- Hardcover: 792 pages
- Publisher: Pearson; 2 edition (November 5, 2011)
- Language: English
- ISBN-10: 013608592X
- ISBN-13: 978-0136085928
- Product Dimensions: 8.2 x 1.8 x 10.1 inches
- Shipping Weight: 3 pounds (View shipping rates and policies)
- Average Customer Review: 29 customer reviews
Amazon Best Sellers Rank:
#803,222 in Books (See Top 100 in Books)
- #152 in Books > Computers & Technology > Computer Science > AI & Machine Learning > Computer Vision & Pattern Recognition
- #256 in Books > Textbooks > Computer Science > Artificial Intelligence
- #678 in Books > Computers & Technology > Computer Science > AI & Machine Learning > Intelligence & Semantics
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Computer Vision: A Modern Approach (2nd Edition) 2nd Edition
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From the Publisher
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. KEY TOPICS: Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. MARKET: Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise. --This text refers to an out of print or unavailable edition of this title.
From the Back Cover
A Modern Approach
This extraordinary book gives a uniquely modern view of computer vision. Offering a general survey of the whole computer vision enterprise along with sufficient detail for readers to be able to build useful applications, this book is invaluable in providing a strategic overview of computer vision. With extensive use of probabalistic methods topics have been selected for their importance, both practically and theoreticallythe book gives the most coherent possible synthesis of current views, emphasizing techniques that have been successful in building applications. Readers engaged in computer graphics, robotics, image processing, and imaging in general will find this text an informative reference.
- Application SurveysNumerous examples, including Image Based Rendering and Digital Libraries
- Boxed AlgorithmsKey algorithms broken out and illustrated in pseudo code
- Self-ContainedNo need for other references
- Extensive, Detailed IllustrationsExamples of inputs and outputs for current methods
- Programming Assignments50 programming assignments and 150 exercises
Top customer reviews
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In general, the book tends to run both hot and cold. Clearly the authors are deeply knowledgeable about the subject. And there are many good sections of the book that do reasonable job of explaining the concepts. It is the sections that dive into the math where the authors tend to undermine their own hard work and that, I believe, are source of a number of the book's poor reviews.
One of the topics of the book is the classification (of images), so in keeping with this let me attempt to classify this book. This book seems to fall into the category of a book written by really smart people that loses more than it has to when read by a not-so-smart person. Said differently, this is probably a great book for those that already know the subject and the math. That is, the book can be quite readable for a few paragraphs and give the reader some intuition for the topic. However, when the book dives into the math for a few paragraphs and then emerges on the far shore, it has probably abandoned most readers. Certainly, more often than not it has abandoned me and, from the reviews, I believe that I am not the only one. I suspect the authors have majors in math, but perhaps they have been swimming in the math for so long that it has become comfortable. Whatever the reason, the authors do a poor job in setting up the math, are too dependent on concise math notation (again which would be well know to a math major but not necessarily by others) and as the math discussion progresses the authors make among the largest leaps mathematically among any textbook that I can recall. Additionally, the sections that discuss the math seem to be of varying quality. Often I would get the sense that what made it to final print were a set of notes or a rough draft that had not yet been completed let alone edited.
Regarding the poor setup and excessive brevity in a passage I just read, the authors describe an equation as having three terms, then they give the equation and never state which term is which. As the math unfolds, the reader is stuck because, although he can read the transformations relating to (for example) the rho term he does not know which term is represented by rho. The author also at points use what I find to be a somewhat odd notation (e.g., for linear algebra). In general a few examples would go a long way as well. The authors attempts at homogeneous coordinates and scale rotate and translate was awful and awfully short. A book that I have on motion in robotics spends perhaps 5 times as many pages to discuss a similar topic, with more examples and less dense notation, with the upshot being that the reader of the robotics book walks away having learned the concept and the Computer Vision reader walks away confused and having learned little (again, a math major might have been able to track better with the CV book and gotten a little more).
Were the authors to read this critique, they might counter that they were trying limit the math and instead to provide narratives that provide for an intuitive understanding of the subject. This would be a fair point and a worthy goal. When writing a book, the author must decide who his intended audience is; e.g., an undergraduate engineering student, a graduate student, academic colleagues, etc. However, if this was their intent then the approach the authors took was not unlike trying to meet a page count by removing every third word from the draft text.
In short, of what I have read so far, this book can only be followed without great struggle by those already familiar with the subject and the math. It has lots of potential, so I hope that the authors take the criticism in the constructive spirit in which it is offered with the result being a still better third edition.
Forsyth and Ponce do not provide the necessary qualitative and intuitive descriptions of the various concepts prior to engaging in the rigorous mathematics. Moreover, they simply do a shabby job of explaining some rather simple concepts in mathematics and their application to Vision. They babble on and on about very simple concepts, over complexifying them, and then spend too little time giving intuitive overviews.
The 5 star reviews are written by the authors and/or publishers. No self respecting PhD student, Masters student, or teacher, other than the author, would ever endorse this collossal waste of money. My own Vision professor said the only reason he has it up there is because there isn't an alternative.
When receiving a poor review, authors typically respond with, "well, you need to have such and such a basis before appreciating the book". This is basically, self-admitted failure. Granted, a book like this should not go into the depths of linear algebra, and should fairly assume some basic requisities. However THIS book just flat out fails as a TEXT-BOOK. As a book to teach students computer vision, it is just horrible. Not much more needs to be said. The authors cannot clearly, logically, and intuitively explain concepts. Its as simple as that. Has nothing to do with the intelligence of the reader.
A certain well known professor in Vision called it, and I quote, "utter garbage as a student text".