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 Zisserm 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
Multiple View Geometry in Computer Vision
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 Zisserm 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
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Wooi Hen Yap –
The book title says it all. It's not exaggerating when I considered this one a must have for students, practitioners and researchers alike intended to work on 3D computer vision. It covers broad yet deep state-of-the-art methods in 3D reconstruction from multiple cameras, from single camera. However it is not for the faint-hearted .. Not recommended for beginners who had no good knowledge linear algebra, bayesian estimation or tensor algebra. The book title says it all. It's not exaggerating when I considered this one a must have for students, practitioners and researchers alike intended to work on 3D computer vision. It covers broad yet deep state-of-the-art methods in 3D reconstruction from multiple cameras, from single camera. However it is not for the faint-hearted .. Not recommended for beginners who had no good knowledge linear algebra, bayesian estimation or tensor algebra.
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