, many approaches rely on the results of a point cloud classification, where each 3D point is assigned a respective semantic class label. Such an assignment, in turn, typically involves statistical methods for feature extraction and machine learning. Whereas the different components in the processing workflow have extensively, but separately been investigated in recent years, the respective connection by sharing the results of crucial tasks across all components has not yet been addressed. This connection not only encapsulates the interrelated issues of neighborhood selection and feature extraction, but also the issue of how to involve spatial context in the classification step. In this paper, we present a novel and generic approach for 3D scene analysis which relies on (i) individually optimized 3D neighborhoods for (ii) the extraction of distinctive geometric features and (iii) the contextual classification of point cloud data. For a labeled benchmark dataset, we demonstrate the beneficial impact of involving contextual information in the classification process and that using individual 3D neighborhoods of optimal size significantly increases the quality of the results for both pointwise and contextual classification. Numéro de notice : A2015--052 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-W4-271-2015 Date de publication en ligne : 11/03/2015 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-W4-271-2015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82698
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol II-3 W4 (March 2015) . - pp 271 - 278[article]Documents numériques
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Contextual classification of point cloud data ... - pdf éditeurAdobe Acrobat PDF
Titre : 3D heterogeneous interactive web mapping application Type de document : Article/Communication Auteurs : Quoc-Dinh Nguyen , Auteur ; Alexandre Devaux , Auteur ; Nicolas Paparoditis , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2015 Conférence : VR 2015, IEEE Virtual reality 23/03/2015 27/03/2015 Arles France Proceedings IEEE Importance : pp 323 - 324 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] données localisées 3D
[Termes IGN] globe virtuel
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] réalité augmentée
[Termes IGN] réalité virtuelle
[Termes IGN] scène urbaine
[Termes IGN] SIG 3D
[Termes IGN] web mapping
[Termes IGN] webGLRésumé : (auteur) The internet browsers nowadays show incredible possibilities with HTML5. It makes it possible to use all the power of your device such as the GPU and all its sensors, GPS, accelerometer, camera, etc. The ability to put hardware-accelerated 3D content in the browser provides a way for the creation of new web based applications that were previously the exclusive domain of the desktop environment. This paper introduces a novel implementation of a 3D GIS WebGL-based navigation system which allows end-users to navigate in a 3D realistic and immersive urban scene, to interact with different spatial data such as panoramic image, laser, 3D-city model, and vector data with modern functionalities such as using your smartphone as a remote, render for 3D screen and make the scene dynamic. Numéro de notice : C2015-032 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : GEOMATIQUE/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/VR.2015.7223426 Date de publication en ligne : 27/08/2015 En ligne : https://doi.org/10.1109/VR.2015.7223426 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83155 Semantic 3D scene interpretation: A framework combining optimal neighborhood size selection with relevant features / Martin Weinmann in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 (September 2014)PermalinkPermalinkImagerie terrestre urbaine : vers une méthode physique d'estimation de la réflectance / Fabien Coubard (2014)PermalinkChange Detection in 3D Point Clouds Acquired by a Mobile Mapping System / Wen Xiao in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-5 W2 (November 2013)PermalinkThe emergency social network: Geovisualising Twitter provides early warnings and on-scene reports to first responders and emergency managers / Deborah Davis in GEO: Geoconnexion international, vol 12 n° 4 (april 2013)PermalinkAppariement entre images de point de vue éloignés par utilisation de carte de profondeur / Narut Soontranon (2013)PermalinkA 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)PermalinkCreating 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)PermalinkLocal coregistration adjustment for anomalous change detection / J. Theiler in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)PermalinkTrees detection from laser point clouds acquired in dense urban areas by a mobile mapping system / Fabrice Monnier in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-3 (2012)Permalink