Download Ebook Computer Vision: Algorithms and Applications (Texts in Computer Science)

Download Ebook Computer Vision: Algorithms and Applications (Texts in Computer Science)

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

Download Ebook Computer Vision: Algorithms and Applications (Texts in Computer Science)

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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)

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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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Product details

Series: Texts in Computer Science

Hardcover: 812 pages

Publisher: Springer; 2011 edition (November 24, 2010)

Language: English

ISBN-10: 1848829345

ISBN-13: 978-1848829343

Product Dimensions:

8.9 x 1.5 x 11.3 inches

Shipping Weight: 5.2 pounds (View shipping rates and policies)

Average Customer Review:

3.8 out of 5 stars

33 customer reviews

Amazon Best Sellers Rank:

#367,579 in Books (See Top 100 in Books)

The book acts as a good high level introduction to various significant sub-fields inside of computer vision. It is also one of the more up to date books (as of 2012) discussing more recent advances. However, because it is so high level and attempts to cover so much information, it is not a good book to try to learn from alone and provides no practical information on implementation details or problems. The best way to use the book, in my opinion, is to skim through it and learn the keywords to search for and use the references as a starting point. If you are a self learner like myself, one of the more frustrating problems is when you search for the wrong keywords and can't find the material.On the whole the writing quality is good in terms of clarity and insight. There are some spots that I felt that the book did little more than restate what was said by other authors of highly cited papers. While this is not always a bad thing, there were times that I disagreed with statements due to various practical considerations. Yes the original author was technically correct, but in the years since publication very few people actually do that since it's too computationally expensive or turned out to be less stable than advertised.The layout and organization of the book is well done and contains many full color pictures. For a new text book it is also very reasonably priced. I suspect that it would be more expensive to print the book's PDF out in color rather than buying it! I bought the book instead of just skimming through the older drafts (available online from the author's website) primarily because I prefer printed books and to support the authors publication approach.My rating is 4 stars based upon it being a high level introduction. As mentioned before, if you want a practical book that goes into how to implement all the techniques it discusses and issues that will arise, look elsewhere.

Good as a reference book, horrible if you actually intend to learn CV. It will point you in the right direction, and reference lots of external material and research papers, but you must be already familiarized with the algorithms it describes or you will learn as much CV as you would learn from a Shakespeare's book.Reference: *****Textbook: *

I'm returning to CV after a long absence, and this book is perfect for me. I've done three deep topic dives so far, and the book's coverage of each (with additional pointers into the literature) is spot on. The author has generously provided a PDF version online (search for the book title). Still, the physical version of the book is really nice, with large format pages on good paper. Since the book has already paid for itself in time savings, I'm happy to have made the purchase.

This book covers a lot of topics. It provides a brief explanation for each one, normally involving a lot of math, and occasionally an algorithm.Unfortunately, because the descriptions are so short and technical, nothing is ever really explained at an intuitive enough level to really grasp the concept. This part isn't great, but that seems to be pretty standard for most technical textbooks, and if you're using it for a course you generally have a teacher to explain the concept up front and then you can use the book to elaborate on it. Right?That's where this book fails. Not only does it not provide intuitive explanations, it doesn't cover any topic in enough depth to help with any written assignment or exam, and it fails completely to help with any programming assignments.It's a nice book - it's very well written and illustrated, it's just not that helpful. The one good part about it is that it does cover a very wide range of topics. Rather than taking notes externally I just wrote them down in the book in each of the appropriate sections - at least this way I can reference it again and get the intuition and depth I need from it.

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.)

For anyone looking for comprehensive coverage of all the fundamentals of computer vision, this is the book for you. The style of the book is that he gives you the general concept of a method and the required equations, and then provides you with the title of the paper it is sourced from (which are almost all available online as PDFs) in case you want more detail. Because of this approach, he has managed to fit into 800 pages what it could easily have taken 2000 to explain in fine detail.Don't take this as the book being too vague, because I have yet to need to refer to the papers to understand a concept (although it has been useful when I wanted more information into *how* the result was arrived at). It does help if you have a baseline understanding of how to do general operations on images (e.g. array manipulation in code) and whatnot, but a beginner could still use this book with a little more effort.There's no book that covers this breadth of information on computer vision, so I can't recommend it more highly.

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

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