Multimedia Database Retrieval: A Human-Centered Approach

• Κύριοι συγγραφείς: Muneesawang, Paisarn (Συγγραφέας), Guan, Ling (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Boston, MA : Springer US, 2006.
• Σειρά: Signals and Communication Technology,
• Θέματα: Computer science.; Information storage and retrieval.; Multimedia information systems.; Image processing.; Electrical engineering.; Computer Science.; Multimedia Information Systems.; Signal, Image and Speech Processing.; Image Processing and Computer Vision.; Information Storage and Retrieval.; Electrical Engineering.

 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. 

 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.