Principles of Visual Information Retrieval by Michael S. LewPrinciples of Visual Information Retrieval by Michael S. Lew

Principles of Visual Information Retrieval

byMichael S. Lew

Paperback | October 21, 2010

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Principles of Visual Information Retrieval introduces the basic concepts and techniques in VIR and develops a foundation that can be used for further research and study.
Divided into 2 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 context into the search process.
The second part looks at advanced topics such as multimedia query, specification, visual learning and semantics, and offers state-of-the-art coverage that is not available in any other book on the market.
This book will be essential reading for researchers in VIR, and for final year undergraduate and postgraduate students on courses such as Multimedia Information Retrieval, Multimedia Databases, Computer Vision and Pattern Recognition.
Title:Principles of Visual Information RetrievalFormat:PaperbackDimensions:356 pages, 22.9 × 15.2 × 1.73 inPublished:October 21, 2010Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:1849968683

ISBN - 13:9781849968683

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Table of Contents

I: Fundamental Principles.- 1. Visual Information Retrieval: Paradigms, Applications, and Research Issues.- 2. Color-Based Retrieval.- 3. Texture Features for Content-Based Retrieval.- 4. State of the Art in Shape Matching.- 5. Feature Similarity.- 6. Feature Selection and Visual Learning.- 7. Video Indexing and Understanding.- II: Advanced Topics.- 8. Query Languages for Multimedia Search.- 9. Relevance Feedback Techniques in Image Retrieval.- 10. Mix and Match Features in the ImageRover Search Engine.- 11. Integrating Analysis of Context and Image Content.- 12. Semantic-Based Retrieval of Visual Data.- 13. Trademark Image Retrieval.- Author Index.