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Multiple View Geometry in Computer Vision [Format Kindle]

Richard Hartley , Andrew Zisserman

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Descriptions du produit

Revue de presse

'I am very positive about this book. 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.' Computing Reviews

'… a book which is timely, extremely thorough and commendably clear … Overall, the approach is masterly … The authors have managed to present the very essence of the subject in a way which the most subtle ideas seem natural and straightforward. I have never seen such a clear exploration of the geometry of vision. I would wholeheartedly recommend this book. It deserves to be in the library of every serious researcher in the field of computer vision.' Journal of Robotica

'The new edition features an extended introduction covering the key ideas in the book (which itself have 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.' Zentralblatt MATH

Présentation de l'éditeur

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.

Détails sur le produit

  • Format : Format Kindle
  • Taille du fichier : 31711 KB
  • Nombre de pages de l'édition imprimée : 672 pages
  • Utilisation simultanée de l'appareil : Jusqu'à 4 appareils simultanés, selon les limites de l'éditeur
  • Editeur : Cambridge University Press; Édition : 2 (25 mars 2004)
  • Vendu par : Amazon Media EU S.à r.l.
  • Langue : Anglais
  • ASIN: B00AKE1QK4
  • Synthèse vocale : Activée
  • X-Ray :
  • Word Wise: Non activé
  • Composition améliorée: Activé
  • Classement des meilleures ventes d'Amazon: n°645.076 dans la Boutique Kindle (Voir le Top 100 dans la Boutique Kindle)

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Amazon.com: 4.5 étoiles sur 5  25 commentaires
23 internautes sur 23 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Good on the explanations of the theory 26 avril 2009
Par calvinnme - Publié sur Amazon.com
Format:Broché|Achat vérifié
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.
15 internautes sur 18 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 A must for readers in computer vision 11 janvier 2001
Par Un client - Publié sur Amazon.com
Format:Relié
It is the best book in this area that I have seen up to now. It is well-organized and all the notations and words are friendly to beginners and even experts in this field. Included materials are really tracing the latest advanced techniques. Actually, it is great that there are a lot of exercises at the ends of each chapters but there is no sufficient solutions or detail explanations to each questions.
10 internautes sur 12 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Comment on the first edition 3 janvier 2004
Par Un client - Publié sur Amazon.com
Format:Broché|Achat vérifié
The first edition of this book could have been much better written. It took up a lot of topics, but treated each in a summary fashion. In fairness, though, I must say that this may be as good as any other book with its aim and scope, and better than some. Any writer on computer vision faces the problem of guessing who the reader is likely to be and what the reader's background is. Also, each of the various topics really merits a sizable book. In particular, the mathematics needs a truly mathematical treatment in a separate book. I have not seen this second edition, but there was room for improvement over the first edition.
3 internautes sur 3 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Good book, but.... 21 juillet 2010
Par A. Nagy - Publié sur Amazon.com
Format:Broché
Great book in this subject. The good things are...
- Clear theoritical introduction which many books miss to add
- Great appendixes about some mathematical theories necessary to understand this book
- Great organizaion of book chapters and coherent topics for each
- Bonus: Chapters for estimating hemographies and the math behind that
I cannot see any cons of the boox except that there is no clear road map to go into specific topic. For example, I am interested in multiple view geometry only (Trifocal tensor and above), I cannot figure out what I should read and what I can skip. I have to figure my way through.
After all, the best in the subject. Recommended.
4 internautes sur 5 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 The bible for 3D surface reconstruction from 2D images 20 septembre 2012
Par Homer - Publié sur Amazon.com
Format:Broché
This book should be considered as the essentially the bible for anybody working on the 3D surface reconstruction from 2D images. After I read through the book for the first time 5 years ago, I have revisit some chapters numerous times and each time I had a more deeper understanding on this particular topic.

When I began working on 3D surface reconstruction 5 years ago, I had close to zero background on stereophotogrammetry, or even in projective geometry, however I had good background in linear algebra, image processing using matlab, and Engineering. It was painful to read through the book the first time because 1) I had very little background of the particular topic, 2) like one of the other reviewer said: " this book just seems more focused on providing complete proofs than giving you a feel for how you would approach a real problem". But later on when I had more deeper knowledge of this research field, I have to disagree with that comments. There are significant amount of algorithms presented in this book. When I finished reading the book the first time, I was frustrated because I am not very clear on where is a practical solution for the problem. Then I read some other books such as Introductory Techniques for 3-D Computer Vision. That book is a good start and did help me making a better understanding of the 3D surface reconstruction techniques. But it doesn't cover the research topic thoroughly like Hartley and Zisserman's book on stereophotogrammetry. It is very important to follow through the proofs to obtain a clear picture of solving problems and implementing algorithms presented in Hartley and Zisserman's book.

And this book provides clear and easily implemented algorithms in both matlab and C++ (with help from open source libraries such as openCV).
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