---
product_id: 9090296
title: "Computer Vision: Algorithms and Applications (Texts in Computer Science)"
price: "₹ 3030"
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---

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

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## Description

Computer Vision: Algorithms and Applications (Texts in Computer Science): 9781848829343: Computer Science Books @ desertcart.com

Review: Top-Notch - 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.)
Review: he has managed to fit into 800 pages what it could easily have taken 2000 to explain in fine detail - 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.

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #1,734,721 in Books ( See Top 100 in Books ) #223 in Computer Graphics #593 in Graphics & Multimedia Programming #2,664 in Computer Graphics & Design |
| Customer Reviews | 4.3 4.3 out of 5 stars (102) |
| Dimensions  | 8.9 x 1.5 x 11.3 inches |
| Edition  | 2011th |
| ISBN-10  | 1848829345 |
| ISBN-13  | 978-1848829343 |
| Item Weight  | 5.4 pounds |
| Language  | English |
| Print length  | 832 pages |
| Publication date  | October 19, 2010 |
| Publisher  | Springer |

## Images

![Computer Vision: Algorithms and Applications (Texts in Computer Science) - Image 1](https://m.media-amazon.com/images/I/61tjbTJwL6L.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Top-Notch
*by B***T on November 29, 2011*

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.)

### ⭐⭐⭐⭐⭐ he has managed to fit into 800 pages what it could easily have taken 2000 to explain in fine detail
*by B***T on October 25, 2014*

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.

### ⭐⭐⭐⭐⭐ Realy good book.
*by F***N on December 27, 2012*

It's impossible to cover the whole topic in one book. This one has the main ideas, some explanations and examples, and a lot of external references. It's not an easy book (as I was hoping;)). You will need other sources to understand where the formulas came from, and what do they actually mean. As a result you will have a good understanding. It's better to start with this rather than with product oriented books (like OpenCV). These should go after, IMHO. PS: Author provides a free beta PDF (very smart idea), makes sense to check it first. I realized that was what I was looking for, and bot the book.

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*Last updated: 2026-04-25*