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Shot Boundary Detection Based on Distance Separability

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Artificial Intelligence and Computational Intelligence (AICI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7003))

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Abstract

Shot boundary detection is the first important task of content-based video retrieval. In this paper, a new SBD algorithm is proposed aiming to obtain accurate detection, and its performances are evaluated with different types of video. This algorithm computes distance ratio between within-class and between-class of two group frames, rather than the difference between two frames, which can resist light effects and camera/object movements in the same shot. The experimental results show that this universal algorithm can gain higher precision and recall.

This paper is funded by Returned students in personnel fund projects in Shanxi Province (2009-31) and International scientific and technological cooperation projects in Shanxi Province (2008081026).

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Author information

Authors and Affiliations

  1. College of Information Engineering, Taiyuan University of Technology, 79 Yingze West Street, Taiyuan, China, 030024

    Shaoshuai Lei, Xinying Xu, Qian Yang, Gang Xie & Hao Duan

Authors
  1. Shaoshuai Lei
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  2. Xinying Xu
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  3. Qian Yang
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  4. Gang Xie
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  5. Hao Duan
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Editor information

Editors and Affiliations

  1. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, VIC, Australia

    Hepu Deng

  2. School of Electronics and Information, Tongji University, 201804, Shanghai, China

    Duoqian Miao

  3. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  4. Department of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Lei, S., Xu, X., Yang, Q., Xie, G., Duan, H. (2011). Shot Boundary Detection Based on Distance Separability. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7003. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23887-1_63

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  • DOI: https://doi.org/10.1007/978-3-642-23887-1_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23886-4

  • Online ISBN: 978-3-642-23887-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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