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Computer Vision: Algorithms and Applications (Texts in Computer Science) Hardcover


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Computer Vision: Algorithms and Applications (Texts in Computer Science) + Multiple View Geometry in Computer Vision + Computer Vision: Models, Learning, and Inference
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Product Details

  • Series: Texts in Computer Science
  • Hardcover: 833 pages
  • Publisher: Springer; 2011 edition (October 19, 2010)
  • Language: English
  • ISBN-10: 1848829345
  • ISBN-13: 978-1848829343
  • Product Dimensions: 3.2 x 4.4 x 0.6 inches
  • Shipping Weight: 5.2 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (13 customer reviews)
  • Amazon Best Sellers Rank: #100,500 in Books (See Top 100 in Books)

Editorial Reviews

Review

From the reviews:

“This large work by Szeliski (Microsoft Research), an experienced computer vision researcher and instructor, contains hundreds of glossy color photos that illustrate the variety of techniques used to analyze and interpret images. … It is suitable for teaching a senior-level undergraduate course in computer vision or graduate courses covering the more demanding material. Its primary use will be as a general reference to the fundamental techniques and recent research literature for graduate students, faculty/researchers, and professionals. Summing Up: Recommended. Upper-division undergraduates and above.” (C. Tappert, Choice, Vol. 48 (9), May, 2011)

“The aim of this book is to provide a course in computer vision for undergraduate students in computer science or electrical engineering. … The focus is on algorithms and applications. … The mathematics covered is nicely presented … . Each chapter contains exercises and references to additional reading. … The book also contains many references to resources on the Internet.” (Lisbeth Fajstrup, Zentralblatt MATH, Vol. 1219, 2011)

“The main interests of Richard Szeliski’s book is to give a … up-to-date overview of the state of the art. … a valuable resource for teaching computer vision at either the undergraduate or graduate level. … an interesting read for any student or engineer who wants a broad introduction to the field of computer vision. … From a teaching point of view, the book is a valuable resource, offering an extended list of exercises, project proposals, and appealing applications of computer vision techniques.” (Sebastien Lefevre, ACM Computing Reviews, July, 2011)

From the Back Cover

Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art?

Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos.

More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques

Topics and features:

  • Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses
  • Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects
  • Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory
  • Suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book
  • Supplies supplementary course material for students at the associated website, http://szeliski.org/Book/

Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

Dr. Richard Szeliski has more than 25 years’ experience in computer vision research, most notably at Digital Equipment Corporation and Microsoft Research. This text draws on that experience, as well as on computer vision courses he has taught at the University of Washington and Stanford.


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Customer Reviews

4.5 out of 5 stars
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If more details are needed one can check the specific cited papers.
Laura
This book is written to cover almost all state-of-the-art research areas in computer vision and provides a solid introduction and reference.
Shanmuganathan Raman
This is a comprehensive computer vision book and is definitely a good textbook.
David Tsai

Most Helpful Customer Reviews

23 of 23 people found the following review helpful By Eric Haines on February 25, 2012
Format: Hardcover
Here's a key fact: this book is free for download as an unprotected PDF from the author's site. So, go judge for yourself - Google the title, download, and it's yours.

Having helped write a similar book about interactive rendering ("Real-Time Rendering"), I understand the dilemma the author faces with this book: cover all the basics in depth (which other books do fine), or survey all the current literature, or some hybrid approach? Given that there are many books about the foundations of image processing and rendering, it's fine that the author chooses to go a more survey-oriented route, though there is some solid (albeit brief) coverage of the basics in the first few chapters.

What this means is that this is probably not the first book you want to read on the subject, unless you're made of sterner stuff than most. There are other books on the topic, go search them out. If you plan on doing any serious work in this area, this book will save you a huge amount of time understanding important trends and previous work in the field.
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26 of 28 people found the following review helpful By Shanmuganathan Raman on November 11, 2010
Format: Hardcover
I have been reading the drafts of this book posted on Richard Szeliski's website, [...] , for about an year now. This book is written to cover almost all state-of-the-art research areas in computer vision and provides a solid introduction and reference. Unlike other books on vision, this book is about applications. The chapters are arranged keeping in mind the different key research areas which should be learned by a computer vision student. Apart from providing an overview, every chapter has abundant key references which direct the student for in-depth understanding of a particular area. This book is a welcome addition as literary resource for the computer vision community. Even though Szeliski has kept the digital version freely accessible in his site, this book as a hardbound version with color figures is definitely indispensable for every computer vision student and researcher. After Horn's landmark book, this book is here to stay as the premier computer vision book for years to come. I have started recommending this book for all the undergraduate and graduate students in my lab and I am planning to order a hardbound version for my personal bookshelf.

I strongly recommend this book for every computer vision enthusiast and I definitely feel that this book has the best content to interest people working in different areas of computer vision either in industry or academia. This book is surely the best book to learn computer vision at this point of time.
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23 of 27 people found the following review helpful By ethan on February 4, 2012
Format: Hardcover
I am a new to the world of computer vision (but not to CS or math), and I hoped that this book would be a good way to get into the field. Unfortunately, this was not the case.

I only read the first 4 chapters and gave up, so things might be different later on, but the book read like a review article and not a text book. It seems like you get a long list of ideas and techniques, with very little explanations and a lot of referrals to articles where the real information is found. I do like when authors point out where to find all the information they did not have time to put in, but for me at least it felt like there was almost no substance to the book.
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9 of 10 people found the following review helpful By abliviax on April 6, 2011
Format: Hardcover Verified Purchase
Good overall -- Broad overview, sometimes fails to explain concepts in as much detail a new student might wish, reads like a literature survey in some places.
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2 of 2 people found the following review helpful By David Tsai on April 14, 2012
Format: Hardcover Verified Purchase
This is a comprehensive computer vision book and is definitely a good textbook. I used it to prepare my PhD qualifying exam and it went well. One negative comment is that the book focuses too much on the geometry stuff (nearly half of the book). However the computer vision community is developing as more machine-learning oriented.
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Format: Hardcover
I prefer an oldie but a goodie - Linda Shapiro's Computer Vision. Read this one for timely topics and big ideas. Read Shapiro's book on how it's actually done. I was really disappointed by this one on the algorithm front, especially since "Algorithms" is part of the title.
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1 of 1 people found the following review helpful By Brent Foust on November 28, 2011
Format: Hardcover Verified Purchase
A great introduction to Computer Vision, a nice review of the history of Computer Vision, and an enlightening survey of current and ongoing research.

Richard Szeliski is a great teacher, at the top of his game, who gives motivation for the problems we may need to solve using Computer Vision.

The algorithms are not provided as software code, but as descriptions with plenty of mathematical equations, references to papers, and copious diagrams and color photos.

An enjoyable read, there is something for everyone interested in Computer Vision in this book. But although it is very broad, packing 700 textbook-sized pages with information, it does not always go very deep. And there is no source code. So you're on your own if you want to turn the discussed algorithms into working code. It's apparently intended to be used as a textbook, as there are questions at the end of each section. So reading each of the relevant papers and producing working software algorithms is left up to the reader.

The example applications are motivating and there are a huge number of paper references (the footnotes section takes up 100 pages at the end of the book, just before the relatively-small 20-page index.)
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