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A Fast Ancauhor Shot Detection Algorithm on Compressed Video

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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

Detecting anchor shots accurately is very important for automatically parsing news video and extracting news items. The paper presents a fast anchor shot detection algorithm, based on background chrominance and skin tone models. The algorithm involves only simple computation, but robust. Moreover it operates in MPEG compression domain, which makes the detection speed very fast. The algorithm was evaluated on a big test set containing more than 480000 frames and news video from two different TV stations. More than 98.9% accuracy and 100% recall have been obtained. The experiment results also show the system has an average detection speed of 77.55 f/s. The statistics indicates the algorithm is fast and effective.

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References

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Author information

Authors and Affiliations

  1. Institute of Computing Technology, Chinese Academy of Sciences, BeiJing, 100080

    WeiQiang Wang & Wen Gao

  2. Department of Computer Science, Harbin Institute of Technology, 150001

    Wen Gao

Authors
  1. WeiQiang Wang
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  2. Wen Gao
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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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Wang, W., Gao, W. (2001). A Fast Ancauhor Shot Detection Algorithm on Compressed Video. 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_114

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  • DOI: https://doi.org/10.1007/3-540-45453-5_114

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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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