Détail de l'indexation
33.00 Photogrammétrie - généralitésOuvrages de la bibliothèque en indexation 33.30 (96)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Titre : Pointless global bundle adjustment with relative motions Hessians Type de document : Article/Communication Auteurs : Ewelina Rupnik , Auteur ; Marc Pierrot-Deseilligny
Editeur : Computer vision foundation CVF Année de publication : 2023 Conférence : CVPR 2023, IEEE Conference on Computer Vision and Pattern Recognition 18/06/2023 22/06/2023 Vancouver Colombie britannique - Canada OA Proceedings Importance : pp 6517 - 6525 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] compensation par faisceaux
[Termes IGN] estimation de pose
[Termes IGN] matriceIndex. décimale : 33.30 Photogrammétrie numérique Résumé : (auteur) Bundle adjustment (BA) is the standard way to optimise camera poses and to produce sparse representations of a scene. However, as the number of camera poses and features grows, refinement through bundle adjustment becomes inefficient. Inspired by global motion averaging methods, we propose a new bundle adjustment objective which does not rely on image features' reprojection errors yet maintains precision on par with classical BA. Our method averages over relative motions while implicitly incorporating the contribution of the structure in the adjustment. To that end, we weight the objective function by local hessian matrices-a by-product of local bundle adjustments performed on relative motions (eg, pairs or triplets) during the pose initialisation step. Such hessians are extremely rich as they encapsulate both the features' random errors and the geometric configuration between the cameras. These pieces of information propagated to the global frame help to guide the final optimisation in a more rigorous way. We argue that this approach is an upgraded version of the motion averaging approach and demonstrate its effectiveness on both photogrammetric datasets and computer vision benchmarks. Numéro de notice : C2023-008 Affiliation des auteurs : UGE-LASTIG (2020- ) Autre URL associée : vers OA paper Thématique : IMAGERIE/INFORMATIQUE/MATHEMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans En ligne : https://openaccess.thecvf.com/content/CVPR2023W/PCV/papers/Rupnik_Pointless_Glob [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103282
Titre : Close-range photogrammetry and 3D imaging Type de document : Guide/Manuel Auteurs : Thomas Luhmann, Auteur ; Stuart Robson, Auteur ; Stephen Kyle, Auteur ; Jan Böhm Editeur : Berlin, New York : Walter de Gruyter Année de publication : 2019 Importance : 822 p. Format : 17 x 24 cm ISBN/ISSN/EAN : 978-3-11-060724-6 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] analyse d'image numérique
[Termes IGN] étalonnage
[Termes IGN] image 3D
[Termes IGN] instrument de photogrammétrie
[Termes IGN] logiciel de photogrammétrie
[Termes IGN] modélisation 3D
[Termes IGN] orientation d'image
[Termes IGN] photogrammétrie métrologique
[Termes IGN] précision des mesures
[Termes IGN] reconstruction 3D
[Termes IGN] transformation mathématiqueIndex. décimale : 33.30 Photogrammétrie numérique Résumé : (Editeur) This is the third edition of the well-known guide to close-range photogrammetry. It provides a thorough presentation of the methods, mathematics, systems and applications which comprise the subject of close-range photogrammetry, which uses accurate imaging techniques to analyse the three-dimensional shape of a wide range of manufactured and natural objects. Note de contenu : 1. Introduction
2. Mathematical fundamentals
3. Imaging technology
4. Analytical methods
5. Digital image analysis
6. Measuring tasks and systems
7. Measurement design and quality
8. Example applicationsNuméro de notice : 26341 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Manuel de cours DOI : 10.1515/9783110607253 Accessibilité hors numérique : Non accessible via le SUDOC En ligne : https://doi.org/10.1515/9783110607253 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95700
Titre : Photogrammetric computer vision : statistics, geometry, orientation and reconstruction Type de document : Guide/Manuel Auteurs : Wolfgang Förstner, Auteur ; Bernhard P. Wrobel, Auteur Editeur : Springer Nature Année de publication : 2016 Collection : Geometry and computing, ISSN 1866-6795 num. 11 Importance : 816 p. Format : 21 x 28 cm ISBN/ISSN/EAN : 978-3-319-11549-8 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] aérotriangulation numérique
[Termes IGN] compensation par faisceaux
[Termes IGN] couple stéréoscopique
[Termes IGN] données maillées
[Termes IGN] données vectorielles
[Termes IGN] estimation statistique
[Termes IGN] géométrie
[Termes IGN] géométrie projective
[Termes IGN] image 2D
[Termes IGN] image 3D
[Termes IGN] incertitude géométrique
[Termes IGN] ligne (géométrie)
[Termes IGN] modèle de Gauss-Markov
[Termes IGN] modèle géométrique de prise de vue
[Termes IGN] plan (géométrie)
[Termes IGN] point
[Termes IGN] reconstruction 3D
[Termes IGN] reconstruction d'objet
[Termes IGN] rotation d'objet
[Termes IGN] semis de points
[Termes IGN] transformation géométrique
[Termes IGN] variable aléatoire
[Termes IGN] vision par ordinateur
[Termes IGN] visualisation 3DIndex. décimale : 33.30 Photogrammétrie numérique Résumé : (Editeur) This textbook offers a statistical view on the geometry of multiple view analysis, required for camera calibration and orientation and for geometric scene reconstruction based on geometric image features. The authors have backgrounds in geodesy and also long experience with development and research in computer vision, and this is the first book to present a joint approach from the converging fields of photogrammetry and computer vision. Part I of the book provides an introduction to estimation theory, covering aspects such as Bayesian estimation, variance components, and sequential estimation, with a focus on the statistically sound diagnostics of estimation results essential in vision metrology. Part II provides tools for 2D and 3D geometric reasoning using projective geometry. This includes oriented projective geometry and tools for statistically optimal estimation and test of geometric entities and transformations and their relations, tools that are useful also in the context of uncertain reasoning in point clouds. Part III is devoted to modelling the geometry of single and multiple cameras, addressing calibration and orientation, including statistical evaluation and reconstruction of corresponding scene features and surfaces based on geometric image features. The authors provide algorithms for various geometric computation problems in vision metrology, together with mathematical justifications and statistical analysis, thus enabling thorough evaluations. The chapters are self-contained with numerous figures and exercises, and they are supported by an appendix that explains the basic mathematical notation and a detailed index. The book can serve as the basis for undergraduate and graduate courses in photogrammetry, computer vision, and computer graphics. It is also appropriate for researchers, engineers, and software developers in the photogrammetry and GIS industries, particularly those engaged with statistically based geometric computer vision methods. Note de contenu : 1. Introduction
1.1. Tasks for Photogrammetric Computer Vision
1.2. Modelling in Photogrammetric Computer Vision
1.3. The Book
1.4. On Notation
Part One - Statistics and Estimation
2. Probability Theory and Random Variables
2.1. Notions of Probability
2.2. Axiomatic Definition of Probability
2.3. Random Variables
2.4. Distributions
2.5. Moments
2.6. Quantiles of a Distribution
2.7. Functions of Random Variables
2.8. Stochastic Processes
2.9. Generating Random Numbers
2.10. Exercises
3. Testing
3.1. Principles of Hypothesis Testing
3.2. Testability of an Alternative Hypothesis
3.3. Common Tests
3.4. Exercises
4. Estimation
4.1. Estimation Theory
4.2. The Linear Gauss–Markov Model
4.3. Gauss–Markov Model with Constraints
4.4. The Nonlinear Gauss–Markov Model
4.5. Datum or Gauge Definitions and Transformations
4.6. Evaluation
4.7. Robust Estimation and Outlier Detection
4.8. Estimation with Implicit Functional Models
4.9. Methods for Closed Form Estimations
4.10. Estimation in Autoregressive Models
4.11. Exercises
Part two - Geometry
5. Homogeneous Representations of Points, Lines and Planes
5.1. Homogeneous Vectors and Matrices
5.2. Homogeneous Representations of Points and Lines in 2D
5.3. Homogeneous Representations in IPn
5.4. Homogeneous Representations of 3D Lines
5.5. On Plücker Coordinates for Points, Lines and Planes
5.6. The Principle of Duality
5.7. Conics and Quadrics
5.8. Normalizations of Homogeneous Vectors
5.9. Canonical Elements of Coordinate Systems
5.10. Exercises
6. Transformations
6.1. Structure of Projective Collineations
6.2. Basic Transformations
6.3. Concatenation and Inversion of Transformations
6.4. Invariants of Projective Mappings
6.5. Perspective Collineations
6.6. Projective Correlations
6.7. Hierarchy of Projective Transformations and Their Characteristics
6.8. Normalizations of Transformations
6.9. Conditioning
6.10. Exercises
7. Geometric Operations
7.1. Geometric Operations in 2D Space
7.2. Geometric Operations in 3D Space
7.3. Vector and Matrix Representations for Geometric Entities
7.4. Minimal Solutions for Conics and Transformations
7.5. Exercises
8. Rotations
8.1. Rotations in 3D
8.2. Concatenation of Rotations
8.3. Relations Between the Representations for Rotations
8.4. Rotations from Corresponding Vector Pairs
8.5. Exercises
9. Oriented Projective Geometry
9.1. Oriented Entities and Constructions
9.2. Transformation of Oriented Entities
9.3. Exercises
10. Reasoning with Uncertain Geometric Entities
10.1. Motivation
10.2. Representing Uncertain Geometric Elements
10.3. Propagation of the Uncertainty of Homogeneous Entities
10.4. Evaluating Statistically Uncertain Relations
10.5. Closed Form Solutions for Estimating Geometric Entities
10.6. Iterative Solutions for Maximum Likelihood Estimation
10.7. Exercises
Part Three - Orientation and Reconstruction
11. Overview
11.1. Scene, Camera, and Image Models
11.2. The Setup of Orientation, Calibration, and Reconstruction
11.3. Exercises
12. Geometry and Orientation of the Single Image
12.1. Geometry of the Single Image
12.2. Orientation of the Single Image
12.3. Inverse Perspective and 3D Information from a Single Image
12.4. Exercises
13. Geometry and Orientation of the Image Pair
13.1. Motivation
13.2 The Geometry of the Image Pair
13.3 Relative Orientation of the Image Pair
13.4. Triangulation
13.5. Absolute Orientation and Spatial Similarity Transformation
13.6. Orientation of the Image Pair and Its Quality
13.7. Exercises
14. Geometry and Orientation of the Image Triplet
14.1. Geometry of the Image Triplet
14.2. Relative Orientation of the Image Triplet
14.3. Exercises
15. Bundle Adjustment
15.1. Motivation for Bundle Adjustment and Its Tasks
15.2. Block Adjustment
15.3. Sparsity of Matrices, Free Adjustment and Theoretical Precision
15.4. Self-calibrating Bundle Adjustment
15.5. Camera Calibration
15.6. Outlier Detection and Approximate Values
15.7. View Planning
15.8. Exercises
16. Surface Reconstruction
16.1. Introduction
16.2. Parametric 21/2D Surfaces
16.3. Models for Reconstructing One-Dimensional Surface Profiles
16.4. Reconstruction of 21/2D Surfaces from 3D Point Clouds
16.5. Examples for Surface Reconstruction
16.6. Exercises
Appendix: Basics and Useful Relations from Linear AlgebraNuméro de notice : 22610 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Manuel Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82915 Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 22610-02 DEP-ECP Livre Marne-la-Vallée Dépôt en unité Exclu du prêt 22610-03 DEP-ELZ Livre Marne-la-Vallée Dépôt en unité Exclu du prêt
Titre : Géoreferencer des plans ou images anciennes : méthodes et précautions à prendre Type de document : Guide/Manuel Auteurs : Cécile Huet Editeur : Champs-sur-Marne : Ecole nationale des sciences géographiques ENSG Année de publication : 2014 Importance : 128 p. Format : 21 x 30 cm Langues : Français (fre) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] carte ancienne
[Termes IGN] géoréférencementIndex. décimale : 33.30 Photogrammétrie numérique Note de contenu : 1. De quels documents parle-t-on ?
1.1. Les types de sources
1.2. Le scannage
2. Le géoréférencement d'une image d'une image sous SIG
2.1. Définition
2.2. Les formats image sous SIG
2.3. Méthodes
2.4. Référentiels
3. Cas typiques
3.1. Carte d'Etat-Major
(3.2. Photo aérienne)Numéro de notice : 15902 Affiliation des auteurs : ENSG (2012-2019) Thématique : GEOMATIQUE Nature : Manuel de cours IGN DOI : sans Accessibilité hors numérique : Non accessible via le SUDOC Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79096 Registration quality - towards integration of laser scanning and photogrammetry / Petri Rönnholm (2011)
Titre : Registration quality - towards integration of laser scanning and photogrammetry Autre titre : Atlas of INSPIRE implementation methods Type de document : Rapport Auteurs : Petri Rönnholm, Auteur ; Ingrid Vanden Berghe, Auteur ; Joep Crompvoets, Auteur ; Walter de Vries, Auteur ; Jantien E. Stoter, Auteur Editeur : Dublin : European Spatial Data Research EuroSDR Année de publication : 2011 Collection : EuroSDR official publication, ISSN 0257-0505 num. 59 Importance : 298 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-90-5179-768-8 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] acquisition de données
[Termes IGN] analyse comparative
[Termes IGN] enregistrement de données
[Termes IGN] instrument aéroporté
[Termes IGN] intégration de données
[Termes IGN] lasergrammétrie
[Termes IGN] photogrammétrie numériqueIndex. décimale : 33.30 Photogrammétrie numérique Résumé : (Auteur)1 : Laser scanning and photogrammetry are powerful 3D data acquisition methods providing both overlapping and complementary information. Currently, integration of laser data and images provides the most complete information for various surveying and 3D modelling tasks. However, this integration requires that both data sets are accurately oriented to the same coordinate system. In 2008, the EuroSDR launched the project "Registration Quality - Towards Integration of Laser Scanning and Photogrammetry" in order to collect knowledge about current registration methods and their performance. The project attracted the involvement of numerous research institutes and companies. Therefore, this test gives a quite extensive set of examples and comparisons of the most important registration strategies today. The empirical results indicated that the relative orientation of airborne laser scanning data and aerial images is a feasible method in order to get data sets within the common coordinate frame. The experiment revealed that, currently, the level of automation was not the most significant factor affecting the quality of registration. More important factors included the type of tie features and the implementation of the methods. The processing time was shortest with most automatic methods, whereas the amount of manual work tended to increase the processing times. It should be noted that many of the methods were still at the developmental stage. It is expected that the performance and processing speed, in most cases, can be enhanced in the future. The test data represented an urban area and many of the methods relied upon certain objects, such as buildings. Therefore, the performance of applied methods in non-built environments should be investigated separately. ;
(Auteur)2 : This report is the final report of the EuroSDR project "Atlas of INSPIRE Implementation Methods". In two two-day workshops and one pre-workshop of the INSPIRE Conference in Krakow, June, 2010 we investigated strategies to implement INSPIRE in several members states. We focused specifically on the relations between the implemented strategy and how successful the INSPIRE implementation is perceived in a specific country. A questionnaire was carried out as well. This report describes the project, presents the conclusions and contains the main deliverables of the project which are: -Two workshop reports - Research agenda for the implementation of INSPIRE -A network of SDI-practitioners and scientists across Europe that are strongly involved in the development of INSPIRE SDI-strategies -Scientific paper publications Scientific paper publications: published IJSDIR article [1] and article in progress for CEUS (Journal for Computers, Environment and Urban Systems) -INSPIRE-Conference pre-conference workshop, abstract and presentation -Key documents collection regarding INSPIRE-implementation -Prototype INSPIRE atlas (see: http://www.spatialist.be)Note de contenu : Registration quality - towards integration of laser scanning and photogrammetry
1 INTRODUCTION
2 DESCRIPTION OF THE PROJECT
2.1 Aims of the project.
2.2 Participants.
2.3 Description of test data
2.4 Reference data.
2.5 Test procedure.
3 SHORT DESCRIPTIONS OF THE APPLIED METHODS
3.1 Method of the Aalto University School of Engineering (Aalto).
3.2 Method of the Dublin Institute of Technology (DIT).
3.3 Method of the Finnish Geodetic Institute, Aalto University School of Engineering and
TerraSolid Oy (FGI et al.)
3.4 Method of the Independent Research Group on Geospatial (IRGG)
3.5 Method 1 of the National Geographic Institute, Spain (IGN-1).
3.6 Method 2 of the National Geographic Institute, Spain (IGN-2) .
3.7 Planar patches method of the University of Calgary (UofC-1).
3.8 Straight lines method of the University of Calgary (UofC-2).
3.9 Combined method of the University of Calgary (UofC-3).
3.10 Method of the University College London (UCL).
3.11 ICP-based method of the University of Stuttgart (IFP-1).
3.12 Point-Based method of the University of Stuttgart (IFP-2)
3.13 Method of the Vienna University of Technology (IPF)
4 RESULTS AND DISCUSSION
4.1 Comparison of planimetric accuracies.
4.2 Comparison of vertical accuracies.
4.3 Comparison of accuracies in rotations.
4.4 Influence of the type of tie features
4.5 Influence of the analytical characteristics of the applied methods
4.6 Influence of the level of automation
4.7 Processing time
5 SUMMARY AND CONCLUSIONS
6 ACKNOWLEDGEMENTS
7 REFERENCES
Atlas of INSPIRE implementation
1 INTRODUCTION
2 QUESTIONNAIRE
2.1 Introduction
2.2 Questions
2.3 Analysis of the questionnaire responses
2.4 Conclusions of the questionnaire
3 REPORT OF 1ST PROJECT WORKSHOP, 29 & 30 APRIL 2009
3.1 Introduction
3.2 Brief description of the Workshop 29 - 30 April 2009
3.3 Research questions identified by the participants
3.4 Main observations during the workshop
3.5 Remarkable quotes
4 REPORT OF 2ND PROJECT WORKSHOP 14/15 JANUARY 2010
4.1 Introduction
4.2 Successes and disappointments
4.3 Propositions
4.4 Research agenda
4.5 Concluding remarks
5 PRE-CONFERENFE INSPIRE WORKSHOP, 22 JUNE 2010
6 CONCLUSIONNuméro de notice : 10477 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Rapport d'étude technique En ligne : http://www.eurosdr.net/sites/default/files/uploaded_files/eurosdr_publication_nd [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=62449 Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 10477-01 33.30 Livre Centre de documentation Photogrammétrie - Lasergrammétrie Disponible Documents numériques
en open access
Eurosdr bull 59Adobe Acrobat PDFAutomatic building reconstruction from aerial images : a generic Bayesian Framework / Patrick Taillandier (2004)
PermalinkPermalinkPermalinkPermalinkPermalink
