Multimedia Retrieval
Blanken, Henk M.
Multimedia Retrieval [electronic resource] / edited by Henk M. Blanken, Henk Ernst Blok, Ling Feng, Arjen P. Vries. - XVIII, 372 p. online resource. - Data-Centric Systems and Applications . - Data-Centric Systems and Applications .
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.
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.
9783540728955
10.1007/978-3-540-72895-5 doi
Computer science.
Information storage and retrieval systems.
Multimedia systems.
Computer vision.
Optical pattern recognition.
Computer Science.
Information Storage and Retrieval.
Multimedia Information Systems.
Pattern Recognition.
User Interfaces and Human Computer Interaction.
Image Processing and Computer Vision.
QA75.5-76.95
025.04
Multimedia Retrieval [electronic resource] / edited by Henk M. Blanken, Henk Ernst Blok, Ling Feng, Arjen P. Vries. - XVIII, 372 p. online resource. - Data-Centric Systems and Applications . - Data-Centric Systems and Applications .
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.
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.
9783540728955
10.1007/978-3-540-72895-5 doi
Computer science.
Information storage and retrieval systems.
Multimedia systems.
Computer vision.
Optical pattern recognition.
Computer Science.
Information Storage and Retrieval.
Multimedia Information Systems.
Pattern Recognition.
User Interfaces and Human Computer Interaction.
Image Processing and Computer Vision.
QA75.5-76.95
025.04