Based on more than 10 years of teaching experience, Blanken and his coeditors have assembled all the topics that should be covered in advanced undergraduate or graduate courses on multimedia retrieval and multimedia databases. The single chapters of this textbook explain the general architecture of multimedia information retrieval systems and cover various metadata languages such as Dublin Core, RDF, or MPEG. They run through, among other subjects, pattern recognition through Markov models, unsupervised learning, and pattern clustering. They also delineate in detail various indexing approaches to audio and video streams; interaction and control; the protection of content and user privacy; and search effectiveness and efficiency. The authors emphasize high-level features and show how these are used in mathematical models to support the retrieval process. For each chapter, there's detail on further reading, and additional exercises and teaching material is available online.
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Retrieval of multimedia data is different from retrieval of structured data. A key problem in multimedia databases is search, and the proposed solutions to the problem of multimedia information retrieval span a rather wide spectrum of topics outside the traditional database area, ranging from information retrieval and human computer interaction to computer vision and pattern recognition. Based on more than 10 years of teaching experience, Blanken and his coeditors have assembled all the topics that should be covered in advanced undergraduate or graduate courses on multimedia retrieval and multimedia databases. The single chapters of this textbook explain the general architecture of multimedia information retrieval systems; various metadata languages like Dublin Core, RDF, or MPEG; pattern recognition through Markov models, unsupervised learning, and pattern clustering; various indexing approaches to audio and video streams; interaction and control; the protection of content and user privacy; and search effectiveness and efficiency. The authors emphasize high-level features and show how these features are used in mathematical models to support the retrieval process. For each chapter, there s detail on further reading, and additional exercises and teaching material is available online.
"Multimedia information retrieval has lacked a textbook as this one for many years. The editors realised this need ... they took over the task of compiling contributions from several researchers to create this textbook. Multimedia Retrieval is an inspiring collection of expertise that presents some of the state-of-the-art work done by researchers in The Netherlands. ... This is a unique textbook that gathers expertise valuable for any MSc student or PhD researching in the field of Multimedia Information Retrieval." --João Magalhães, Informer, Issue 27, Summer, 2008
"This book contains 13 chapters that discuss the different aspects of multimedia retrieval and is intended for masters-level students. I believe that it is a good effort and a useful resource for advanced undergraduates and early graduate students to begin their research journey. ... Overall, the book is well written. ... Readers can gain some breadth about the problems, approaches, and challenges in the multimedia analysis research domain. ... I believe that the book will be beneficial for multimedia-analysis-related university courses." --Dhiraj Joshi, Journal of Electronic Imaging, Vol. 17 (3), 2008
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