Overview

Content-Based Image And Video Retrieval addresses the basic concepts and techniques for designing content-based image and video retrieval systems. It also discusses a variety of design choices for the key components of these systems. This book gives a comprehensive survey of the content-based image retrieval systems, including several content-based video retrieval systems. The survey includes both research and commercial content-based retrieval systems. Content-Based Image And Video Retrieval includes pointers to two hundred representative bibliographic references on this field, ranging from survey papers to descriptions of recent work in the area, entire books and more than seventy websites. Finally, the book presents a detailed case study of designing MUSE–a content-based image retrieval system developed at Florida Atlantic University in Boca Raton, Florida.

Full Product Details

Author:   Oge Marques ,  Borko Furht
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 2002
Volume:   21
Dimensions:   Width: 15.50cm , Height: 1.10cm , Length: 23.50cm
Weight:   0.314kg
ISBN:  

9781461353386

ISBN 10:   1461353386
Pages:   182
Publication Date:   09 November 2012
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1. Introduction.- 2. Fundamentals of Content-Based Image and Video Retrieval.- 1. Basic Concepts.- 2. A Typical CBIVR System Architecture.- 3. The User’s Perspective.- 4. Summary.- 3. Designing a Content-Based Image Retrieval System.- 1. Feature Extraction and Representation.- 2. Similarity Measurements.- 3. Dimension Reduction and High-dimensional Indexing.- 4. Clustering.- 5. The Semantic Gap.- 6. Learning.- 7. Relevance Feedback (RF).- 8. Benchmarking CBVIR Solutions.- 9. Design Questions.- 10. Summary.- 4. Designing a Content-Based Video Retrieval System.- 1. The Problem.- 2. The Solution.- 3. Video Parsing.- 4. Video Abstraction and Summarization.- 5. Video Content Representation, Indexing, and Retrieval.- 6. Video Browsing Schemes.- 7. Examples of Video Retrieval Systems.- 8. Summary.- 5. A Survey of Content-Based Image Retrieval Systems.- 1. Introduction.- 2. Criteria.- 3. Systems.- 4. Summary and Conclusions.- 6. Case Study: Muse.- 1. Overview of the System.- 2. The User’s Perspective.- 3. The RF Mode.- 4. The RFC Mode.- 5. Experiments and Results.- 6. Summary.- 7. Future Work.- References.

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