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An Invitation to 3-D Vision: From Images to Geometric Models (Interdisciplinary Applied Mathematics) Hardcover – June 17, 2005

ISBN-13: 978-0387008936 ISBN-10: 0387008934 Edition: 1St Edition

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An Invitation to 3-D Vision: From Images to Geometric Models (Interdisciplinary Applied Mathematics) + Multiple View Geometry in Computer Vision + Computer Vision: Algorithms and Applications (Texts in Computer Science)
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Product Details

  • Series: Interdisciplinary Applied Mathematics (Book 26)
  • Hardcover: 528 pages
  • Publisher: Springer; 1St Edition edition (June 17, 2005)
  • Language: English
  • ISBN-10: 0387008934
  • ISBN-13: 978-0387008936
  • Product Dimensions: 6.1 x 1.2 x 9.2 inches
  • Shipping Weight: 2 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (7 customer reviews)
  • Amazon Best Sellers Rank: #1,265,127 in Books (See Top 100 in Books)

Editorial Reviews

Review

From the reviews:

"Computer vision is invading our daily lives … . Covering all the aspects would be too vast an area to cover in one book, so here, the authors concentrated on the specific goal of recovering the geometry of a 3D object … . The 22 pages of references form a good guide to the literature. The authors found an excellent balance between a thorough mathematical treatment and the applications themselves. … the text will be a pleasure to read for students … ." (Adhemar Bultheel, Bulletin of the Belgian Mathematical Society, Vol. 12 (2), 2005)

"This is primarily a textbook of core principles, taking the reader from the most basic concepts of machine vision … to detailed applications, such as autonomous vehicle navigation. … It is a clearly written book … . Everything that is required is introduced … . an entirely self-contained work. … The book is aimed at graduate or advanced undergraduate students in electrical engineering, computer science, applied mathematics, or indeed anyone interested in machine vision … . is highly recommended." (D.E. Holmgren, The Photogrammetric Record, 2004)

"This very interesting book is a great book teaching how to go from two-dimensional (2D)-images to three-dimensional (3D)-models of the geometry of a scene. … A good part of this book develops the foundations of an appropriate mathematical approach necessary for solving those difficult problems. … Exercises (drill exercises, advanced exercises and programming exercises) are provided at the end of each chapter." (Hans-Dietrich Hecker, Zentralblatt MATH, Vol. 1043 (18), 2004)

"This book gives senior undergraduate and beginning graduate students and researchers in computer vision, applied mathematics, computer graphics, and robotics a self-contained introduction to the geometry of 3D vision. That is the reconstruction of 3D models of objects from a collection of 2D images. … Exercises are provided at the end of each chapter. Software for examples and algorithms are available on the author’s website." (Daniel Leitner, Simulation News Europe, Vol. 16 (1), 2006)

From the Back Cover

Endowing machines with a sense of vision has been a dream of scientists and engineers alike for over half a century. Only in the past decade, however, has the geometry of vision been understood to the point where this dream becomes attainable, thanks also to the remarkable progress in imaging and computing hardware.

This book addresses a central problem in computer vision -- how to recover 3-D structure and motion from a collection of 2-D images -- using techniques drawn mainly from linear algebra and matrix theory. The stress is on developing a unified framework for studying the geometry of multiple images of a 3-D scene and reconstructing geometric models from those images. The book also covers relevant aspects of image formation, basic image processing, and feature extraction. The authors bridge the gap between theory and practice by providing step-by-step instructions for the implementation of working vision algorithms and systems.

Written primarily as a textbook, the aim of this book is to give senior undergraduate and beginning graduate students in computer vision, robotics, and computer graphics a solid theoretical and algorithmic foundation for future research in this burgeoning field. It is entirely self-contained with necessary background material covered in the beginning chapters and appendices, and plenty of exercises, examples, and illustrations given throughout the text.

Customer Reviews

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See all 7 customer reviews
This book gives a very nice treatment of these subjects.
S. Billings
I am saying that as a PhD in applied mathematics who knows very well the math in the book.
Oleg Alexandrov
We used this book at Duke University for our graduate course in 3D reconstruction.
Charlie

Most Helpful Customer Reviews

19 of 20 people found the following review helpful By A Customer on March 29, 2004
Format: Hardcover
The authors do an outstanding job of balancing theory and practice in this book. In particular, Ch. 11 (Step-by-Step Building of a 3-D Model from Images) is a gem. The new student of computer vision that finds Structure from Motion (SFM) daunting should read this chapter first to build motivation by means of seeing concrete examples.
What's most notable about this book is its thoroughness. The authors humbly get their hands dirty with crucial low-level matters like interest point detection and feature tracking. In Ch. 5 and 6 (calibrated and uncalibrated reconstruction) you'll get an excellent treatment of the necessary background in these areas, along with numerous new insights and `nuggets.' This is particularly true in their treatment of homographies. Ch. 2 has all the material on rigid body motion and the exponential map that students used to need to get from Murray, Li and Sastry, once again with substantial added value.
The exercises in all the chapters are very well thought out, and they -- together with the clearly written Algorithm Boxes -- greatly simplify the job of the instructor. (I am currently using this as the text for my graduate level class this quarter.) The appendices (especially the one on Linear Algebra) also help to make this a self-contained resource for SFM.
I haven't gotten into the material on multi-body motion and n>2 views, so I can't comment on those parts(...)In summary, this is a great book, well worth the money.
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8 of 9 people found the following review helpful By calvinnme HALL OF FAMETOP 1000 REVIEWERVINE VOICE on December 9, 2005
Format: Hardcover
I really liked this book. However, I use it for vision issues as they relate to robotics rather than as an introductory text on 3D vision. If a general or introductory textbook on 3D computer vision is what you desire, then you might be better off with "Multiple View Geometry in Computer Vision" by Hartley or my personal favorite, "Introductory Techniques for 3-D Computer Vision" by Trucco and Verri. For individuals studying robotic vision, many parts of this book are useful not only for characterizing vision, but for putting together algorithms and equations that are useful for describing robotic motion in general. For example, chapter two of the book collects equations and algorithms that are very useful in describing forward kinematics. Chapters five through ten cover all of the considerations and algorithms needed to produce a 3D image from a collection of images taken from different viewpoints. Chapter eleven applies this knowledge with sequential instructions on building a 3D image from a group of images. Chapter twelve has a second application that shows how to perform autonomous control of a moving vehicle via video feedback. The appendices have some very good information on linear algebra as it relates to computer vision as well as details on the Kalman filter, which is also of great interest to those of us who are interested in computational robotics. Algorithms are blocked out and explained in logical steps throughout the book, and it also has very good exercises at the end of each chapter as well as short examples throughout each chapter, although the notation can sometimes be a little confusing.Read more ›
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6 of 8 people found the following review helpful By Oleg Alexandrov on November 15, 2009
Format: Hardcover
This book views the underlying mathematics as the purpose, and the subject of 3D vision as some application; that makes the book hard do read. I am saying that as a PhD in applied mathematics who knows very well the math in the book. The book can rant on and on with pagefuls of formulas and derivations before explaining in a technical language what that means for 3D vision, instead of stating what the problem is, making the case for what needs to be done, and then using the mathematics to get there.

This is a good reference book if you already know the subject and want to deepen your knowledge, rather than something you'd use as an entry point into the field of 3D vision.
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By Charlie on December 31, 2013
Format: Hardcover Verified Purchase
We used this book at Duke University for our graduate course in 3D reconstruction. It is well written, although sometimes the notation is flawed.
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