Introductory Techniques for 3-D Computer Vision

by Emanuele Trucco and Alessandro Verri

FEATURES: *Provides a guide to well-tested theory and algorithms including solutions of problems encountered in modern computer vision. *Contains many practical hints highlighted in the book.... This description may be from another edition of this product.

• Format: Paperback
• Language: English
• ISBN: 0132611082
• ISBN13: 9780132611084
• Release Date: January 1998
• Publisher: Prentice Hall
• Length: 343 Pages
• Weight: 1.66 lbs.
• Dimensions: 1.1" x 7.0" x 9.1"

Customer Reviews

Extra-ordinary book on Computer Vision!

I didn't know or hear about this book till one fine morning when I went to our IIT library looking for some good book on computer vision to supplement the knowledge imparted by Horn's book. I found this book and it contained most of the concepts covered thus far in my lectures. Still I was not convinced about the credibility of this book. Somehow, I started grazing through this book in leisure hours. To my surprise, I found that it was simply an amazing book written so skillfully on computer vision from the basics. The Math fundae in the appendix were the ones I read first. They were very concise and helped me to grasp the concepts quickly. The chapters were also based on recent literature and very much coherent and self-explanatory. This book has the potential to become a master-piece in computer vision. One unique feature of this book is the clear explanation of Math concepts in each chapter. For it to become more user-friendly, some real application oriented problems should be added. But, on the whole, this book is an excellent book to be read along with Horn's book to fully understand the basics of computer vision. I strongly recommend this book to any novice to computer vision with little understanding of image processing concepts.

Excellent intermediate textbook on Computer Vision

If you already understand image processing and the basics of computer vision, this book is a very good at concisely presenting more advanced algorithms to the reader. Also, because this book is so well organized, you can read it from beginning to end. Rest assured if you are looking at an algorithm on page 84, you will not need to skip ahead to later sections in the book to understand it. From the beginning, algorithms are named and presented in numbered steps for clarity of presentation. The book starts out with introductory material such as basic optics and the geometry of camera models. It continues with image denoising, as well as two full chapters devoted to image features and their detection. Finally, the more basic material concludes with a chapter on the mathematics of camera calibration. One aspect of vision that is often neglected in other computer vision books that is treated well here is that of motion. For those working in video processing, this might make this book a good selection. Also, the book gives one of the best discussions of eigenspaces that I have seen in print in chapter ten of the book, where the subject is recognition of 3D objects. I was able to code up the eigenfaces face recognition algorithm based almost entirely on the information found in chapter ten of this book. If you need an introduction to computer vision before tackling the more advanced material in this text, try Shapiro's book "Computer Vision" ISBN 0130307963. A good knowledge of linear algebra is necessary prior to understanding the algorithms in this book such as is found in Schaum's outline of Matrix Operations. Given the specific subject matter of this book, it would probably be an excellent choice for an engineer or scientist that is interested in computer vision as it relates to robotics.

The best textbook for computer vision

This is the best textbook for computer vision I've ever met. Compared with Forsyth and Ponce's heavy book titled with "computer vision: a modern approach", this book is very concise, precise, and suitable to be used in classes. Definitions are carefully given. Pseudocode is extremely helpful for practical use. Also some sections about mathematics are appreciated to understand the underlying algorithms. If you want to learn more or do research, then read Forsyth's book after finishing reading this book. Several my collegues think this book is the first choice for new comers in this field.

An instant classic

Every newcomer to the field of computer vision should own this book. With a well organized blend of theory and algorithms, this text clearly and (as important) succinctly introduces the key elements of computer vision. This text has the best introduction to epipolar geometry that I've seen. For a reference, it's very thin. However, for an introductory text, it is hard for me to imagine a much better one. I am not aware of any book that is even comparable.

Such a great book for novice in computer vision !!!

It's a pretty good reference for the one who want to start in computer vision ,espectially in stereo graphic field. With its comprehensive explanation and well oganization,it should be the first book in your computer vision bookshelf.