Principles of Visual Information Retrieval / Edition 1

Principles of Visual Information Retrieval / Edition 1

by Michael S. Lew, M. S. Lew
     
 

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

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Overview

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

ISBN-13:
9781852333812
Publisher:
Springer London
Publication date:
02/23/2001
Series:
Advances in Computer Vision and Pattern Recognition Series
Edition description:
2001
Pages:
356
Product dimensions:
9.21(w) x 6.14(h) x 0.94(d)

Table of Contents

Part I: Fundamental Principles: Visual Information Retrieval: Paradigms, Applications and Research Issues. Color Based Retrieval. Texture Features for Content Based Retrieval. State of the Art in Shape Matching. Feature Similarity. Feature Selection and Visual Learning. Video Indexing and Understanding.- Part II: Advanced Topics: Query Languages for Multimedia Search. Relevance Feedback Techniques in Image Retrieval. Mix and Match Features in the ImageRover Search Engine. Integrating Analysis of Context and Image Content. Semantic Based Retrieval of Visual Data. Trademark Image Retrieval.- Author Index.- Subject Index.

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