Video Browser Showdown by NUS

  • Jin Yuan
  • Huanbo Luan
  • Dejun Hou
  • Han Zhang
  • Yan-Tao Zheng
  • Zheng-Jun Zha
  • Tat-Seng Chua
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7131)

Abstract

The known item search task (KIS) aims to retrieve a unique video or video clip in the video corpus. This paper presents a novel interactive video browsing system for KIS task. Our system integrates visual content-based, text-based and concept-based search approaches. It allows users to flexibly choose the search approaches. Moreover, two novel feedback schemes are employed: first, users can specify the temporal order in visual and conceptual inputs; second, users can label related samples with respect to visual, textual and conceptual features. Adopting these two feedback schemes greatly enhances search performance.

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References

  1. 1.
    Chen, X.Y., Yuan, J., et al.: TRECVID 2010 Known-item Search by NUS. In: TRECVID Workshop (2010)Google Scholar
  2. 2.
    Yuan, J., Zha, Z.-J., et al.: Utilizing Related Samples to Enhance Interactive Concept-based Video Search. IEEE Transactions on Multimedia (2011)Google Scholar
  3. 3.
    Yuan, J., Zha, Z.-J., et al.: Learning Concept Bundles for Video Search with Complex Queries. In: Proc. of ACM Int. Conf. on Multimedia (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jin Yuan
    • 1
  • Huanbo Luan
    • 1
  • Dejun Hou
    • 1
  • Han Zhang
    • 1
  • Yan-Tao Zheng
    • 1
  • Zheng-Jun Zha
    • 1
  • Tat-Seng Chua
    • 1
  1. 1.School of ComputingNational University of SingaporeSingapore

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