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Visual perception through video imagery [[electronic resource] /] / edited by Michel Dhome
| Visual perception through video imagery [[electronic resource] /] / edited by Michel Dhome |
| Pubbl/distr/stampa | London, : ISTE |
| Descrizione fisica | 1 online resource (309 p.) |
| Disciplina |
006.3/7
006.42 |
| Altri autori (Persone) | DhomeMichel |
| Collana | ISTE |
| Soggetto topico |
Computer vision
Visual perception Vision |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-282-16494-5
9786612164941 0-470-61104-9 0-470-39362-9 |
| Classificazione | ST 330 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Visual Perception through Video Imagery; Table of Contents; Introduction; Part 1; Chapter 1. Calibration of Vision Sensors; 1.1. Introduction; 1.2. General formulation of the problem of calibration; 1.2.1. Formulation of the problem; 1.2.1.1. Modeling the camera and lens: pin-hole model; 1.2.1.2. Formation of images: perspective projection; 1.2.1.3. Changing lens/camera reference point; 1.2.1.4. Changing of the camera/image point; 1.2.1.5. Changing of coordinates in the image plane; 1.2.2. General expression; 1.2.2.1. General formulation of the problem of calibration; 1.3. Linear approach
1.3.1. Principle1.3.2. Notes and comments; 1.4. Non-linear photogrammetric approach; 1.4.1. Mathematic model; 1.4.2. Solving the problem; 1.4.3. Multi-image calibration; 1.4.4. Self-calibration by bundle adjustment; 1.4.4.1. Redefinition of the problem; 1.4.4.2. Estimation of redundancy; 1.4.4.3. Solution for a near scale factor; 1.4.4.4. Initial conditions; 1.4.5. Precision calculation; 1.5. Results of experimentation; 1.5.1. Bundle adjustment for a traditional lens; 1.5.1.1. Initial and experimental conditions; 1.5.1.2. Sequence of classic images; 1.5.2. Specific case of fish-eye lenses 1.5.2.1. Traditional criterion1.5.2.2. Zero distortion at r0; 1.5.2.3. Normalization of distortion coefficients; 1.5.2.4. Experiments; 1.5.3. Calibration of underwater cameras; 1.5.3.1. Theoretical notes; 1.5.3.2. Experiments; 1.5.3.3. The material; 1.5.3.4. Results in air; 1.5.3.5. Calibration in water; 1.5.3.6. Relation between the calibration in air and in water; 1.5.4. Calibration of zooms; 1.5.4.1. Recalling optical properties; 1.5.4.2. Estimate of the principal point; 1.5.4.3. Experiments; 1.6. Bibliography; Chapter 2. Self-Calibration of Video Sensors; 2.1. Introduction 2.2. Reminder and notation2.3. Huang-Faugeras constraints and Trivedi's equations; 2.3.1. Huang-Faugeras constraints; 2.3.2. Trivedi's constraints; 2.3.3. Discussion; 2.4. Kruppa equations; 2.4.1. Geometric derivation of Kruppa equations; 2.4.2. An algebraic derivation of Kruppa equations; 2.4.3. Simplified Kruppa equations; 2.5. Implementation; 2.5.1. The choice of initial conditions; 2.5.2. Optimization; 2.6. Experimental results; 2.6.1. Estimation of angles and length ratios from images; 2.6.2. Experiments with synthetic data; 2.6.3. Experiments with real data; 2.7. Conclusion 2.8. Acknowledgement2.9. Bibliography; Chapter 3. Specific Displacements for Self-calibration; 3.1. Introduction: interest to resort to specific movements; 3.2. Modeling: parametrization of specific models; 3.2.1. Specific projection models; 3.2.2. Specifications of internal parameters of the camera; 3.2.3. Taking into account specific displacements; 3.2.4. Relation with specific properties in the scene; 3.3. Self-calibration of a camera; 3.3.1. Usage of pure rotations or points at the horizon; 3.3.2. Pure rotation and fixed parameters; 3.3.3. Rotation around a fixed axis 3.4. Perception of depth |
| Record Nr. | UNINA-9910139468403321 |
| London, : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Visual perception through video imagery [[electronic resource] /] / edited by Michel Dhome
| Visual perception through video imagery [[electronic resource] /] / edited by Michel Dhome |
| Pubbl/distr/stampa | London, : ISTE |
| Descrizione fisica | 1 online resource (309 p.) |
| Disciplina |
006.3/7
006.42 |
| Altri autori (Persone) | DhomeMichel |
| Collana | ISTE |
| Soggetto topico |
Computer vision
Visual perception Vision |
| ISBN |
1-282-16494-5
9786612164941 0-470-61104-9 0-470-39362-9 |
| Classificazione | ST 330 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Visual Perception through Video Imagery; Table of Contents; Introduction; Part 1; Chapter 1. Calibration of Vision Sensors; 1.1. Introduction; 1.2. General formulation of the problem of calibration; 1.2.1. Formulation of the problem; 1.2.1.1. Modeling the camera and lens: pin-hole model; 1.2.1.2. Formation of images: perspective projection; 1.2.1.3. Changing lens/camera reference point; 1.2.1.4. Changing of the camera/image point; 1.2.1.5. Changing of coordinates in the image plane; 1.2.2. General expression; 1.2.2.1. General formulation of the problem of calibration; 1.3. Linear approach
1.3.1. Principle1.3.2. Notes and comments; 1.4. Non-linear photogrammetric approach; 1.4.1. Mathematic model; 1.4.2. Solving the problem; 1.4.3. Multi-image calibration; 1.4.4. Self-calibration by bundle adjustment; 1.4.4.1. Redefinition of the problem; 1.4.4.2. Estimation of redundancy; 1.4.4.3. Solution for a near scale factor; 1.4.4.4. Initial conditions; 1.4.5. Precision calculation; 1.5. Results of experimentation; 1.5.1. Bundle adjustment for a traditional lens; 1.5.1.1. Initial and experimental conditions; 1.5.1.2. Sequence of classic images; 1.5.2. Specific case of fish-eye lenses 1.5.2.1. Traditional criterion1.5.2.2. Zero distortion at r0; 1.5.2.3. Normalization of distortion coefficients; 1.5.2.4. Experiments; 1.5.3. Calibration of underwater cameras; 1.5.3.1. Theoretical notes; 1.5.3.2. Experiments; 1.5.3.3. The material; 1.5.3.4. Results in air; 1.5.3.5. Calibration in water; 1.5.3.6. Relation between the calibration in air and in water; 1.5.4. Calibration of zooms; 1.5.4.1. Recalling optical properties; 1.5.4.2. Estimate of the principal point; 1.5.4.3. Experiments; 1.6. Bibliography; Chapter 2. Self-Calibration of Video Sensors; 2.1. Introduction 2.2. Reminder and notation2.3. Huang-Faugeras constraints and Trivedi's equations; 2.3.1. Huang-Faugeras constraints; 2.3.2. Trivedi's constraints; 2.3.3. Discussion; 2.4. Kruppa equations; 2.4.1. Geometric derivation of Kruppa equations; 2.4.2. An algebraic derivation of Kruppa equations; 2.4.3. Simplified Kruppa equations; 2.5. Implementation; 2.5.1. The choice of initial conditions; 2.5.2. Optimization; 2.6. Experimental results; 2.6.1. Estimation of angles and length ratios from images; 2.6.2. Experiments with synthetic data; 2.6.3. Experiments with real data; 2.7. Conclusion 2.8. Acknowledgement2.9. Bibliography; Chapter 3. Specific Displacements for Self-calibration; 3.1. Introduction: interest to resort to specific movements; 3.2. Modeling: parametrization of specific models; 3.2.1. Specific projection models; 3.2.2. Specifications of internal parameters of the camera; 3.2.3. Taking into account specific displacements; 3.2.4. Relation with specific properties in the scene; 3.3. Self-calibration of a camera; 3.3.1. Usage of pure rotations or points at the horizon; 3.3.2. Pure rotation and fixed parameters; 3.3.3. Rotation around a fixed axis 3.4. Perception of depth |
| Record Nr. | UNINA-9910830635703321 |
| London, : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Visual perception through video imagery / / edited by Michel Dhome
| Visual perception through video imagery / / edited by Michel Dhome |
| Pubbl/distr/stampa | London, : ISTE |
| Descrizione fisica | 1 online resource (309 p.) |
| Disciplina | 006.3/7 |
| Altri autori (Persone) | DhomeMichel |
| Collana | ISTE |
| Soggetto topico |
Computer vision
Visual perception Vision |
| ISBN |
1-282-16494-5
9786612164941 0-470-61104-9 0-470-39362-9 |
| Classificazione | ST 330 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Visual Perception through Video Imagery; Table of Contents; Introduction; Part 1; Chapter 1. Calibration of Vision Sensors; 1.1. Introduction; 1.2. General formulation of the problem of calibration; 1.2.1. Formulation of the problem; 1.2.1.1. Modeling the camera and lens: pin-hole model; 1.2.1.2. Formation of images: perspective projection; 1.2.1.3. Changing lens/camera reference point; 1.2.1.4. Changing of the camera/image point; 1.2.1.5. Changing of coordinates in the image plane; 1.2.2. General expression; 1.2.2.1. General formulation of the problem of calibration; 1.3. Linear approach
1.3.1. Principle1.3.2. Notes and comments; 1.4. Non-linear photogrammetric approach; 1.4.1. Mathematic model; 1.4.2. Solving the problem; 1.4.3. Multi-image calibration; 1.4.4. Self-calibration by bundle adjustment; 1.4.4.1. Redefinition of the problem; 1.4.4.2. Estimation of redundancy; 1.4.4.3. Solution for a near scale factor; 1.4.4.4. Initial conditions; 1.4.5. Precision calculation; 1.5. Results of experimentation; 1.5.1. Bundle adjustment for a traditional lens; 1.5.1.1. Initial and experimental conditions; 1.5.1.2. Sequence of classic images; 1.5.2. Specific case of fish-eye lenses 1.5.2.1. Traditional criterion1.5.2.2. Zero distortion at r0; 1.5.2.3. Normalization of distortion coefficients; 1.5.2.4. Experiments; 1.5.3. Calibration of underwater cameras; 1.5.3.1. Theoretical notes; 1.5.3.2. Experiments; 1.5.3.3. The material; 1.5.3.4. Results in air; 1.5.3.5. Calibration in water; 1.5.3.6. Relation between the calibration in air and in water; 1.5.4. Calibration of zooms; 1.5.4.1. Recalling optical properties; 1.5.4.2. Estimate of the principal point; 1.5.4.3. Experiments; 1.6. Bibliography; Chapter 2. Self-Calibration of Video Sensors; 2.1. Introduction 2.2. Reminder and notation2.3. Huang-Faugeras constraints and Trivedi's equations; 2.3.1. Huang-Faugeras constraints; 2.3.2. Trivedi's constraints; 2.3.3. Discussion; 2.4. Kruppa equations; 2.4.1. Geometric derivation of Kruppa equations; 2.4.2. An algebraic derivation of Kruppa equations; 2.4.3. Simplified Kruppa equations; 2.5. Implementation; 2.5.1. The choice of initial conditions; 2.5.2. Optimization; 2.6. Experimental results; 2.6.1. Estimation of angles and length ratios from images; 2.6.2. Experiments with synthetic data; 2.6.3. Experiments with real data; 2.7. Conclusion 2.8. Acknowledgement2.9. Bibliography; Chapter 3. Specific Displacements for Self-calibration; 3.1. Introduction: interest to resort to specific movements; 3.2. Modeling: parametrization of specific models; 3.2.1. Specific projection models; 3.2.2. Specifications of internal parameters of the camera; 3.2.3. Taking into account specific displacements; 3.2.4. Relation with specific properties in the scene; 3.3. Self-calibration of a camera; 3.3.1. Usage of pure rotations or points at the horizon; 3.3.2. Pure rotation and fixed parameters; 3.3.3. Rotation around a fixed axis 3.4. Perception of depth |
| Record Nr. | UNINA-9910877476003321 |
| London, : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||