As the size of multimedia databases grows, retrieval becomes a key challenge in multimedia database management. Accordingly, it is necessary to apply machine learning techniques to automatically tune the mechanism of multimedia retrieval systems.

Machine Learning Techniques for Adaptive Multimedia Retrieval: Technologies Applications and Perspectives disseminates current information on multimedia retrieval, advances the field of multimedia databases, and educates the multimedia database community. It is a critical text for professionals who are engaged in efforts to understand machine learning techniques for adaptive multimedia retrieval research, design and applications.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

Artificial Intelligence in Multimedia Databases Technologies
Content Processing, Analysis, Extraction, Synthesis, and Representation
Indexing, Searching, Retrieving, Querying, and Archiving Multimedia Databases
Metadata Generation, Coding and Transformation
Multimedia Database Integration and Query Languages
Multimedia for Interactive Services
Multimedia Security, Modeling, Coding, and Compression
Semantic Web and Ontology
Sequence Database Techniques, Indexing, and Approximate Matching
User Interaction and Relevance Feedback

Reviews & Statements

This book focuses on theories, methods, algorithms, and applications multimedia retrieval using machine learning techniques. The mission of this book is to disseminate state-of-the-art multimedia retrieval, advance the field of multimedia databases, and educate the multimedia database community. The individual chapters are contributed by different authors and present various solutions to the different kinds of problems concerning machine learning for multimedia retrieval. The prospective audience of the proposed book would be academics, scientists, practitioners and engineers who are engaged in efforts to understand the state of the art in multimedia retrieval research, design and applications. This book can also be used as a supplement in multimedia related courses for lecturers, upper-level undergraduates and graduate students. Moreover, fellow researchers and PhD students intending to broaden their scope or looking for a research topic in multimedia retrieval may find the book inspiring.

– Chia-Hung Wei, Ching Yun University, Taiwan; and Yue Li, Nankai University, China

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Editor/Author Biographies

Chia-Hung Wei is currently an assistant professor of the Department of Information Management at Ching Yun University, Taiwan. He obtained his Ph.D. degree in Computer Science from the University of Warwick, UK, and Master's degree from the University of Sheffield, UK, and Bachelor degree from the Tunghai University, Taiwan. His research interests include content-based image retrieval, digital image processing, medical image processing and analysis, machine learning for multimedia applications and information retrieval. He has published over 10 research papers in those research areas.

Yue Li received his Ph.D. degree in computer science from University of Warwick, UK, in 2009, M.S. in Information Technology from Department of Computer Science, University of Nottingham, UK, in 2005, and B.Sc. in Mathematics from Nankai University, China, in 2003. He is currently an assistant professor of Collage of Software, University of Nankai, China. He serves as a member of editorial review board of International Journal of Digital Crime and Forensics. His research interests include digital forensics, multimedia security, digital watermarking, pattern recognition, machine learning and content-based image retrieval.

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Editorial Advisory Board

Qi Tian, University of Texas at San Antonio, USA
Alan Hanjalic, Delft University of Technology, The Netherlands
Stefano Berretti, University of Florence, Italy
Marcel Worring, University of Amsterdam, The Netherlands
George Ioannidis, University of Bremen, Germany
Mei-Ling Shyu, University of Miami, USA
Shu-Ching Chen, Florida International University, USA
Yixin Chen, University of Mississippi, USA
Min Chen, University of Montana, Missoula, USA
Qiang Cheng, Southern Illinois University, USA
Clement Leung, Victoria University, Australia
Remco Veltkamp, Utrecht University, The Netherlands
Xin-Jing Wang, Microsoft Research Asia
Mohan S Kankanhalli, National University of Singapore, Singapore
Jianping Fan, The University of North Carolina at Charlotte, USA
Zhongfei Zhang, State University of New York (SUNY) at Binghamton, USA
Man-Kwan Shan, National Chengchi University, Taiwan
Bill Grosky, University of Michigan – Dearborn, USA