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Computer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles. 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 Incorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented reality Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects Includes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decade Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and software 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. Review: Physical book is worth it. Quality materials used. - This book is great. Excellent treatment of computer vision contained within. This is really a great resource. Got it for a computer vision class. I ended up referencing for two other classes. The page quality is excellent and thick and lends itself to showing images on the page without transparency. The book is heavy. Don't drop this book because the binding won't hold up to the shear mass of the pages. Mine fell off my bed. I was nearly in tears. The binding held on... but it ripped up a bit from the hard cover. My fault. Excellent value imo. Review: Came hardcover as announced - 8 lb parcel
| Best Sellers Rank | #269,972 in Books ( See Top 100 in Books ) #23 in Computer Networks #24 in Computer Vision & Pattern Recognition #448 in Artificial Intelligence & Semantics |
| Customer Reviews | 4.4 out of 5 stars 97 Reviews |
D**.
Physical book is worth it. Quality materials used.
This book is great. Excellent treatment of computer vision contained within. This is really a great resource. Got it for a computer vision class. I ended up referencing for two other classes. The page quality is excellent and thick and lends itself to showing images on the page without transparency. The book is heavy. Don't drop this book because the binding won't hold up to the shear mass of the pages. Mine fell off my bed. I was nearly in tears. The binding held on... but it ripped up a bit from the hard cover. My fault. Excellent value imo.
C**R
Came hardcover as announced
8 lb parcel
K**R
My review
This book is the benefit for explanation of whole computer vision. so this book has a lot of example. but a chapter cover some different book shortly.
A**N
Just buy it!
The print quality is exceptional - I really wasn't expecting that. The topics look great. The notation is typical and should facilitate easy understanding of the concepts.
G**S
Comprehensive reference book for those already familiar with computer vision; NOT a textbook
This is a good book, and I would say an essential one to include in your library if you are a computer vision practitioner. But only if you think of it as a giant "survey paper" covering all of computer vision. It is NOT suitable as a textbook for those learning computer vision- much of the math is glossed over quickly, and for many fundamental algorithms you are referred to other papers and textbooks. This includes fundamental algorithms such as RANSAC, a fundamentally important one in computer vision, which is given an incomplete top-level summary (not enough to clarify what it is or enable one to attempt implementing it) and then referenced by several papers. It does have an extensive appendix section referencing numerous software packages and sample data sets that one can use to help learn the field. This is valuable. In short, this would be a good 3rd or 4th book to add to your CV library, but not your first! For this I rated it four stars above. If you are already a seasoned CV practitioner and want to round out your library, this book would be a 5-star investment.
J**O
Hardcover Exceptional Print Quality
Never saw similar reference books to be so high-quality print and yet below $100.
D**R
Obfuscated
This was a soup salad of new terminology. Geoffrey Barrows' review was on the money. It is more of a survey of current knowledge and not an instructional book on computer vision. I don't know why this book was assigned to our course. As I read though, I write down things I need to look up. It's a lot. The explanations are quite sparse. I would avoid this book if you're looking for a top-down explanation of computer vision material. If you already know this stuff, then this might work for you.
D**B
Bad sticker placement
Book came with a sticker on the front and when removed left a sticky spot. It's one thing if it's in the corner on the back but being on the front is gross. The content of the book itself is fine. Just the seller made a mistake.
T**A
Durable and colorful
The size of paper is almost A4, with this hard cover and color picture in the book. The paper is glossy
J**O
ótimo livro e capa dura
ótimo livro e capa dura
A**N
Very good book for comprehensive understanding of the topic
Good book. If you want to learn the subject, buy it. If you can go 900 pages without burning yourself out, you will not regret the purchase.
A**R
A Deniz
Thanks
E**A
Excepcional
Visão geral da Visão Computacional
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