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.

Only up-to-date textbook for multimedia information retrieval Complete coverage of all media types Solid mathematical foundations combined with application relevance Detailed suggestions for further reading Additional teaching material available online Includes supplementary material: sn.pub/extras

Inhalt
Languages for Metadata.- Pattern Recognition for Multimedia Content Analysis.- Searching for Text Documents.- Image Processing.- Generative Probabilistic Models.- Speech Indexing.- Semantic Video Indexing.- A Spatio-Temporal and a Probabilistic Approach for Video Retrieval.- Multimodal Content-based Video Retrieval.- Interaction.- Digital Rights Management.- Evaluation of Multimedia Retrieval Systems.