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Hierarchical extraction of urban objects from mobile laser scanning data / Bisheng Yang in ISPRS Journal of photogrammetry and remote sensing, vol 99 (January 2015)
[article]
Titre : Hierarchical extraction of urban objects from mobile laser scanning data Type de document : Article/Communication Auteurs : Bisheng Yang, Auteur ; Zhen Dong, Auteur ; Gang Zhao, Auteur ; Wenxia Dai, Auteur Année de publication : 2015 Article en page(s) : pp 45 - 57 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection d'objet
[Termes IGN] extraction automatique
[Termes IGN] levé urbain
[Termes IGN] semis de points
[Termes IGN] Station laser ultra-mobile
[Termes IGN] traitement de données
[Termes IGN] voxelRésumé : (Auteur) Point clouds collected in urban scenes contain a huge number of points (e.g., billions), numerous objects with significant size variability, complex and incomplete structures, and variable point densities, raising great challenges for the automated extraction of urban objects in the field of photogrammetry, computer vision, and robotics. This paper addresses these challenges by proposing an automated method to extract urban objects robustly and efficiently. The proposed method generates multi-scale supervoxels from 3D point clouds using the point attributes (e.g., colors, intensities) and spatial distances between points, and then segments the supervoxels rather than individual points by combining graph based segmentation with multiple cues (e.g., principal direction, colors) of the supervoxels. The proposed method defines a set of rules for merging segments into meaningful units according to types of urban objects and forms the semantic knowledge of urban objects for the classification of objects. Finally, the proposed method extracts and classifies urban objects in a hierarchical order ranked by the saliency of the segments. Experiments show that the proposed method is efficient and robust for extracting buildings, streetlamps, trees, telegraph poles, traffic signs, cars, and enclosures from mobile laser scanning (MLS) point clouds, with an overall accuracy of 92.3%. Numéro de notice : A2014-635 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.10.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.10.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75061
in ISPRS Journal of photogrammetry and remote sensing > vol 99 (January 2015) . - pp 45 - 57[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2015011 RAB Revue Centre de documentation En réserve L003 Disponible Mediterranean forest species mapping using classification of Hyperion imagery / Georgia Galidaki in Geocarto international, vol 30 n° 1 - 2 (January - February 2015)
[article]
Titre : Mediterranean forest species mapping using classification of Hyperion imagery Type de document : Article/Communication Auteurs : Georgia Galidaki, Auteur ; Ioannis Z. Gitas, Auteur Année de publication : 2015 Article en page(s) : pp 48 - 61 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte de la végétation
[Termes IGN] classification barycentrique
[Termes IGN] classification orientée objet
[Termes IGN] classification pixellaire
[Termes IGN] forêt méditerranéenne
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectraleRésumé : (auteur) Regional operational forest species mapping is an active research topic that aims to provide the systematic and updatable information necessary for understanding and monitoring the rapidly changing forest environment. In this study, we investigated the potential of satellite hyperspectral imagery in regional forest species mapping by employing a pixel-based and an object-based nearest neighbour classifier in two different Mediterranean study areas. The overall thematic accuracy of the produced maps was assessed using reference data collected in the field and ranged between 0.72 and 0.83. No approach was found to be superior for the study areas. The McNemar test showed no statistically significant difference at the 95% confidence level in the classification accuracies achieved by the two approaches. Both pixel- and object-based approaches provide useful maps, suggesting that regional forest species mapping from space has much potential. Numéro de notice : A2015-245 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2014.883439 En ligne : https://doi.org/10.1080/10106049.2014.883439 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76243
in Geocarto international > vol 30 n° 1 - 2 (January - February 2015) . - pp 48 - 61[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2015011 RAB Revue Centre de documentation En réserve L003 Disponible Modalités de représentation en 3D de données issues du SIG2D, pour la conception et la simulation / Olivier Jest (2015)
Titre : Modalités de représentation en 3D de données issues du SIG2D, pour la conception et la simulation Type de document : Mémoire Auteurs : Olivier Jest, Auteur Editeur : Strasbourg : Institut National des Sciences Appliquées INSA Strasbourg Année de publication : 2015 Importance : 71 p. Format : 21 x 30 cm Note générale : Bibliographie
Mémoire de fin d'études INSA StrasbourgLangues : Français (fre) Descripteur : [Termes IGN] bibliothèque de formes
[Termes IGN] chaîne de traitement
[Termes IGN] CityGML
[Termes IGN] classe d'objets
[Termes IGN] détection d'objet
[Termes IGN] données localisées 2D
[Termes IGN] données localisées 3D
[Termes IGN] état de l'art
[Termes IGN] flore locale
[Termes IGN] FME
[Termes IGN] format OBJ
[Termes IGN] intégration de données
[Termes IGN] maquette numérique
[Termes IGN] métropole
[Termes IGN] mobilier urbain
[Termes IGN] orientation relative
[Termes IGN] SIG 3D
[Termes IGN] Strasbourg
[Termes IGN] symbole graphique 3D
[Termes IGN] VBA
[Termes IGN] visualisation 3D
[Vedettes matières IGN] GéovisualisationIndex. décimale : INSAS Mémoires d'ingénieur de l'INSA Strasbourg - Topographie, ex ENSAIS Résumé : (Auteur) L'objectif de ces travaux réalisés au sein du service Géomatique et Connaissance du Territoire de l'Eurométropole de Strasbourg est l'exploitation des données issues du SIG2D pour enrichir la maquette numérique du SIG3D. Cet objectif est réalisé en trois phases : l'étude des données du SIG2D, l'extraction et la transformation automatique des informations exploitables ; la représentation de la donnée avec la mise en place d'une bibliothèque de symboles 3D adaptés à nos besoins ; l'assemblage et la visualisation de la maquette 3D dans les logiciels. Ces recherches ont été menées lors de l'intégration de la classe des arbres, classe d'objets ayant un impact fort dans le rendu visuel de la maquette. Pour pallier au manque de connaissance des arbres du territoire, nous avons développé une méthode de détection automatique à partir du MNE. Cette méthode crée des fichiers de points d'arbres peuplant fidèlement les forêts mais détectant aussi les arbres isolés. Nous avons créé une chaîne de création automatique des symboles d'arbres pour notre maquette. Numéro de notice : 22483 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Mémoire ingénieur INSAS Organisme de stage : Eurométropole de Strasbourg Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80728 Documents numériques
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22483_Modalités de représentation en 3D de données issues du SIG2D, pour la conception et la simulation_Jest.pdfAdobe Acrobat PDF
Titre : A pipeline of 3D scene reconstruction from point clouds Type de document : Thèse/HDR Auteurs : Lingli Zhu, Auteur ; Henrik Haggren, Directeur de thèse Editeur : Helsinki : Finnish Geodetic Institute FGI Année de publication : 2015 Collection : Publications of the Finnish Geodetic Institute, ISSN 0085-6932 num. 157 Importance : 206 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-951-48-0246-1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données topographiques
[Termes IGN] détection d'objet
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] reconstruction de route
[Termes IGN] réseau routierRésumé : (auteur) 3D technologies are becoming increasingly popular as their applications in industrial, consumer, entertainment, healthcare, education, and governmental increase in number. According to market predictions, the total 3D modeling and mapping market is expected to grow from $1.1 billion in 2013 to $7.7 billion by 2018. Thus, 3D modeling techniques for different data sources are urgently needed.
This thesis addresses techniques for automated point cloud classification and the reconstruction of 3D scenes (including terrain models, 3D buildings and 3D road networks). First, georeferenced binary image processing techniques were developed for various point cloud classifications. Second, robust methods for the pipeline from the original point cloud to 3D model construction were proposed. Third, the reconstruction for the levels of detail (LoDs) of 1-3 (CityGML website) of 3D models was demonstrated. Fourth, different data sources for 3D model reconstruction were studied. The strengths and weaknesses of using the different data sources were addressed. Mobile laser scanning (MLS), unmanned aerial vehicle (UAV) images, airborne laser scanning (ALS), and the Finnish National Land Survey’s open geospatial data sources e.g. a topographic database, were employed as test data. Among these data sources, MLS data from three different systems were explored, and three different densities of ALS point clouds (0.8, 8 and 50 points/m2) were studied.
The results were compared with reference data such as an orthophoto with a ground sample distance of 20cm or measured reference points from existing software to evaluate their quality. The results showed that 74.6% of building roofs were reconstructed with the automated process. The resulting building models provided an average height deviation of 15 cm. A total of 6% of model points had a greater than one-pixel deviation from laser points. A total of 2.5% had a deviation of greater than two pixels. The pixel size was determined by the average distance of input laser points. The 3D roads were reconstructed with an average width deviation of 22 cm and an average height deviation of 14 cm. The results demonstrated that 93.4% of building roofs were correctly classified from sparse ALS and that 93.3% of power line points are detected from the six sets of dense ALS data located in forested areas.
This study demonstrates the operability of 3D model construction for LoDs of 1-3 via the proposed methodologies and datasets. The study is beneficial to future applications, such as 3D-model-based navigation applications, the updating of 2D topographic databases into 3D maps and rapid, large-area 3D scene reconstruction.Numéro de notice : 21975 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Thèse étrangère Note de thèse : Doctoral thesis : Geoinformatics : Aalto university : 2015 En ligne : https://aaltodoc.aalto.fi/bitstream/handle/123456789/16214/isbn9789514802478.pdf [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93653 A hybrid framework for single tree detection from airborne laser scanning data: A case study in temperate mature coniferous forests in Ontario, Canada / Junjie Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 98 (December 2014)
[article]
Titre : A hybrid framework for single tree detection from airborne laser scanning data: A case study in temperate mature coniferous forests in Ontario, Canada Type de document : Article/Communication Auteurs : Junjie Zhang, Auteur ; Gunho Sohn, Auteur ; Mathieu Brédif , Auteur Année de publication : 2014 Article en page(s) : pp 44 - 57 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre (flore)
[Termes IGN] détection d'objet
[Termes IGN] hauteur des arbres
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle stochastique
[Termes IGN] Pinophyta
[Termes IGN] traitement d'imageRésumé : (Auteur) This study presents a hybrid framework for single tree detection from airborne laser scanning (ALS) data by integrating low-level image processing techniques into a high-level probabilistic framework. The proposed approach modeled tree crowns in a forest plot as a configuration of circular objects. We took advantage of low-level image processing techniques to generate candidate configurations from the canopy height model (CHM): the treetop positions were sampled within the over-extracted local maxima via local maxima filtering, and the crown sizes were derived from marker-controlled watershed segmentation using corresponding treetops as markers. The configuration containing the best possible set of detected tree objects was estimated by a global optimization solver. To achieve this, we introduced a Gibbs energy, which contains a data term that judges the fitness of the objects with respect to the data, and a prior term that prevents severe overlapping between tree crowns on the configuration space. The energy was then embedded into a Markov Chain Monte Carlo (MCMC) dynamics coupled with a simulated annealing to find its global minimum. In this research, we also proposed a Monte Carlo-based sampling method for parameter estimation. We tested the method on a temperate mature coniferous forest in Ontario, Canada and also on simulated coniferous forest plots with different degrees of crown overlap. The experimental results showed the effectiveness of our proposed method, which was capable of reducing the commission errors produced by local maxima filtering, thus increasing the overall detection accuracy by approximately 10% on all of the datasets. Numéro de notice : A2014-631 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.08.007 Date de publication en ligne : 20/10/2014 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.08.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75047
in ISPRS Journal of photogrammetry and remote sensing > vol 98 (December 2014) . - pp 44 - 57[article]Réservation
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