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Fast Content-Based Mining of Web2.0 Videos

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Advances in Multimedia Information Processing - PCM 2008 (PCM 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5353))

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Abstract

The accumulation of many transformed versions of the same original videos on Web2.0 sites has a negative impact on the quality of the results presented to the users and on the management of content by the provider. An automatic identification of such content links between video sequences can address these difficulties. We put forward a fast solution to this video mining problem, relying on a compact keyframe descriptor and an adapted indexing solution. Two versions are developed, an off-line one for mining large databases and an online one to quickly post-process the results of keyword-based interactive queries. After demonstrating the reliability of the method on a ground truth, the scalability on a database of 10,000 hours of video and the speed on 3 interactive queries, some results obtained on Web2.0 content are illustrated.

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Author information

Authors and Affiliations

  1. Vertigo - CNAM, 292 rue St Martin, 75141, Paris cedex 03, France

    Sébastien Poullot & Michel Crucianu

  2. Institut National de l’Audiovisuel, 94366, Bry-sur-Marne, France

    Sébastien Poullot & Olivier Buisson

Authors
  1. Sébastien Poullot
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  2. Michel Crucianu
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  3. Olivier Buisson
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Editor information

Editors and Affiliations

  1. Department of Engineering Science, National Cheng Kung University, No.1, University Road, 701, Tainan City, Taiwan

    Yueh-Min Ray Huang

  2. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95, Zhongguancun East Road, 100190, Beijing, China

    Changsheng Xu

  3. Institute of Biomedical Engineering, National Cheng Kung University, No. 1, University Road, 701, Tainan City, Taiwan

    Kuo-Sheng Cheng

  4. Department of Electrical Engineering, National Cheng Kung University, No. 1, University Road, 701, Tainan City, Taiwan

    Jar-Ferr Kevin Yang

  5. Department of Electrical and Computer Engineering, Concordia University, S-EV005.139, 1515 St. Catherine West, Montreal, H4G 2W1, Quebec, Canada

    M. N. S. Swamy

  6. Microsoft Research Asia, 5/F, Beijing Sigma Center, No. 49, Zhichun Road, Hai Dian District, 100080, Beijing, China

    Shipeng Li

  7. Department of Information Management, National Kaohsiung University of Applied Sciences, No. 415, Jiangong Road, Sanmin District, 80778, Kaohsiung, Taiwan

    Jen-Wen Ding

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© 2008 Springer-Verlag Berlin Heidelberg

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Poullot, S., Crucianu, M., Buisson, O. (2008). Fast Content-Based Mining of Web2.0 Videos. In: Huang, YM.R., et al. Advances in Multimedia Information Processing - PCM 2008. PCM 2008. Lecture Notes in Computer Science, vol 5353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89796-5_11

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  • DOI: https://doi.org/10.1007/978-3-540-89796-5_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89795-8

  • Online ISBN: 978-3-540-89796-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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