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A Time-Constrained Sequential Pattern Mining for Extracting Semantic Events in Videos

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Multimedia Data Mining and Knowledge Discovery

Abstract

In this chapter, we present a time-constrained sequential pattern mining method for extracting semantic patterns associated with semantically relevant events (semantic events) in videos. Since a video itself is just a rawmaterial, we transform the video into a multistream of rawlevel metadata.

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Authors
  1. Kimiaki Shirahama
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  2. Koichi Ideno
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  3. Kuniaki Uehara
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Editor information

Editors and Affiliations

  1. Accenture Technology Labs, Accenture Ltd, 161 N. Clark St., 60601, Chicago, IL, USA

    Valery A. Petrushin MS, PhD

  2. School of Forest Resources and Conservation, University of Florida, EC 31 2601 N. Floyd Rd., 75080-1407, Richardson, TX, USA

    Latifur Khan BS, MS, PhD

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Shirahama, K., Ideno, K., Uehara, K. (2007). A Time-Constrained Sequential Pattern Mining for Extracting Semantic Events in Videos. In: Petrushin, V.A., Khan, L. (eds) Multimedia Data Mining and Knowledge Discovery. Springer, London. https://doi.org/10.1007/978-1-84628-799-2_20

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  • DOI: https://doi.org/10.1007/978-1-84628-799-2_20

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84628-436-6

  • Online ISBN: 978-1-84628-799-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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