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An introduction to 3D computer vision techniques and algorithms [[electronic resource] /] / Bogusław Cyganek, J. Paul Siebert
| An introduction to 3D computer vision techniques and algorithms [[electronic resource] /] / Bogusław Cyganek, J. Paul Siebert |
| Autore | Cyganek Bogusław |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Chichester, U.K., : John Wiley & Sons, 2009 |
| Descrizione fisica | 1 online resource (514 p.) |
| Disciplina |
006.3/7
006.37 |
| Altri autori (Persone) | SiebertJ. Paul |
| Soggetto topico |
Computer vision
Three-dimensional imaging Computer algorithms |
| ISBN |
1-119-96447-4
1-282-03422-7 9786612034220 0-470-69972-8 0-470-71444-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
AN INTRODUCTION TO 3D COMPUTER VISION TECHNIQUES AND ALGORITHMS; Contents; Preface; Acknowledgements; Notation and Abbreviations; Part I; 1 Introduction; 2 Brief History of Research on Vision; Part II; 3 2D and 3D Vision Formation; 4 Low-level Image Processing for Image Matching; 5 Scale-space Vision; 6 Image Matching Algorithms; 7 Space Reconstruction and Multiview Integration; 8 Case Examples; Part III; 9 Basics of the Projective Geometry; 10 Basics of Tensor Calculus for Image Processing; 11 Distortions and Noise in Images; 12 Image Warping Procedures
13 Programming Techniques for Image Processing and Computer Vision14 Image Processing Library; References; Index; Colorplate |
| Record Nr. | UNINA-9910145261603321 |
Cyganek Bogusław
|
||
| Chichester, U.K., : John Wiley & Sons, 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
An introduction to 3D computer vision techniques and algorithms [[electronic resource] /] / Bogusław Cyganek, J. Paul Siebert
| An introduction to 3D computer vision techniques and algorithms [[electronic resource] /] / Bogusław Cyganek, J. Paul Siebert |
| Autore | Cyganek Bogusław |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Chichester, U.K., : John Wiley & Sons, 2009 |
| Descrizione fisica | 1 online resource (514 p.) |
| Disciplina |
006.3/7
006.37 |
| Altri autori (Persone) | SiebertJ. Paul |
| Soggetto topico |
Computer vision
Three-dimensional imaging Computer algorithms |
| ISBN |
1-119-96447-4
1-282-03422-7 9786612034220 0-470-69972-8 0-470-71444-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
AN INTRODUCTION TO 3D COMPUTER VISION TECHNIQUES AND ALGORITHMS; Contents; Preface; Acknowledgements; Notation and Abbreviations; Part I; 1 Introduction; 2 Brief History of Research on Vision; Part II; 3 2D and 3D Vision Formation; 4 Low-level Image Processing for Image Matching; 5 Scale-space Vision; 6 Image Matching Algorithms; 7 Space Reconstruction and Multiview Integration; 8 Case Examples; Part III; 9 Basics of the Projective Geometry; 10 Basics of Tensor Calculus for Image Processing; 11 Distortions and Noise in Images; 12 Image Warping Procedures
13 Programming Techniques for Image Processing and Computer Vision14 Image Processing Library; References; Index; Colorplate |
| Record Nr. | UNINA-9910830734503321 |
|
Cyganek Bogusław
|
||
| Chichester, U.K., : John Wiley & Sons, 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Object detection and recognition in digital images [[electronic resource] ] : theory and practice / / Bogusław Cyganek
| Object detection and recognition in digital images [[electronic resource] ] : theory and practice / / Bogusław Cyganek |
| Autore | Cyganek Bogusław |
| Pubbl/distr/stampa | Chichester, West Sussex, U.K., : John Wiley & Sons, Inc., 2013 |
| Descrizione fisica | 1 online resource (552 p.) |
| Disciplina | 621.39/94 |
| Soggetto topico |
Pattern recognition systems
Image processing - Digital techniques Computer vision |
| ISBN |
1-118-61836-X
1-118-61838-6 1-118-61837-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
OBJECT DETECTION AND RECOGNITION IN DIGITAL IMAGES; Contents; Preface; Acknowledgements; Notations and Abbreviations; 1 Introduction; 1.1 A Sample of Computer Vision; 1.2 Overview of Book Contents; References; 2 Tensor Methods in Computer Vision; 2.1 Abstract; 2.2 Tensor - A Mathematical Object; 2.2.1 Main Properties of Linear Spaces; 2.2.2 Concept of a Tensor; 2.3 Tensor - A Data Object; 2.4 Basic Properties of Tensors; 2.4.1 Notation of Tensor Indices and Components; 2.4.2 Tensor Products; 2.5 Tensor Distance Measures; 2.5.1 Overview of Tensor Distances
2.5.1.1 Computation of Matrix Exponent and Logarithm Functions2.5.2 Euclidean Image Distance and Standardizing Transform; 2.6 Filtering of Tensor Fields; 2.6.1 Order Statistic Filtering of Tensor Data; 2.6.2 Anisotropic Diffusion Filtering; 2.6.3 IMPLEMENTATION of Diffusion Processes; 2.7 Looking into Images with the Structural Tensor; 2.7.1 Structural Tensor in Two-Dimensional Image Space; 2.7.2 Spatio-Temporal Structural Tensor; 2.7.3 Multichannel and Scale-Space Structural Tensor; 2.7.4 Extended Structural Tensor; 2.7.4.1 IMPLEMENTATION of the Linear and Nonlinear Structural Tensor 2.8 Object Representation with Tensor of Inertia and Moments2.8.1 IMPLEMENTATION of Moments and their Invariants; 2.9 Eigendecomposition and Representation of Tensors; 2.10 Tensor Invariants; 2.11 Geometry of Multiple Views: The Multifocal Tensor; 2.12 Multilinear Tensor Methods; 2.12.1 Basic Concepts of Multilinear Algebra; 2.12.1.1 Tensor Flattening; 2.12.1.2 IMPLEMENTATION Tensor Representation; 2.12.1.3 The k-mode Product of a Tensor and a Matrix; 2.12.1.4 Ranks of a Tensor; 2.12.1.5 IMPLEMENTATION of Basic Operations on Tensors; 2.12.2 Higher-Order Singular Value Decomposition (HOSVD) 2.12.3 Computation of the HOSVD2.12.3.1 Implementation of the HOSVD Decomposition; 2.12.4 HOSVD Induced Bases; 2.12.5 Tensor Best Rank-1 Approximation; 2.12.6 Rank-1 Decomposition of Tensors; 2.12.7 Best Rank-(R1, R2, . . . , RP) Approximation; 2.12.8 Computation of the Best Rank-(R1, R2, . . . , RP) Approximations; 2.12.8.1 IMPLEMENTATION - Rank Tensor Decompositions; 2.12.8.2 CASE STUDY - Data Dimensionality Reduction; 2.12.9 Subspace Data Representation; 2.12.10 Nonnegative Matrix Factorization; 2.12.11 Computation of the Nonnegative Matrix Factorization 2.12.12 Image Representation with NMF2.12.13 Implementation of the Nonnegative Matrix Factorization; 2.12.14 Nonnegative Tensor Factorization; 2.12.15 Multilinear Methods of Object Recognition; 2.13 Closure; 2.13.1 Chapter Summary; 2.13.2 Further Reading; 2.13.3 Problems and Exercises; References; 3 Classification Methods and Algorithms; 3.1 Abstract; 3.2 Classification Framework; 3.2.1 IMPLEMENTATION Computer Representation of Features; 3.3 Subspace Methods for Object Recognition; 3.3.1 Principal Component Analysis; 3.3.1.1 Computation of the PCA 3.3.1.2 PCA for Multi-Channel Image Processing |
| Record Nr. | UNINA-9910141726103321 |
|
Cyganek Bogusław
|
||
| Chichester, West Sussex, U.K., : John Wiley & Sons, Inc., 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Object detection and recognition in digital images : theory and practice / / Bogusław Cyganek
| Object detection and recognition in digital images : theory and practice / / Bogusław Cyganek |
| Autore | Cyganek Bogusław |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Chichester, West Sussex, U.K., : John Wiley & Sons, Inc., 2013 |
| Descrizione fisica | 1 online resource (552 p.) |
| Disciplina | 621.39/94 |
| Soggetto topico |
Pattern recognition systems
Image processing - Digital techniques Computer vision |
| ISBN |
1-118-61836-X
1-118-61838-6 1-118-61837-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
OBJECT DETECTION AND RECOGNITION IN DIGITAL IMAGES; Contents; Preface; Acknowledgements; Notations and Abbreviations; 1 Introduction; 1.1 A Sample of Computer Vision; 1.2 Overview of Book Contents; References; 2 Tensor Methods in Computer Vision; 2.1 Abstract; 2.2 Tensor - A Mathematical Object; 2.2.1 Main Properties of Linear Spaces; 2.2.2 Concept of a Tensor; 2.3 Tensor - A Data Object; 2.4 Basic Properties of Tensors; 2.4.1 Notation of Tensor Indices and Components; 2.4.2 Tensor Products; 2.5 Tensor Distance Measures; 2.5.1 Overview of Tensor Distances
2.5.1.1 Computation of Matrix Exponent and Logarithm Functions2.5.2 Euclidean Image Distance and Standardizing Transform; 2.6 Filtering of Tensor Fields; 2.6.1 Order Statistic Filtering of Tensor Data; 2.6.2 Anisotropic Diffusion Filtering; 2.6.3 IMPLEMENTATION of Diffusion Processes; 2.7 Looking into Images with the Structural Tensor; 2.7.1 Structural Tensor in Two-Dimensional Image Space; 2.7.2 Spatio-Temporal Structural Tensor; 2.7.3 Multichannel and Scale-Space Structural Tensor; 2.7.4 Extended Structural Tensor; 2.7.4.1 IMPLEMENTATION of the Linear and Nonlinear Structural Tensor 2.8 Object Representation with Tensor of Inertia and Moments2.8.1 IMPLEMENTATION of Moments and their Invariants; 2.9 Eigendecomposition and Representation of Tensors; 2.10 Tensor Invariants; 2.11 Geometry of Multiple Views: The Multifocal Tensor; 2.12 Multilinear Tensor Methods; 2.12.1 Basic Concepts of Multilinear Algebra; 2.12.1.1 Tensor Flattening; 2.12.1.2 IMPLEMENTATION Tensor Representation; 2.12.1.3 The k-mode Product of a Tensor and a Matrix; 2.12.1.4 Ranks of a Tensor; 2.12.1.5 IMPLEMENTATION of Basic Operations on Tensors; 2.12.2 Higher-Order Singular Value Decomposition (HOSVD) 2.12.3 Computation of the HOSVD2.12.3.1 Implementation of the HOSVD Decomposition; 2.12.4 HOSVD Induced Bases; 2.12.5 Tensor Best Rank-1 Approximation; 2.12.6 Rank-1 Decomposition of Tensors; 2.12.7 Best Rank-(R1, R2, . . . , RP) Approximation; 2.12.8 Computation of the Best Rank-(R1, R2, . . . , RP) Approximations; 2.12.8.1 IMPLEMENTATION - Rank Tensor Decompositions; 2.12.8.2 CASE STUDY - Data Dimensionality Reduction; 2.12.9 Subspace Data Representation; 2.12.10 Nonnegative Matrix Factorization; 2.12.11 Computation of the Nonnegative Matrix Factorization 2.12.12 Image Representation with NMF2.12.13 Implementation of the Nonnegative Matrix Factorization; 2.12.14 Nonnegative Tensor Factorization; 2.12.15 Multilinear Methods of Object Recognition; 2.13 Closure; 2.13.1 Chapter Summary; 2.13.2 Further Reading; 2.13.3 Problems and Exercises; References; 3 Classification Methods and Algorithms; 3.1 Abstract; 3.2 Classification Framework; 3.2.1 IMPLEMENTATION Computer Representation of Features; 3.3 Subspace Methods for Object Recognition; 3.3.1 Principal Component Analysis; 3.3.1.1 Computation of the PCA 3.3.1.2 PCA for Multi-Channel Image Processing |
| Record Nr. | UNINA-9910815468903321 |
|
Cyganek Bogusław
|
||
| Chichester, West Sussex, U.K., : John Wiley & Sons, Inc., 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||