Paisarn Muneesawang, Ling Guan

Multimedia Database Retrieval:

A Human-Centered Approach

• Broschiertes Buch

Produktbeschreibung

Multimedia Database Retrieval: A Human-Centered Approach presents the
latest development in user-centered methods and the state-of-the-art in
visual media retrieval. It includes discussion on perceptually inspired
non-linear paradigm in user-controlled interactive retrieval (UCIR)
systems. It also features a coherent approach which focuses on specific topics
within content/concept-based retrievals via audio-visual information modeling
of multimedia.

Highlights include:

_ Exploring an adaptive machine that can learn from its
environment

_ Optimizing the learning system by incorporating self-organizing
adaptation into the retrieval process

_ Demonstrating state-of-the-art applications within small,
medium, and large databases

The authors also include applications related to Digital Asset
Management (DAM), Computer Aided Referral (CAR) System, Geographical
Database Retrieval, retrieval of Art Documents, and Films and Video
Retrieval.

Multimedia Database Retrieval: A Human-Centered Approach presents the
fundamental and advanced aspects of these topics, as well as the
philosophical directions in the field. The methods detailed in this
book possess broad applications which will advance the technology in
this fast developing topical area.

Produktdetails

• Signals and Communication Technology
• Verlag: Springer / Springer US / Springer, Berlin
• Artikelnr. des Verlages: 978-1-4419-3815-2
• Softcover reprint of hardcover 1st ed. 2006
• Seitenzahl: 196
• Erscheinungstermin: 25. November 2010
• Englisch
• Abmessung: 229mm x 152mm x 11mm
• Gewicht: 305g
• ISBN-13: 9781441938152
• ISBN-10: 144193815X
• Artikelnr.: 32109439

Inhaltsangabe

Interactive Content-based Image Retrieval.- High Performance Retrieval: A New Machine Learning Approach.- Automatic Relevance Feedback.- Automatic Retrieval on P2P Network and Knowledge-based Databases.- Adaptive Video Indexing and Retrieval.- Movie Retrieval Using Audio-visual Fusion.

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Interactive Content-based Image Retrieval.- High Performance Retrieval: A New Machine Learning Approach.- Automatic Relevance Feedback.- Automatic Retrieval on P2P Network and Knowledge-based Databases.- Adaptive Video Indexing and Retrieval.- Movie Retrieval Using Audio-visual Fusion.