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

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.

REFERENCES

• 1: Nettuno. http://www.uninettuno.it.
• 2: Mpeg requirements group, mpeg-7 overview, 2003. Doc. ISO/IEC JTC1/SC29/WG11N5525.
• 3: G. Amato, F. Debole, F. Rabitti, and P. Zezula. YAPI: Yet another path index for XML searching. In ECDL 2003, 7th European Conference on Research and Advanced Technology for Digital Libraries, Trondheim, Norway, August 17-22, 2003, 2003.
• 4: G. Amato, C. Gennaro, P. Savino, and F. Rabitti. Milos: a multimedia content management system for digital library applications. In Proceedings of the 8th European Conference on Research and Advanced Technology for Digital Libraries (ECDL 2004), volume 3232 of Lecture Notes in Computer Science, pages 14-25. Springer, September 2004.
• 5: Christian Böhm , Stefan Berchtold , Daniel A. Keim, Searching in high-dimensional spaces: Index structures for improving the performance of multimedia databases, ACM Computing Surveys (CSUR), v.33 n.3, p.322-373, September 2001 [doi>10.1145/502807.502809]
• 6: Dick C. A. Bulterman, Is It Time for a Moratorium on Metadata?, IEEE MultiMedia, v.11 n.4, p.10-17, October 2004 [doi>10.1109/MMUL.2004.29]
• 7: I. L. T. S. Committee. Ieee 1484.12.1-2002, draft standard for learning object metadata. http://ltsc.ieee.org/wg12/index.html, 2002.
• 8: W. W. W. Consortium. XML path language (XPath), version 1.0, W3C. Recommendation, November 1999.
• 9: Nello Cristianini , John Shawe-Taylor, An introduction to support Vector Machines: and other kernel-based learning methods, Cambridge University Press, New York, NY, 1999
• 10: A. Hauptmann , H. Wactlar, Indexing and Search of Multimodal Information, Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1, p.195, April 21-24, 1997
• 11: ISO/IEC. Information technology-Multimedia content description interfaces. Part 3: Visual. 15938-3:2002.
• 12: ISO/IEC. Information technology-Multimedia content description interfaces. Part 6: Reference Software. 15938-6:2003.
• 13: Gerard Salton , Michael J. McGill, Introduction to Modern Information Retrieval, McGraw-Hill, Inc., New York, NY, 1986
• 14: P. Zezula, G. Amato, F. Debole, and F. Rabitti. Tree signatures for xml querying and navigation. In Database and XML Technologies, First International XML Database Symposium, XSym 2003, volume 2824 of Lecture Notes in Computer Science, pages 149--163. Springer, 2003.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.7 Digital Libraries

General Terms:
Algorithms, Design, Documentation

Keywords:
MPEG-7, automatic extraction, metadata, multimedia content management system, similarity search, user interface