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{ "item_title" : "Multimedia Retrieval", "item_author" : [" Henk M. Blanken", "Arjen P. De Vries", "Henk Ernst Blok "], "item_description" : "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.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/54/072/894/3540728945_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Multimedia Retrieval|Henk M. Blanken

Multimedia Retrieval

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Overview

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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Details

  • ISBN-13: 9783540728948
  • ISBN-10: 3540728945
  • Publisher: Springer
  • Publish Date: July 2007
  • Dimensions: 9.32 x 6.36 x 0.99 inches
  • Shipping Weight: 1.67 pounds
  • Page Count: 372

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