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Content-Based Video Retrieval

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Encyclopedia of Database Systems

Synonyms

Digital video search; Digital video retrieval

Definition

Content-based Video Retrieval refers to the provision of search facilities over archives of digital video content, where these search facilities are based on the outcome of an analysis of digital video content to extract indexable data for the search process.

Historical Background

As the volume of digital video data in existence constantly increases, the resulting vast archives of professional video content and UCC (User Created Content) are presenting an opportunity for the development of content-based video retrieval systems. Content-based video retrieval system development was initially lead by academic research such as the Informedia Digital Video Library [3] from CMU and the Físchlár Digital Video Suite [6] from DCU (Dublin City University). Both of these systems operated over thousands of hours of content, however digital video search has now become an everyday WWW phenomenon, with millions of items of digital...

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Recommended Reading

  1. Browne P., Smeaton A.F., Murphy N., O’Connor N., Marlow S., and Berrut C. 2000, Evaluating and combining digital video shot boundary detection algorithms. In Proc. IMVIP 2000 – Irish Machine Vision and Image Processing Conference, pp. 93–100.

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  2. Christel M.G., Hauptmann A.G., Wactlar H.D., and Ng T.D., 2002, Collages as dynamic summaries for news video. In Proc. 10th ACM Int. Conf. on Multimedia, pp. 561–569.

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  3. Hauptmann A. lessons for the future from a decade of informedia video analysis research, image and video retrieval. In Proc. 4th Int. Conf. Image and Video Retrieval, 2005, pp. 1–10.

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  4. Sadlier D. and O’Connor N. Event detection in field sports video using audio-visual features and a support vector machine. IEEE Trans. Circuits Syst. Video Technol., 15(10):1225–1233, 2005.

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  5. Sivic J. AND Zisserman A. Video Google: a text retrieval approach to object matching in videos. In Proc. 9th IEEE Conf. Computer Vision, Vol. 2, 2003, pp. 1470–1477.

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  6. Smeaton A.F., Lee H., and Mc Donald K. Experiences of creating four video library collections with the Físchlár system. Int. J. Digit. Libr., 4(1):42–44, 2004.

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  7. Smeaton A.F., Over P., and Kraaij W. 2006, Evaluation campaigns and TRECVid. In Proc. 8th ACM SIGMM Int. Workshop on Multimedia Information Retrieval, pp. 321–330.

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  8. http://trec.nist.gov Last visited June '08.

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Author information

Authors and Affiliations

  1. Dublin City University, Dublin, Ireland

    Cathal Gurrin

Authors
  1. Cathal Gurrin
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Editor information

Editors and Affiliations

  1. College of Computing, Georgia Institute of Technology, 266 Ferst Drive, 30332-0765, Atlanta, GA, USA

    LING LIU (Professor) (Professor)

  2. Database Research Group David R. Cheriton School of Computer Science, University of Waterloo, 200 University Avenue West, N2L 3G1, Waterloo, ON, Canada

    M. TAMER ÖZSU (Professor and Director, University Research Chair) (Professor and Director, University Research Chair)

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© 2009 Springer Science+Business Media, LLC

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Gurrin, C. (2009). Content-Based Video Retrieval. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_1027

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