Taking a novel approach to 3D computer vision, An Introduction to 3D ComputerVision Techniques and Algorithms provides a comprehensive coverage of methodsand theory, with a strong emphasis on practical algorithms and implementationissues. The book explores the basics of computer vision, the history of vision research, 2D and 3D vision and image analysis, image matching algorithms, space reconstruction, and multi-view integration. Stressing the importance of real-world application with practical examples of working algorithms, the text is an essential tool for practitioners and programmers, advanced students, and researchers. INDICE: Preface. Acknowledgements. Notation and Abbreviations. Part I. 1 Introduction. 1.1 Stereo-pair Images and Depth Perception. 1.2 3D Vision Systems. 1.3 3D Vision Applications. 1.4 Contents Overview: The 3D Vision Task in Stages. 2 Brief History of Research on Vision. 2.1 Abstract. 2.2 Retrospective of Vision Research. 2.3 Closure. Part II. 3 2D and 3D Vision Formation. 3.1 Abstract. 3.2 Human Visual System. 3.3 Geometry and Acquisition of a Single Image. 3.4 Stereoscopic Acquisition Systems. 3.5 Stereo Matching Constraints. 3.6 Calibration of Cameras. 3.7 Practical Examples. 3.8 Appendix: Derivation of thePin-hole Camera Transformation. 3.9 Closure. 4 Low-level Image Processing forImage Matching. 4.1 Abstract. 4.2 Basic Concepts. 4.3 Discrete Averaging. 4.4Discrete Differentiation. 4.5 Edge Detection. 4.6 Structural Tensor. 4.7 Corner Detection. 4.8 Practical Examples. 4.9 Closure. 5 Scale-space Vision. 5.1 Abstract. 5.2 Basic Concepts. 5.3 Constructing a Scale-space. 5.4 Multi-resolution Pyramids. 5.5 Practical Examples. 5.6 Closure. 6 Image Matching Algorithms. 6.1 Abstract. 6.2 Basic Concepts. 6.3 Match Measures. 6.4 Computational Aspects of Matching. 6.5 Diversity of Stereo Matching Methods. 6.6 Area-based Matching. 6.7 Area-based Elastic Matching. 6.8 Feature-based Image Matching. 6.9 Gradient-based Matching. 6.10 Method of Dynamic Programming. 6.11 Graph Cut Approach. 6.12 Optical Flow. 6.13 Practical Examples. 6.14 Closure. 7 Space Reconstruction and Multiview Integration. 7.1 Abstract. 7.2 General 3D Reconstruction. 7.3 Multiview Integration. 7.4 Closure. 8 Case Examples. 8.1 Abstract. 8.23D System for Vision-Impaired Persons. 8.3 Face and Body Modelling. 8.4 Clinical and Veterinary Applications. 8.5 Movie Restoration. 8.6 Closure. Part III.9 Basics of the Projective Geometry. 9.1 Abstract. 9.2 Homogeneous Coordinates. 9.3 Point, Line and the Rule of Duality. 9.4 Point and Line at Infinity. 9.5 Basics on Conics. 9.6 Group of Projective Transformations. 9.7 Projective Invariants. 9.8 Closure. 10 Basics of Tensor Calculus for Image Processing. 10.1Abstract. 10.2 Basic Concepts. 10.3 Change of a Base. 10.4 Laws of Tensor Transformations. 10.5 The Metric Tensor. 10.6 Simple Tensor Algebra. 10.7 Closure. 11 Distortions and Noise in Images. 11.1 Abstract. 11.2 Types and Models of Noise. 11.3 Generating Noisy Test Images. 11.4 Generating Random Numbers with Normal Distributions. 11.5 Closure. 12 Image Warping Procedures. 12.1 Abstract. 12.2 Architecture of the Warping System. 12.3 Coordinate Transformation Module. 12.4 Interpolation of Pixel Values. 12.5 The Warp Engine. 12.6 Software Model of the Warping Schemes. 12.7 Warp Examples. 12.8 Finding the Linear Transformation from Point Correspondences. 12.9 Closure. 13 Programming Techniques for Image Processing and Computer Vision. 13.1 Abstract. 13.2 Useful Techniquesand Methodology. 13.3 Design Patterns. 13.4 Object Lifetime and Memory Management. 13.5 Image Processing Platforms. 13.6 Closure. 14 Image Processing Library. References. Index.
- ISBN: 978-0-470-01704-3
- Editorial: John Wiley & Sons
- Encuadernacion: Cartoné
- Páginas: 504
- Fecha Publicación: 09/01/2009
- Nº Volúmenes: 1
- Idioma: Inglés