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Video Sequence Matching Using Singular Value Decomposition

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Image Analysis and Recognition (ICIAR 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4141))

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Abstract

This paper proposes a novel signature based on singular value decomposition (SVD) for video sequence matching. By considering the input image as a matrix, a partition procedure is first performed to separate the matrix into non-overlapping sub-images of a fixed size. The SVD process then individually decomposes each partitioned sub-image into an singular value and the corresponding singular vector factorization. As a result, several dominant singular values are obtained for each sub-image, allowing the dissimilarity to be determined between the reference video clip and the query one. Experimental results based on receiver operating characteristics (ROC) curves confirm the effective performance of the proposed video signature.

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References

  1. Jain, A.K., Vailaya, A., Xiong, W.: Query by clip. Multimedia Syst. J. 7(5), 369–384 (1999)

    Article  Google Scholar 

  2. Naphade, M., Yeung, M., Yeo, B.: A novel scheme for fast and efficient video sequence matching using compact signatures. In: Proc. SPIE Conf. Storage and Retrieval for Media Databases, January 2000, vol. 3972, pp. 564–572 (2000)

    Google Scholar 

  3. Bhat, D.N., Nayar, S.K.: Ordinal measures for image correspondence. IEEE Trans. Pattern Anal. Mach. Intell. 20(4), 415–423 (1998)

    Article  Google Scholar 

  4. Mohan, R.: Video sequence matching. In: Proc. Int. Conf. Audio, Speech and Signal Processing (ICASSP), vol. 6, pp. 3697–3700 (January 1998)

    Google Scholar 

  5. Hampapur, A., Hyun, K.H., Bolle, R.M.: Comparison of sequence matching techniques for video copy detection. In: Proc. Storage and Retrieval for Media Databases, pp. 194–201 (January 2002)

    Google Scholar 

  6. Luo, J.H., Chen, C.C.: Singular value decomposition for texture analysis. In: Proceedings of SPIE- The International Society of Optical Engineering, Applications of Digital Image Processing XVII, CA, USA, vol. 2298, pp. 407–418 (1994)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Information Communication, Kyungnam College of Information & Technology, Busan, 617-701, South Korea

    Kwang-Min Jeong

  2. Dept. of Computer and Information Engineering, Dongseo University, Busan, 617-716, South Korea

    Joon-Jae Lee

  3. School of Electrical Engineering and Computer Science, Kyungpook National University, Daegu, 702-701, South Korea

    Yeong-Ho Ha

Authors
  1. Kwang-Min Jeong
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  2. Joon-Jae Lee
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  3. Yeong-Ho Ha
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Editor information

Editors and Affiliations

  1. Departamento de Engenharia Electrotécnica e de Computadores da, Faculdade de Engenharia da, Universidade do Porto, Campus FEUP, 4200-465, Porto, Portugal

    Aurélio Campilho

  2. Electrical and Computer Engineering Department, University of Waterloo,  

    Mohamed S. Kamel

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© 2006 Springer-Verlag Berlin Heidelberg

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Jeong, KM., Lee, JJ., Ha, YH. (2006). Video Sequence Matching Using Singular Value Decomposition. In: Campilho, A., Kamel, M.S. (eds) Image Analysis and Recognition. ICIAR 2006. Lecture Notes in Computer Science, vol 4141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11867586_40

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  • DOI: https://doi.org/10.1007/11867586_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44891-4

  • Online ISBN: 978-3-540-44893-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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