Principles of Visual Information Retrieval (Advances in Computer Vision and Pattern Recognition) [Hardcover]

Michael S. Lew (Editor)

Book Description

Series: Advances in Computer Vision and Pattern Recognition | Publication Date: February 23, 2001

This text introduces the basic concepts and techniques in VIR. In doing so, it develops a foundation for further research and study. Divided into two parts, the first part describes the fundamental principles. A chapter is devoted to each of the main features of VIR, such as colour, texture and shape-based search. There is coverage of search techniques for time-based image sequences or videos, and an overview of how to combine all the basic features described and integrate them into the search process. The second part looks at advanced topics such as multimedia query. This book is essential reading for researchers in VIR, and final-year undergraduate and postgraduate students on courses such as Multimedia Information Retrieval, Multimedia Databases, and others.

Product Details

• Hardcover: 376 pages
• Publisher: Springer; 1st Edition. edition (February 23, 2001)
• Language: English
• ISBN-10: 1852333812
• ISBN-13: 978-1852333812
• Product Dimensions: 9.3 x 6.3 x 0.9 inches
• Shipping Weight: 1.5 pounds (View shipping rates and policies)
• Average Customer Review: 3.2 out of 5 stars  See all reviews (4 customer reviews)
• Amazon Best Sellers Rank: #3,930,575 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

2 of 2 people found the following review helpful:

5.0 out of 5 stars Great for researchers, December 2, 2005

By 

H M "H M" (Calif, USA) - See all my reviews

This review is from: Principles of Visual Information Retrieval (Advances in Computer Vision and Pattern Recognition) (Hardcover)

As a researcher in multimedia search (at Google), I absolutely love this book! It abounds with tremendously useful information to computer vision and multimedia search developers such as the brilliant chapters on color, texture, shape, and similarity measures. These go far beyond any other books on the market now even though they were written in 2000. I read on the Amazon site some criticisms of this book but I suspect they were written by undergraduates - i.e. No PhD would criticize a work published in early 2001 for only having references from 2000.

My only criticism of this book is that the reader should have expertise in fundamentals of image processing or computer vision beforehand, know what a color space, texture, etc. Read the CV book by Ponce and Forsyth first.

5.0 out of 5 stars Excellent Review of State of the Art, July 18, 2002

By 

John Sinclair (London, UK) - See all my reviews

This review is from: Principles of Visual Information Retrieval (Advances in Computer Vision and Pattern Recognition) (Hardcover)

There are only two books which cover the new area
of visual information retrieval. One is by Alberto del Bimbo
and gives a good introduction to the subject. It is
written well, but leaves the reader wondering what the
state of the art is.

This book by Prof. Lew covers the state of the art in the
fundamentals of color, texture, shape, and video. Prof. Lew's
book has each fundamental area written by the leading
expert so the material is fresh and truly state of the art.
These experts include the leading researchers from MIT,
Boston University, Univ. of Illinois, etc.

This is the only choice for an advanced book on visual
information retrieval - one for graduate students or
leading edge developers.

- John

0 of 1 people found the following review helpful:

1.0 out of 5 stars Dry and Fragmented, May 1, 2005

By 

Alan Chen (United States) - See all my reviews

This review is from: Principles of Visual Information Retrieval (Advances in Computer Vision and Pattern Recognition) (Hardcover)

This book was quite a disappointment. The equations the author throws at the reader are extremely abstract and do not get elaborated. I don't think you will be able to implement any of these algorithms in a language like C++ because many details are missing. Most explanations are not self-contained; they usually go along the lines of "[author] uses this function to do blah blah..."