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Automatic reconstruction of industrial installations using point clouds and images / Tahir Rabbani Shah (2006)
Titre : Automatic reconstruction of industrial installations using point clouds and images Type de document : Thèse/HDR Auteurs : Tahir Rabbani Shah, Auteur Editeur : Delft : Netherlands Geodetic Commission NGC Année de publication : 2006 Collection : Netherlands Geodetic Commission Publications on Geodesy, ISSN 0165-1706 num. 62 Importance : 160 p. Format : 17 x 24 cm ISBN/ISSN/EAN : 978-90-6132-297-9 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie terrestre
[Termes IGN] appariement de formes
[Termes IGN] bâtiment industriel
[Termes IGN] conception assistée par ordinateur
[Termes IGN] détection d'objet
[Termes IGN] détection de contours
[Termes IGN] données localisées 3D
[Termes IGN] lissage de données
[Termes IGN] métrologie industrielle
[Termes IGN] modélisation 3D
[Termes IGN] photogrammétrie terrestre
[Termes IGN] reconstruction 3D
[Termes IGN] segmentation
[Termes IGN] segmentation d'image
[Termes IGN] semis de points
[Termes IGN] transformation de HoughIndex. décimale : 33.70 Photogrammétrie terrestre Résumé : (Auteur) Up to date and accurate 3D models of industrial sites are required for different applications like planning, documentation and training. Traditional methods for acquiring as-built information like manual measurements by tape and tacheometry are not only slow and cumbersome but most of the time they also fail to provide the amount of detail required. Many industrial facilities provide a limited personnel access because of the presence of radioactive, toxic or hazardous materials together with an unsafe working environment, which necessitates the use of non-contact measurement methods.
Traditional photogrammetry depends on point or line measurements from which it is very hard to get complete CAD models without extensive manual editing and refinement. Compared to photogrammetry laser scanning provides explicit and dense 3D measurements. There has been a rapid increase in the speed and accuracy of the laser scanners in the last decade, while their costs and sizes have been continuously shrinking. All modeling tools available on the market depend on heavy operator intervention for most of the modeling tasks. Although there are some semi-automatic tools like plane or cylinder growing even there the operator has to start the growing process for each primitive. Furthermore, the fitted surfaces must be manually edited by the operator to convert them to a CAD description.
This thesis presents new methods and techniques which can be used for automatic or efficient semiautomatic 3D modeling of existing industrial installations from point clouds and images. The goal is to use explicit 3D information from the point clouds to automatically detect the objects and structure present in the scene. The detected objects are then used as targets for model based registration, which can be automated by searching for object correspondences. To avoid manual editing the presented techniques use models from a catalogue of commonly found CAD objects as templates for model fitting. In the final fitting phase images are also included to improve the quality of parameter estimation.
Segmentation is a very important step that needs to be carried out as a pre cursor to object recognition and model fitting. We present a method for the segmentation of the point clouds, which avoids over-segmentation while partitioning the input data into mutually disjoint, smoothly connected regions. It uses a criterion based on a combination of surface normal similarity and spatial connectivity, which we call smoothness constraint. As we do not use surface curvature our algorithm is less sensitive to noise. Moreover, there are only a few parameters which can be adjusted to get a desired trade-off between under- and over-segmentation.
Segmentation is followed by a stage of object recognition based on a variation of the Hough transform for automatic plane and cylinder detection in the point clouds. For plane detection the Hough transform is three dimensional. For the cylinder detection the direct application of the Hough transform requires a 5D Hough space, which is quite impractical because of its space and computational complexity. To resolve this problem we present a two-step approach requiring a 2D and 3D Hough space. In the first step we detect strong hypotheses for the cylinder orientation. The second step estimates the remaining three parameters of the cylinder i.e. radius and position.
The problem of fitting models like planes, cylinders, spheres, cones, tori and CSG models to point clouds is very important for data reduction. For the fitting of CSG models, this thesis presents three different methods for approximating the orthogonal distance, which are compared based on speed and accuracy.
We also present methods for using modeled objects in individual scans as targets for registration. As the available geometrie structure is used, there is no need to place artificial targets. We present two different methods for this purpose called Indirect and Direct method. The Indirect method is a quick way to get approximate values while the Direct method is then used to refine the approximate solution. We also present techniques for automatically finding the corresponding objects for registration of scans. The presented techniques are based on constraint propagation which use the geometric information available from the previously made correspondence decision to filter out the possibilites for future correspondences.
Although point clouds are very important for the automation because of their explicit 3D information, images provide a complementary source of information as they contain well-defined edges of the bounded objects. We present methods for the fitting of CSG models to a combination of point clouds and images. We also present techniques for the specification of geometric constraints between sub-parts of a CSG tree and their inclusion in the model estimation process. A taxonomy of commonly encountered geometric constraints and their mathematical formulation is also given.
We hope that the techniques presented in this thesis will lead to an improvement in efficiency and quality of the models obtained for industrial installations from point clouds and images.Note de contenu : 1 Introduction
1.1 Literature survey
1.2 Objectives and modeling pipeline
1.3 Outline of the thesis
2 Segmentation using smoothness constraint
2.1 Introduction
2.2 Segmentation algorithm
2.3 Results
2.4 Conclusions
3 Object recognition
3.1 Introduction
3.2 Plane detection
3.3 Cylinder detection
3.4 Ambiguity resolution by hypothesis testing
3.5 Results
3.6 Conclusions
4 Model fitting to point clouds
4.1 Introduction
4.2 Problem definition
4.3 Fitting of simple géométrie objects
4.4 CSG Fitting
4.5 Results
4.6 Conclusions
5 Model-based registration
5.1 Introduction
5.2 Notation.
5.3 Indirect Method.
5.4 Direct Method
5.5 Results and discussion
5.6 Conclusions.
6 Automatic correspondence search
6.1 Introduction
6.2 Algorithm outline
6.3 Constrained Search for Correspondences
6.4 Comparison
6.5 Results
6.6 Conclusions
7 Constrained CSG fitting
7.1 Introduction
7.2 Model Fitting
7.3 Types of constraints
7.4 Examples of constraints
7.5 Fitting Experiments
7.6 Results .
7.7 Conclusions
8 Conclusions
8.1 Achievements
8.2 Directions for future workNuméro de notice : 15184 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère En ligne : https://www.ncgeo.nl/index.php/en/publicatiesgb/publications-on-geodesy/item/251 [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=55091 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 15184-01 33.70 Livre Centre de documentation Photogrammétrie - Lasergrammétrie Disponible 15184-02 33.70 Livre Centre de documentation Photogrammétrie - Lasergrammétrie Disponible A model-driven approach to management of integrated metadata-spatial data in the context of spatial infrastructures / Chouaieb Najar (2006)
Titre : A model-driven approach to management of integrated metadata-spatial data in the context of spatial infrastructures Type de document : Thèse/HDR Auteurs : Chouaieb Najar, Auteur Editeur : Zurich : Institut für Geodäsie und Photogrammetrie IGP - ETH Année de publication : 2006 Collection : IGP Mitteilungen, ISSN 0252-9335 num. 090 Importance : 164 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-3-906467-60-3 Note générale : Bibliographie
Doctoral thesisLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] architecture orientée modèle
[Termes IGN] données localisées
[Termes IGN] implémentation (informatique)
[Termes IGN] infrastructure nationale des données localisées
[Termes IGN] intégration de données
[Termes IGN] INTERLIS
[Termes IGN] interopérabilité
[Termes IGN] interopérabilité sémantique
[Termes IGN] métadonnées
[Termes IGN] métadonnées géographiques
[Termes IGN] modèle conceptuel de données localisées
[Termes IGN] prototype
[Termes IGN] relation sémantique
[Termes IGN] segmentation sémantique
[Termes IGN] serveur web
[Termes IGN] service web géographique
[Termes IGN] UMLRésumé : (Auteur) The demand for spatial metadata to describe spatial data is growing in the networked environment. Yet, currently metadata acquisition and management often play a subordinate role in many organizations and are considered overhead. If at all, metadata are acquired much after the spatial data and are stored in separate repositories. Consequently, there are two independent data sets to manage and update: spatial data and metadata. These are often redundant and inconsistent, as it is not always clear which information is metadata and which is spatial data.
Looking at the interoperability in Spatial Data Infrastructures (SDIs) from a technical point of view, the specialized spatial search engine needs spatial data which are labeled and indexed by metadata. The more reliable and consistent such metadata are, the better they support an SDI as an enabling platform to search, exchange and process spatial data. This leaves a gap between the status-quo of metadata and the demand for metadata which needs to be accounted for with new metadata management concepts.
Consequently, the main focus of this thesis concerns the optimization of metadata management by integrating metadata and spatial data in a common file or database. This common metadata-spatial data set can be considered to be 'comprehensive spatial data'.
The concept of metadata-spatial data integration enables the spatial data to carry their own metadata description with them. The approach distinguishes between already existing spatial data models, which have to be extended and newly planned data models and sets, which can managed commonly from the beginning. The different groups of metadata which can be integrated are discussed (implicitly derivable, explicitly derivable and new metadata attributes) and the principles how these might be placed in a model (top-down and bottom-up). The three steps of integration include firstly a semantic analysis and translation, secondly a structural analysis and thirdly hierarchical integration as well as a semantic transformation.
Provided that common metadata-spatial data sets exist, the concept of views offers the possibility to extract metadata and spatial data according to various standards and other excepts from the comprehensive data set. This gains flexibility and interoperability for using common metadata-spatial data sets in an SDI environment in which different services and users need different extracts and structures of a certain data or metadata set.
In order to review the feasibility of the concept of metadata-spatial data integration three test data models and their data sets are integrated with their corresponding metadata. The Swiss federal cadastral model, a water supply model of the City of Zurich and an environmental data model vary in complexity, size modeling structure, modeling language as well as in the question whether they are standardized. The results of this case study show that the integration of metadata in existing models and data sets is feasible. For each of the chosen models certain top-down and bottom-up metadata attributes are defined. Furthermore, the implicitly and explicitly derivable attributes are ascertained. In a workshop the common models were verified with experts who know the original models well.
In order to be able to use the concept of integration on any data set in a similar way, rules for the integration are necessary. Therefore, general principles are derived for object-oriented and relational modeling languages by comparing the results from the case study and abstracting them to a general case of any spatial data set. A group of general, automatic principles to insert certain metadata at a specific place in the model has been defined. These automatic principles consist of general top-down metadata that are valid for the whole model and bottom-up metadata that mirror the changes and heterogeneity of data within the model. Notwithstanding, it is also necessary for the modeling expert who knows the spatial data well to choose which metadata can be derived implicitly and explicitly.
In order to support the common management of metadata and spatial data with tools and to support new metadata-spatial data sets in their common handling, two prototype implementations are realized. The first prototype is an existing open source modeling software called INTERLIS/UML Editor, which is extended by implementing the principles for metadata-spatial data integration. For example, a new functionality is that certain metadata are added automatically when a new model is generated. Consequently common modeling for spatial data and metadata is supported in a harmonized way. The second prototype implementation explores the possibilities of creating views and functionalities of views in the relational database management system Oracle 9i. Views according to different profiles of ISO 19115 are extracted from integrated data sets.Note de contenu : Chapter 1 Introduction
1.1 Background
1.2 Motivation.
1.3 Problem Statement
1.4 Hypothesis and Objectives
1.5 Approach
1.6 Structure of the Thesis
1.7 Summary
Chapter 2 Basic Concepts and Related Literature
2.1 Basic Definitions
2.2 Spatial Data Infrastructures and GIS
2.3 Components of Spatial Data Infrastructures
2.4 Current SDI Initiatives
2.5 Spatial Data Modeling
2.6 Semantic Processing of Spatial Data Sets
2.7 Summary
Chapter 3 State of the Art in Metadata
3.2 Current Situation in Research of Metadata Management
3.2 Relevance of Concept of Integration in Research
3.3 Summary
Chapter 4 Concept of Integration and Views
4.1 Introduction to Semantic Mapping
4.2 Concept of Metadata-Spatial Data Integration
4.3 Concept of Views
4.4 Discussion in Context of SDI
4.5 Summary
Chapter 5 Creating Principles for Metadata- Spatial Data Integration
5.1 Case Study with Existing Spatial Data Sets
5.2 Discussion of Integration
5.3 The Design of Principles
5.4 Summary
Chapter 6 Prototype Implementation
6.1 Introduction of General Tools
6.2 Implementation of the Modeling Prototype.
6.3 Implementation of the View Process
6.4 Demonstrator for Web Services using Integrated Metadata Spatial Data Sets
6.5 Summary
Chapter 7 Discussion of Results
7.1 Summary of Results
7.2 Discussion of Results and Conclusion
7.3 OutlookNuméro de notice : 15200 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Thèse étrangère DOI : 10.3929/ethz-a-005201125 En ligne : http://dx.doi.org/10.3929/ethz-a-005201125 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=55092 Réservation
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Titre : Tree detection in aerial LIDAR and image data Type de document : Article/Communication Auteurs : John Secord, Auteur ; Avideh Zahkor, Auteur Editeur : New York [Etats-Unis] : IEEE Signal Processing Society 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 : 35 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage dirigé
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection d'arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image aérienne
[Termes IGN] modélisation 3D
[Termes IGN] segmentationRésumé : (auteur) In this paper, we present an approach to detecting trees in registered aerial image and range data obtained via LiDAR. The motivation for this problem comes from automated city modeling, in which such data is used to generate textured 3-D models. Representing the trees in these models is problematic because the data is usually too sparsely sampled in tree regions to create an accurate 3-D model of the trees. Furthermore, including the tree data points interferes with the polygonization step of the building roof top models. Therefore, it is advantageous to detect and remove points that represent trees in both LiDAR and aerial imagery. In this paper, we propose a two-step method for tree detection consisting of segmentation followed by classification. The segmentation is done using a simple region-growing algorithm using weighted features from aerial image and LiDAR, such as height, texture map, height variation, and normal vector estimates. The weights for the features are determined using a learning method on random walks. The classification is done using weighted support vector machines (SVM), allowing us to control the misclassification rate. The overall problem is formulated as a binary detection problem, and receiver operating characteristic curves are shown to validate our approach. Numéro de notice : C2006-024 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Communication DOI : 10.1109/ICIP.2006.312850 En ligne : https://doi.org/10.1109/ICIP.2006.312850 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90963 Utilisation conjointe de données image et laser pour la segmentation et la modélisation 3D / Matthieu Deveau (2006)
Titre : Utilisation conjointe de données image et laser pour la segmentation et la modélisation 3D Type de document : Thèse/HDR Auteurs : Matthieu Deveau , Auteur ; Marc Pierrot-Deseilligny , Directeur de thèse ; Georges Stamon, Directeur de thèse Editeur : Paris : Université de Paris 5 René Descartes Année de publication : 2006 Importance : 135 p. Format : 21 x 30 cm Note générale : Bibliographie
Thèse présentée pour l'obtention du titre de docteur de l'université René Descartes Paris 5, spécialité informatiqueLangues : Français (fre) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] appariement de points
[Termes IGN] détection de contours
[Termes IGN] données laser
[Termes IGN] forme linéaire
[Termes IGN] image numérique
[Termes IGN] modélisation 3D
[Termes IGN] orientation interne
[Termes IGN] orientation relative
[Termes IGN] point d'intérêt
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] segmentation
[Termes IGN] semis de pointsIndex. décimale : THESE Thèses et HDR Résumé : (Auteur) Cette thèse aborde le sujet de l'automatisation de la modélisation 3D de scènes complexes par combinaison d'une image numérique et de données laser. La complémentarité géométrique de l'image et des données laser est mise à profit dans une configuration faisant intervenir une image haute résolution et un nuage de points de résolution inférieure, acquis du même point de vue. Ces travaux s'articulent autour de trois thèmes principaux : l'orientation relative des données, leur segmentation et leur modélisation. Une méthode de mise en place relative des images à partir de points et de segments est proposée. Cette méthode s'appuie d'une part sur l'appariement de points d'intérêts par corrélation entre image numérique et image d'intensité laser, dans les zones texturées, et d'autre part sur l'extraction d'éléments linéaires, sur les discontinuités radiométriques et géométriques. Une deuxième étape consiste à séparer les différents objets présents dans la scène. Cette étape a été étudiée en s'appuyant sur le principe de segmentation hiérarchique. Cette solution permet de combiner information radiométrique et géométrique dans le processus de segmentation. Elle conduit à disposer d'une architecture compacte de description d'une scène, adaptée à de nombreuses applications : pilotage de la phase d'acquisition, sous-échantillonnage adaptatif, caricature de maillage, modélisation... Si cette structure peut s'intégrer dans un processus de modélisation tout-automatique, elle peut aussi être utilisée à travers un outil de saisie semi-automatique, qui permet de garder une part d'interprétation dans le processus de modélisation, tout en disposant d'un outil de modélisation rapide. Cet outil de saisie réunit des informations 2D et des informations 3D, ce qui facilite l'analyse de la scène. Il permet de visualiser différents niveaux du graphe hiérarchique et de sélectionner pour chaque objet le meilleur niveau de description. Il débouche naturellement sur une fonctionnalité de modélisation, examinée en dernier lieu. Celle-ci s'intéresse à la modélisation automatique de surfaces construites à partir de profils quelconques. On obtient ainsi une décomposition très générale de la scène en plans, cylindres à profils quelconques et surfaces de révolution ; la triangulation venant compléter la description là où les autres modèles ne conviennent pas. Note de contenu : Introduction
1 Contexte
2 Caractéristiques des scènes considérées
3 Description recherchée
4 Précision recherchée
5 Structure du document
6 Méthodes de relevé et de reconstruction 3D
6.1 La topométrie
6.2 La photogrammétrie
6.3 La numérisation laser - lasergrammétrie
6.4 Comparaison entre photogrammétrie et lasergrammétrie
6.5 Automatisation de la reconstruction géométrique - État de l'art
7 Stratégie proposée
8 Données
8.1 Caractéristiques des images numériques
8.2 Caractéristiques des nuages de points
8.3 Jeux de données
Chapitre 1 Orientation relative image/laser
1.1 État de l'art
1.1.1 Méthodes par saisie d'éléments ponctuels
1.1.2 Méthode par comparaison des images
1.1.3 Appariement d'éléments linéaires
1.2 Solution proposée
1.3 Modélisation du système
1.3.1 Distance entre points
1.3.2 Distance entre segments
1.3.3 Énergie globale
1.4 Résolution du système
1.4.1 Solution approchée
1.4.2 Algorithme de Gauss-Newton
1.5 Extraction et appariement de points et de segments
1.5.1 Appariement de points
1.5.2 Extraction de segments
1.6 Résultats et éléments d'évaluation
1.6.1 Tests en simulation
1.6.2 Évaluation qualitative
1.6.3 Évaluation quantitative
1.7 Conclusion et perspectives
Chapitre 2 Segmentation hiérarchique conjointe image/laser
2.1 État de l'art
2.1.1 Les approches frontière
2.1.2 Les approches région
2.1.3 Classification
2.1.4 RANSAC (Random Sample Consensus)
2.1.5 Segmentation et fusion de données
2.2 Solution étudiée : la segmentation hiérarchique
2.3 Segmentation hiérarchique de données hétérogènes
2.3.1 Choix de l'énergie pour la construction de la hiérarchie
2.3.2 Bilan des différentes solutions pour le choix de l'énergie
2.4 Solution retenue : segmentation conjointe image/laser
2.4.1 Segmentation initiale conjointe image/laser
2.4.2 Segmentation conjointe des données - résultat
Chapitre 3 Applications de la segmentation pour la modélisation
3.1 Recherche automatique d'une coupe dans la hiérarchie
3.1.1 Critère de coupe
3.1.2 Sélection de modèle
3.1.3 Signature sur la sphère de Gauss
3.2 Recherche interactive d'une coupe dans la hiérarchie
3.2.1 Outils spécialisés
3.3 Reconstruction
3.3.1 Surface de révolution
3.3.2 Surface de translation
3.4 Évaluation de la segmentation
Conclusion et perspectivesNuméro de notice : 13383 Affiliation des auteurs : MATIS (1993-2011) Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de doctorat : Informatique : Paris 5 : 2006 Organisme de stage : MATIS (IGN) nature-HAL : Thèse DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=45200 Réservation
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Utilisation conjointe de données... - pdf auteur -Adobe Acrobat PDF Reconstructing spatiotemporal trajectories from sparse data / P. Partsinevelos in ISPRS Journal of photogrammetry and remote sensing, vol 60 n° 1 (December 2005 - March 2006)
[article]
Titre : Reconstructing spatiotemporal trajectories from sparse data Type de document : Article/Communication Auteurs : P. Partsinevelos, Auteur ; Peggy Agouris, Auteur ; A. Stefanidis, Auteur Année de publication : 2005 Article en page(s) : pp 3 - 16 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse de groupement
[Termes IGN] carte de Kohonen
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] données spatiotemporelles
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] objet mobile
[Termes IGN] reconstruction d'itinéraire ou de trajectoire
[Termes IGN] segmentation
[Termes IGN] seuillageRésumé : (Auteur) In motion imagery-based tracking applications, it is common to extract locations of moving objects without any knowledge about the identity of the objects they correspond to. The identification of individual spatiotemporal trajectories from such data sets is far from trivial when these trajectories intersect in space, time, or attributes. In this paper, we present a novel approach for the reconstruction of entangled spatiotemporal trajectories of moving objects captured in motion imagery data sets. We have developed AGENT (Attribute-aided Classification of Entangled Trajectories), a novel framework that comprises classification, clustering, and neural net processes to progressively reconstruct elongated trajectories using as input spatiotemporal coordinates of image patches and corresponding attribute values. AGENT proceeds by first forming brief fragments and then linking them and adding points to them. An initial classification allows us to form brief segments corresponding to distinct objects. These segments are then linked together through clustering to form longer trajectories. Back-propagation neural network classification and geometric/self-organizing map (SOM) analysis refine these trajectories by removing misclassified and redistributing unassigned points. Thus, AGENT integrates some established classification and clustering tools to devise a novel approach that can address the tracking challenges of busy environments. Furthermore, AGENT allows us use spatiotemporal (ST) thresholds to cluster trajectories according to their spatial and temporal extent. In the paper, we present in detail our framework and experimental results that support the application potential of our approach. Numéro de notice : A2006-218 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2005.10.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2005.10.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27945
in ISPRS Journal of photogrammetry and remote sensing > vol 60 n° 1 (December 2005 - March 2006) . - pp 3 - 16[article]Réservation
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