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Boresight calibration of low point density Lidar sensors / Sudhagar Nagarajan in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 10 (October 2018)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 10 (October 2018) . - pp 619 - 627 Titre : Boresight calibration of low point density Lidar sensors Type de document : Article/Communication Auteurs : Sudhagar Nagarajan, Auteur ; Shahram Moafipoor, Auteur Année de publication : 2018 Article en page(s) : pp 619 - 627 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] étalonnage d'instrument [Termes IGN] géoréférencement direct [Termes IGN] ligne de visée [Termes IGN] plan (géométrie) [Termes IGN] semis de points Résumé : (Auteur) Mobile Mapping is the technique of acquiring accurate geospatial information of a scene using multiple sensors mounted on a moving platform. At the core of these systems is the direct georeferencing techniques that tie together multi-sensor data on-board. An important aspect of direct georeferencing is to apply accurate boresight calibration of individual sensors with respect to the platform body frame. Conventional techniques use Ground Control Points (GCP) for this calibration. Considering the challenges in identifying GCPs from low density lidar point cloud, this research presents a feature-based registration method that uses control planes. The presented method is performed in a lab-facility utilizing static data to determine the alignment between platform body frame and lidar frame by minimizing the volume formed between low point density lidar and control planes. The paper discusses the mathematical models and feasibility of the technique for use in mapping applications. Numéro de notice : A2018-430 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.10.619 Date de publication en ligne : 01/10/2018 En ligne : https://doi.org/10.14358/PERS.84.10.619 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90988 [article]

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105-2018101	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Photogrammetric computer vision / Wolfgang Förstner (2016)

Public 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 3D Index. 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 Algebra Numéro de notice : 22610 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Manuel Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82915

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22610-03	DEP-ELZ	Livre	Marne-la-Vallée	Dépôt en unité	Exclu du prêt

Weighted straight skeletons in the plane / Therese Biedl in Computational Geometry : theory and applications, vol 48 n° 2 (February 2015)  

Public [article]  inComputational Geometry : theory and applications > vol 48 n° 2 (February 2015) . - pp 120 - 133 Titre : Weighted straight skeletons in the plane Type de document : Article/Communication Auteurs : Therese Biedl, Auteur ; Martin Held, Auteur ; Stefan Huber, Auteur ; Dominik Kaaser, Auteur ; Peter Palfrader, Auteur Année de publication : 2015 Article en page(s) : pp 120 - 133 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] caractérisation [Termes IGN] généralisation automatique de données [Termes IGN] plan (géométrie) [Termes IGN] pondération [Termes IGN] squelettisation Mots-clés libres : Ambiguity  Characterization  Generalization  Positive and negative weights  Straight skeleton Index. décimale : 37.10 Bases de données géographiques Résumé : (auteur) We investigate weighted straight skeletons from a geometric, graph-theoretical, and combinatorial point of view. We start with a thorough definition and shed light on some ambiguity issues in the procedural definition. We investigate the geometry, combinatorics, and topology of faces and the roof model, and we discuss in which cases a weighted straight skeleton is connected. Finally, we show that the weighted straight skeleton of even a simple polygon may be non-planar and may contain cycles, and we discuss under which restrictions on the weights and/or the input polygon the weighted straight skeleton still behaves similar to its unweighted counterpart. In particular, we obtain a non-procedural description and a linear-time construction algorithm for the straight skeleton of strictly convex polygons with arbitrary weights. Numéro de notice : A2015-001 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.comgeo.2014.08.006 En ligne : https://doi.org/10.1016/j.comgeo.2014.08.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74896 [article]

Inner constraints for planar features / Derek D. Lichti in Photogrammetric record, vol 28 n° 141 (March - May 2013)  

Public [article]  inPhotogrammetric record > vol 28 n° 141 (March - May 2013) . - pp 74 - 85 Titre : Inner constraints for planar features Type de document : Article/Communication Auteurs : Derek D. Lichti, Auteur ; Jacky C. K. Chow, Auteur Année de publication : 2013 Article en page(s) : pp 74 - 85 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] auto-étalonnage [Termes IGN] compensation par moindres carrés [Termes IGN] contrainte géométrique [Termes IGN] plan (géométrie) [Termes IGN] télémétrie laser terrestre Résumé : (Auteur) Geometric features, planes in particular, have recently replaced signalised points as the object space primitives of choice for a number of fundamental terrestrial laser scanner data processing tasks such as registration, self-calibration and deformation monitoring. The inner constraints for planes are developed in this paper owing to their importance as the optimal means of datum definition. Pertinent least squares adjustment results from several terrestrial laser scanner datasets are presented to demonstrate the impact of planar inner constraints on registration and self-calibration. When solution quality is measured in terms of parameter precision and correlation, it is demonstrated that the planes should be constrained for both laser scanner registration and self-calibration with a basic additional parameter set. Numéro de notice : A2013-152 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/j.1477-9730.2012.00700.x Date de publication en ligne : 16/12/2012 En ligne : https://doi.org/10.1111/j.1477-9730.2012.00700.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32290 [article]

Exemplaires(1)

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106-2013011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Extracting outlined planar clusters of street facades from 3D point clouds / Karim Hammoudi (2010)  

Public Titre : Extracting outlined planar clusters of street facades from 3D point clouds Type de document : Article/Communication Auteurs : Karim Hammoudi , Auteur ; Fadi Dornaika , Auteur ; Bahman Soheilian , Auteur ; Nicolas Paparoditis , Auteur Editeur : New-York : IEEE Computer society Année de publication : 2010 Conférence : CVR 2010, Canadian Conference on Computer and Robot Vision 31/05/2010 02/06/2010 Ottawa Ontario - Canada Proceedings IEEE Importance : pp 122 - 129 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction automatique [Termes IGN] façade [Termes IGN] Paris (75) [Termes IGN] plan (géométrie) [Termes IGN] scène urbaine [Termes IGN] transformation de Hough Résumé : (auteur) This paper presents an approach for extracting 3D outlined planar clusters of street facades. Terrestrial laser data are acquired using a Mobile Mapping System (MMS). Mapping of street facades is of great interest in various digital mapping and robotic research topics. After a filtering step of the 3D point cloud, the dominant hypothetical facade planes are detected using an adapted Progressive Probabilistic Hough Transform (PPHT). The corresponding planar clusters are extracted using a priori geometric knowledge of street. The clusters are horizontally and vertically delimited using heuristic approaches. The adapted PPHT allows the automatic extraction of georeferenced planar clusters of facades with a fine detection of dominant facade lines and a low computation time. The adopted approach has been tested on a set of point cloud acquired in the city of Paris under real conditions. Examples and experimental results show the efficiency and the potential of the proposed approach. Numéro de notice : C2010-058 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/CRV.2010.23 En ligne : https://doi.ieeecomputersociety.org/10.1109/CRV.2010.23 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101650

Calculs de superficies des figures tracées sur l'ellipsoïde / Albert Reyt (1961)

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