9780470017043

An Introduction to 3D Computer Vision Algorithms and Techniques takes a novel approach to 3D computer vision as it gives comprehensive coverage of methods and theory, but with a strong emphasis on practical algorithms and implementation issues. The book ranges from an overview of the basics of computer vision, with a brief history of vision research and a section on 2D and 3D vision and image analysis, to chapters exploring a range of image matching algorithms, space reconstruction and multi view integration. Concise appendices consolidate advanced modern methods for image analysis such as projective geometry and tensor algebra for machine vision, allowing the reader to become quickly acquainted with these topics. Cyganek and Siebert continually stress the importance of real-world application with practical examples of working algorithms, a chapter on case studies, suggestions for further reading and end-of-chapter exercises and problems. Overall, this text provides an accessible inter-disciplinary reference for advanced students, researchers, practitioners and programmers in the fields of computer science, engineering, robotics and mathematics.

Boguslaw Cyganek, AGH – University of Science and Technology, Department of Computer Science, Signal Processing Laboratory, Krakow, Poland

Boguslaw Cyganek has been teaching at the AGH – University of Science and Technology since 1993 and is now a Lecturer and Researcher in the Department of Electronics and Computer Science. His research interests include the development of image processing systems, robot vision and neural networks. During this time, he has gained several years of practical experience working as a Software Development Manager and a Software Engineer both in the USA and Poland. He has also written Three Dimensional Image Processing (Academic Publisher House, 2002) and 18 academic papers on image processing and algorithms.

Paul Siebert, Department of Computing Science, University of Glasgow, 3D-MATIC Research Laboratory, Scotland

Dr Jan Paul Siebert is currently Director of the 3D-MATIC Research Laboratory in the Department of Computing Science at Glasgow University. His research interests are in computer vision, image processing, and 3D imaging by stereo photogrammetry and its applications in 3D whole human body imaging. He is Scottish Chair of the BMVC and prior to his current position he was Chief Executive of the of the Turing Institute, Glasgow, which developed the ‘C3D’ imaging technology. He has written over 50 journal, technical and conference papers on 3D image processing, modelling virtual images and photogrammetry.

Preface
Acknowledgements
Notation and Abbreviations

Introduction
Stereo-pair Images and Depth Perception
3D Vision Systems
3D Vision Applications
Contents Overview: The 3D Vision Task in Stages
Brief History of Research on Vision
Abstract
Retrospective of Vision Research
Closure
3 2D and 3D Vision Formation
Abstract
Human Visual System
Geometry and Acquisition of a Single Image
Stereoscopic Acquisition Systems
Stereo Matching Constraints
Calibration of Cameras
Practical Examples
Appendix: Derivation of the Pin-hole Camera Transformation
Closure
Low-level Image Processing for Image Matching
Abstract
Basic Concepts
Discrete Averaging
Discrete Differentiation
Edge Detection
Structural Tensor
Corner Detection
Practical Examples
Closure
Scale-space Vision
Abstract
Basic Concepts
Constructing a Scale-space
Multi-resolution Pyramids
Practical Examples
Closure
Image Matching Algorithms
Abstract
Basic Concepts
Match Measures
Computational Aspects of Matching
Diversity of Stereo Matching Methods
Area-based Matching
Area-based Elastic Matching
Feature-based Image Matching
Gradient-based Matching
Method of Dynamic Programming
Graph Cut Approach
Optical Flow
Practical Examples
Closure
Space Reconstruction and Multiview Integration
Abstract
General 3D Reconstruction
Multiview Integration
Closure
Case Examples
Abstract
3D System for Vision-Impaired Persons
Face and Body Modelling
Clinical and Veterinary Applications
Movie Restoration
Closure

Basics of the Projective Geometry
Abstract
Homogeneous Coordinates
Point, Line and the Rule of Duality
Point and Line at Infinity
Basics on Conics
Group of Projective Transformations
Projective Invariants
Closure
Basics of Tensor Calculus for Image Processing
Abstract
Basic Concepts
Change of a Base
Laws of Tensor Transformations
The Metric Tensor
Simple Tensor Algebra
Closure
Distortions and Noise in Images
Abstract
Types and Models of Noise
Generating Noisy Test Images
Generating Random Numbers with Normal Distributions
Closure
Image Warping Procedures
Abstract
Architecture of the Warping System
Coordinate Tran
Table of Contents provided by Publisher. All Rights Reserved.

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An Introduction to 3d Computer Vision Techniques and Algorithms

An Introduction to 3d Computer Vision Techniques and Algorithms

047001704X

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