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Multiple View Geometry in Computer Vision 2nd Edition

by Richard Hartley (Author), Andrew Zisserman (Author)
4.7 out of 5 stars 116 ratings
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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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  1. ISBN-10
    0521540518
  2. ISBN-13
    978-0521540513
  3. Edition
    2nd
  4. Publisher
    Cambridge University Press
  5. Publication date
    April 19, 2004
  6. Language
    English
  7. Dimensions
    7 x 0.25 x 9.5 inches
  8. Print length
    670 pages
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Editorial Reviews

Review

"The authors have succeeded very well in describing the main techniques in mainstream multiple view geometry, both classical and modern, in a clear and consistent way....I heartily recommend this book." Computing Reviews

Book Description

How to reconstruct scenes from images using geometry and algebra, with applications to computer vision.

Product details

  • Publisher ‏ : ‎ Cambridge University Press
  • Publication date ‏ : ‎ April 19, 2004
  • Edition ‏ : ‎ 2nd
  • Language ‏ : ‎ English
  • Print length ‏ : ‎ 670 pages
  • ISBN-10 ‏ : ‎ 0521540518
  • ISBN-13 ‏ : ‎ 978-0521540513
  • Item Weight ‏ : ‎ 3.25 pounds
  • Dimensions ‏ : ‎ 7 x 0.25 x 9.5 inches
  • Customer Reviews:
    4.7 out of 5 stars 116 ratings

About the author

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Richard Hartley

Richard Hartley

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Richard Hartley is a professor at the Australian National University and Distinguished Researcher at NICTA in Canberra. His main area of research is Computer Vision.

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4.7 out of 5 stars
116 global ratings

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Top reviews from the United States

  • JDH
    5.0 out of 5 stars Excellent, Self-Contained Text Book
    Reviewed in the United States on April 11, 2020
    Verified Purchase
    I value text books that are clearly written. You can look at the description of two books, they seem identical, but one is clear and easy to understand, while the other makes no sense at all. This text book is very clearly written, and it's a pleasure to read.

    The book is almost entirely self contained, though understanding Projective Geometry first will help. "Geometry and Analysis of Projective Spaces" by C. E. Springer is a good choice for that. The only weak spot in this book was the description of Plucker lines. Fortunately, these were not used extensively later in the text.
    4 people found this helpful
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  • Michael Sander
    5.0 out of 5 stars Multiple View Geometry - Step by Step
    Reviewed in the United States on May 23, 2013
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    I graduated engineering school several years ago and was a bit intimidated to start something so new, but Hartley does a magnificent job of breaking things down into readable English.

    Have you ever wondered why 4x4 matrices are used in computer graphics? In school we got a half-way answer about the projective matrix, but it was never really satisfying. This book explains the math behind that and much more clearly, leaving you with many "ah ha" moments.
    3 people found this helpful
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  • Che-Tsung Lin
    5.0 out of 5 stars The best book to learn 3D remodeling
    Reviewed in the United States on July 8, 2013
    Verified Purchase
    This book introduces the detail and necessary knowledge in remodeling 3D from multiple images captured either simultaneously or chronologically. For advanced researcher, this book is extremely helpful but it is quite difficult for beginner's level. For anybody wanting to study this field from scratch, i would recommend "Introductory Techniques for 3-D Computer Vision" which is rather easy and explains the algorithm without the requirement of possessing prior field knowledge.
    4 people found this helpful
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  • amanuensis
    5.0 out of 5 stars Outstanding introductory text.
    Reviewed in the United States on September 10, 2012
    Verified Purchase
    First a disclaimer. I am not an expert on projective geometry. However, I found the topics to be clearly explained and motivated so that I had no trouble following the progression. I only wish I had found this book sooner, as I spent much time and effort developing algorithms and formulae that I could have picked straight from the chapters of this text.
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  • calvinnme
    4.0 out of 5 stars Good on the explanations of the theory
    Reviewed in the United States on April 26, 2009
    Verified Purchase
    This book is very complete and rigorous in its explanations of the theory. However, I just think I like the approach in An Invitation to 3-D Vision a bit better. This book is better illustrated than that one and is more careful in its explanations, but this book just seems more focused on providing complete proofs than giving you a feel for how you would approach a real problem. Even the exercises are more along the lines of proofs. I like how An Invitation to 3-D Vision ends the book with a complete example. In all fairness, though, this book does have quite a bit of Matlab code on its website.

    The book begins with some background material on 2D and 3D geometry. Then the author explains single-view geometry and how cameras map an image in 3D space to an image. Two-view geometry is next, with the author describing the epipolar geometry of two cameras ahd projective reconstruction from resulting image map correspondences. Part three of the book extends ideas to three cameras and the resulting trifocal geometry. The final section of the book takes the algorithms of the book to N views. Thus this book has a simple and straightforward structure that belies the complexity of the material.

    If you are really researching this subject you should probably have this book for explanation, illustrations, and rigor, and the Invitation book for enlightenment through a good example-based approach. You should also have Introductory Techniques for 3-D Computer Vision as a text on the individual pieces of algorithms involved in 3D vision. And don't even think about getting into this subject unless you already have a firm foundation in linear algebra, image processing, and computer vision in general as found in Computer Vision, which is my favorite introductory computer vision text.
    48 people found this helpful
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  • Sunny Au Yeung
    5.0 out of 5 stars Delivery date and packing
    Reviewed in the United States on November 18, 2021
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    Just satisfied with the book and delivery.
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  • vicjo
    5.0 out of 5 stars When it comes to vision give me glasses....
    Reviewed in the United States on June 23, 2013
    Verified Purchase
    Great book for anyone interested in Geometry Computer Vision. Can explain in a way you can pick it up and use it. Again it was a gift and makes a wonderful gift for someone in this field.
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  • Jace Priester
    5.0 out of 5 stars Great book. Buy it.
    Reviewed in the United States on August 4, 2011
    Verified Purchase
    If you're interested in photogrammetry, buy this book. Extremely well written, extremely informative, and more clear than I could have hoped for. The only thing it doesn't provide is written out code (not even pseudocode) - just a plain-English description of each algorithm's steps.
    One person found this helpful
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  • n00dle
    5.0 out of 5 stars Pretty much the bible for projective transforms and multi-view geometry
    Reviewed in the United Kingdom on October 3, 2018
    Verified Purchase
    Well written, clear and concise. Builds complexity at a sensible level.
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  • Sunu Wibirama
    5.0 out of 5 stars Great book for 3D reconstruction - need explanation for learning roadmap
    Reviewed in Japan on May 19, 2014
    Verified Purchase
    I have been doing research in 3D computer vision since 2008, but I really got a chance to buy this book just only recently. This is a great book for researcher who studies 3D computer vision and vision-based robotics (i.e.: reconstructing 3D model from multiple images, camera calibration, using stereo camera for visual odometry, etc.). One thing that I admire from this book is the ability of both authors to explain the philosophy behind projective space and homogeneous coordinate. You can find a bunch of equations on the other books, but you can only find here the reason of why we need to use projective space when dealing with 3D reconstruction from multiple images.

    Geometry and algebra require strong imagination. However, a picture is worth a thousand words. This book provides several illustrations that help you understand what the authors meant in explaining several crucial terms, such as affine transformation, distortion from camera projection, etc.

    Several suggestions for better improvement:

    1. The companion website is useful: http://www.robots.ox.ac.uk/~vgg/hzbook/
    However, it is not periodically updated. If the authors can provide a live blog or a github account to provide contributed source code, this book will be really awesome and useful, even for beginners. I really admire how Matthew A. Russell (author of Mining the Social Web) helps his readers developing their skill using his book. He also gives opportunity to his readers to delve broader topics.
    Take a look at these pages:
    https://github.com/ptwobrussell/Mining-the-Social-Web-2nd-Edition
    http://miningthesocialweb.com/

    2. It is better if authors provide "learning road map" for whom newly entering research area in 3D computer vision. New researcher often asks: "What should I do to grasp the content of this book? You said that your book is a primary source in 3D computer vision, but what are introductory references needed to understand your book?"

    Personally, I will suggest you to read a classic "An Introductory Techniques for 3-D Computer Vision" by Trucco and Verri (1998) before getting "bigger image" of what can be done by 3D computer vision. For math, "Introduction to Linear Algebra" by Strang is my favorite.

    Finally, I really recommend this book in your reading list, if you are working on 3D computer vision. You will never regret to have this book in your bookshelf.
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  • Claudia Ramírez
    5.0 out of 5 stars Este libro "is a must" sí investiga sobre vision por computadora, particularmente multiocular.
    Reviewed in Mexico on October 28, 2021
    Verified Purchase
    Este libro es una muy buena referencia sobre geometría proyectiva aplicada a visión por computadora. Es una base sólida para la visión multilocular. Esta literatura abarca tópicos desde los principios de geométrica proyectiva, modelo de cámara pinhole, modelo de sistemas estéreo, rectificación de imagen, tensores triloculares, métodos de reconstrucción tridimensional entre otros. Este libro debe leerse cuidadosamente –detalladamente por no decir--, ya que el autor precisa en muchos detalles para los tópicos, y es fácil perderse si se omite algún de estos. En general, la teoría expuesta en mi experiencia es replicable y experimentable (por ejemplo métodos de triangulación y calibración de dispositivos pinhole) además, este libro contiene algunos métodos matemáticos conocidos sintetizados de manera ecuánime en los apéndices. Sin duda recomendado ampliamente.
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    Claudia Ramírez
    5.0 out of 5 stars
    Este libro "is a must" sí investiga sobre vision por computadora, particularmente multiocular.

    Reviewed in Mexico on October 28, 2021
    Este libro es una muy buena referencia sobre geometría proyectiva aplicada a visión por computadora. Es una base sólida para la visión multilocular. Esta literatura abarca tópicos desde los principios de geométrica proyectiva, modelo de cámara pinhole, modelo de sistemas estéreo, rectificación de imagen, tensores triloculares, métodos de reconstrucción tridimensional entre otros. Este libro debe leerse cuidadosamente –detalladamente por no decir--, ya que el autor precisa en muchos detalles para los tópicos, y es fácil perderse si se omite algún de estos. En general, la teoría expuesta en mi experiencia es replicable y experimentable (por ejemplo métodos de triangulación y calibración de dispositivos pinhole) además, este libro contiene algunos métodos matemáticos conocidos sintetizados de manera ecuánime en los apéndices. Sin duda recomendado ampliamente.
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  • AmazonKunde
    5.0 out of 5 stars 3D Computer Vision - leichter zu verstehen als erwartet
    Reviewed in Germany on August 7, 2012
    Verified Purchase
    Das Buch habe ich als Begleitwerk für eine Vorlesung gekauft.

    Das Buch ist sehr verständlich geschrieben und hat mir sehr gut geholfen Vieles zu verstehen, was in der Vorlesung nicht sehr ausführlich erklärt wurde. Im Endeffekt hat der Prof aus diesem Buch einfach abgeschrieben. In seinen Folien hat er aber nur die Grundaussagen mit ein paar Stichworten benutzt.

    Man braucht schon bestimmte Grundkentnisse in Mathematik, um dem Autor folgen zu können, vor allem in der analytischen Geometrie und der linearen Algebra. Solche Themen wie Vektoren, Matrizen, Geraden, Ebenen, lineare Abbildungen müssen bekannt sein. Wenn man diese Themen nicht kann, wird man NICHTS verstehen und sollte das Buch nicht kaufen.

    Das Buch ist zwar in English, was auf einige (wie mich) zuerst abschreckend wirkt (weil der Inhalt auch nicht gerade trivial ist), die Sprache hat aber eine gewisse Leichtigkeit, der Satzaufbau ist einfach (paar Wörter müsste ich natürlich nachschlagen). Im Prinzip ist das fast das gleiche Vokabular, was man für ein Mathebuch braucht.
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  • Gaia
    5.0 out of 5 stars perfect conditions
    Reviewed in Italy on May 7, 2024
    Verified Purchase
    Perfect conditions and fast delivery. Recommended
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