Content-Based Image and Video Retrieval

Softcover Nachdruck of the original 1. Auflage 2002
ISBN: 978-1-4613-5338-6
Verlag: Springer US

Buch, Englisch, Band 21, 182 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 312 g

Reihe: Multimedia Systems and Applications

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.

Zielgruppe

Research

Autoren/Hrsg.

Furht, Borko

Marques, Oge

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Warehouse
• Mathematik | Informatik EDV | Informatik Professionelle Anwendung
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Information Retrieval

Inhaltsverzeichnis

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.