Everything you ever wanted to know about multimedia retrieval and management. This comprehensive book offers a full picture of the cutting-edge technologies necessary for a profound introduction to the field. Leading experts also cover a broad range of practical applications.

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. 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.

Supporting users in their resource discovery mission when hunting for multimedia material is not a technological indexing problem alone. We look at interactiveways of engaging with repositories through browsing and relevance feedback, roping in geographical context, and providing visual summaries for videos. The book concludes with an overview of state-of-the-art research projects in the area of multimedia information retrieval, which gives an indication of the research and development trends and, thereby, a glimpse of the future world.

This comprehensive text/reference examines in depth the synergy between multimedia content analysis, personalization, and next-generation networking. The book demonstrates how this integration can result in robust, personalized services that provide users with an improved multimedia-centric quality of experience. Each chapter offers a practical step-by-step walkthrough for a variety of concepts, components and technologies relating to the development of applications and services. Topics and features: introduces the fundamentals of social media retrieval, presenting the most important areas of research in this domain; examines the important topic of multimedia tagging in social environments, including geo-tagging; discusses issues of personalization and privacy in social media; reviews advances in encoding, compression and network architectures for the exchange of social media information; describes a range of applications related to social media.

Multimedia data require specialised management techniques because the representations of colour, time, semantic concepts, and other underlying information can be drastically different from one another. This textbook on multimedia data management techniques gives a unified perspective on retrieval efficiency and effectiveness. It provides a comprehensive treatment, from basic to advanced concepts, that will be useful to readers of different levels, from advanced undergraduate and graduate students to researchers and to professionals. After introducing models for multimedia data (images, video, audio, text, and web) and for their features, such as colour, texture, shape, and time, the book presents data structures and algorithms that help store, index, cluster, classify, and access common data representations. The authors also introduce techniques, such as relevance feedback and collaborative filtering, for bridging the 'semantic gap' and present the applications of these to emerging topics, including web and social networking.

Content-based multimedia retrieval is a challenging research field with many unsolved problems. This monograph details concepts and algorithms for robust and efficient information retrieval of two different types of multimedia data: waveform-based music data and human motion data. It first examines several approaches in music information retrieval, in particular general strategies as well as efficient algorithms. The book then introduces a general and unified framework for motion analysis, retrieval, and classification, highlighting the design of suitable features, the notion of similarity used to compare data streams, and data organization.

Multimedia Information Retrieval: Content-Based Information Retrieval from Large Text and Audio Databases addresses the future need for sophisticated search techniques that will be required to find relevant information in large digital data repositories, such as digital libraries and other multimedia databases. Because of the dramatically increasing amount of multimedia data available, there is a growing need for new search techniques that provide not only fewer bits, but also the most relevant bits, to those searching for multimedia digital data. This book serves to bridge the gap between classic ranking of text documents and modern information retrieval where composite multimedia documents are searched for relevant information. Multimedia Information Retrieval: Content-Based Information Retrieval from Large Text and Audio Databases begins to pave the way for speech retrieval; only recently has the search for information in speech recordings become feasible. This book provides the necessary introduction to speech recognition while discussing probabilistic retrieval and text retrieval, key topics in classic information retrieval. The book then discusses speech retrieval, which is even more challenging than retrieving text documents because word boundaries are difficult to detect, and recognition errors affect the retrieval effectiveness. This book also addresses the problem of integrating information retrieval and database functions, since there is an increasing need for retrieving information from frequently changing data collections which are organized and managed by a database system. Multimedia Information Retrieval: Content-Based Information Retrieval from Large Text and Audio Databases serves as an excellent reference source and may be used as a text for advanced courses on the topic.

Several works on multimedia storage appear in literature today, but very little if any, have been devoted to handling long duration video retrieval, over large scale networks. Distributed retrieval of multimedia documents, especially the long duration documents, is an imperative step in rendering high-quality, high-fidelity, and cost-effective services for network service providers. Distributed Multimedia Retrieval Strategies for Large Scale Networked Systems presents an up-to-date research status in the domain of distributed video retrieval. This professional book will include several different techniques that are in place for long duration video retrieval. An experimentally tested technology under the JINI platform, demonstrates a practical working system which serves as a feasibility study, as well as the first step in realizing such a technology.

Due to increasing globalization and the explosion of media available on the Internet, computer techniques to organize, classify, and find desired media are becoming more and more relevant. One such technique to extract semantic information from multimedia data sources is Multimedia Information Retrieval (MMIR or MIR). MIR is a broad area covering both structural issues and intelligent content analysis and retrieval. These aspects must be integrated into a seamless whole, which involves expertise from a wide variety of fields. This book presents recent applications of MIR for content-based image retrieval, bioinformation analysis and processing, forensic multimedia retrieval techniques, and audio and music classification.

This volume constitutes the refereed proceedings of the 6th International Workshop on Adaptive Multimedia Retrieval, AMR 2008, held in Berlin, Germany, in June 2008.