Programming Computer Vision with Python

If you want a basic understanding of computer vision’s underlying theory and algorithms, this hands-on introduction is the ideal place to start. You’ll learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, and other computer vision applications as you follow clear examples written in Python. COMPUTERS / Computer Vision & Pattern Recognition A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book. A Basic Problem In Computer Vision Is To Understand The Structure Of A Real World Scene Given Several Images Of It. The Authors Cover The Geometric Principles And Their Algebraic Representation In Terms Of Camera Projection Matrices, The Fundamental Matrix And The Trifocal Tensor. I. Introduction : A Tour Of Multiple View Geometry -- Part 0. The Background : Projective Geometry, Transformations And Estimation -- Part 1. Camera Geometry And Single View Geometry -- Part 2. Two-view Geometry -- Part 3. Three-view Geometry -- Part 4. N-view Geometry -- Part 5. Appendices. Richard Hartley, Andrew Zisserman. Includes Bibliographical References (p. 634-645) And Index. A basic problem in computer vision is to understand the structure of a real world scene. This book covers relevant geometric principles and how to represent objects algebraically so they can be computed and applied. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. Richard Hartley and Andrew Zisserman provide comprehensive background material and explain how to apply the methods and implement the algorithms. First Edition HB (2000): 0-521-62304-9