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Content-Based News Video Retrieval with Closed Captions and Time Alignment

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Advances in Multimedia Information Processing — PCM 2001 (PCM 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2195))

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Abstract

In this paper, we propose a new method for searching and browsing news videos, based on multi-modal approach. In the proposed scheme, we use closed caption (CC) data to index the contents of TV news articles effectively. To achieve time alignment between the CC texts and video data, which is necessary for multi-modal search and visualization, supervised speech recognition technique is employed. In our implementations, we provide two different mechanisms for news video browsing. One is to use a textual query based search engine, and the other is to use topic based browser which acts as an assistant tool for finding the desired news articles. Compared to other systems mainly dependent on visual features, the proposed scheme could retrieve more semantically relevant articles quite well.

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References

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Author information

Authors and Affiliations

  1. Broadcasting Media Technology Department, Electronics and Telecommunications Research Institute, 161 Gajeong-Dong, Yuseong-Gu, Daejeon, 305-350, Korea

    Young-tae Kim, Jae-Gon Kim, Hyun Sung Chang, Kyeongok Kang & Jinwoong Kim

Authors
  1. Young-tae Kim
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  2. Jae-Gon Kim
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  3. Hyun Sung Chang
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  4. Kyeongok Kang
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  5. Jinwoong Kim
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Editor information

Editors and Affiliations

  1. Microsoft Research China, 5/F Beijing Sigma Center 49 Zhichung Road, Haidian District, Beijing, 100080, China

    Heung-Yeung Shum

  2. Institute of Information Science, Academia Sinica, Taiwan

    Mark Liao

  3. Department of Electrical Engineering, Columbia University, New York, NY, 10027, USA

    Shih-Fu Chang

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© 2001 Springer-Verlag Berlin Heidelberg

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Kim, Yt., Kim, JG., Chang, H.S., Kang, K., Kim, J. (2001). Content-Based News Video Retrieval with Closed Captions and Time Alignment. In: Shum, HY., Liao, M., Chang, SF. (eds) Advances in Multimedia Information Processing — PCM 2001. PCM 2001. Lecture Notes in Computer Science, vol 2195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45453-5_115

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  • DOI: https://doi.org/10.1007/3-540-45453-5_115

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42680-6

  • Online ISBN: 978-3-540-45453-3

  • eBook Packages: Springer Book Archive

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