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  1. Workshop on multimedia information retrieval on The many faces of multimedia semantics (MS '07)
  2. Automatic metadata extraction and indexing for reusing e-learning multimedia objects
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An efficient manual image annotation approach based on tagging and browsing
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Article

Automatic metadata extraction and indexing for reusing e-learning multimedia objects

Content Provider ACM Digital Library
Author Rabitti, Fausto Falchi, Fabrizio Gennaro, Claudio Bolettieri, Paolo
Abstract In this paper we present the architecture of a Digital Library for enabling the reusing of audiovisual documents in an e-Learning context. The reuse of Learning Objects is based on automatically extracted descriptors carrying a semantic meaning for the professional that uses these Learning Objects to prepare new interactive multimedia lectures. The presented system is based on MILOS, a general purpose Multimedia Content Management System created to support design and effective implementation of digital library applications. MILOS supports the storage andcontent based retrieval of any multimedia documents whose descriptions are provided by using arbitrary metadata models represented in XML. The objective is to demonstrate the reuse of digital content, as video documents or Power Point presentations, by exploiting existing technologies for automatic extraction of metadata (OCR, speech recognition, cut detection, MPEG-7 visual descriptors, etc.). The search interface assists the user of the system in the retrieval the multimedia objects in the collection, by combining full-text retrieval on text extracted and metadata, and similarity search on the MPEG-7 visual descriptors.
Starting Page 21
Ending Page 28
Page Count 8
File Format PDF
ISBN 9781595937827
DOI 10.1145/1290067.1290072
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2007-09-28
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Mpeg-7 Multimedia content management system Automatic extraction User interface Metadata Similarity search
Content Type Text
Resource Type Article
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