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Fast Multi-view Disparity Estimation for Multi-view Video Systems

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Advanced Concepts for Intelligent Vision Systems (ACIVS 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4179))

Abstract

Disparity estimation can be used to eliminate redundancy among different views in multi-view video compression to obtain high compression efficiency. However, the problem of high computational complexity in disparity estimation, which limits real-time applications of multi-view systems, needs to be solved. In this paper, a novel fast multi-view disparity estimation algorithm based on Hadamard similarity coefficient for multi-view video coding is proposed by using prediction of initial search point, selection of reference view, determination of the best disparity vector, and strategies of search stop. Experimental results show that the proposed algorithm can significantly reduce the computational complexity in multi-view disparity estimation.

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References

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Author information

Authors and Affiliations

  1. Faculty of Information Science and Eng., Ningbo University, Ningbo, 315211, China

    Gangyi Jiang, Mei Yu, Feng Shao, You Yang & Haitao Dong

  2. Institute of Computing Technology, Chinese Academy of Science, Beijing, 100080, China

    Gangyi Jiang & You Yang

  3. National Key Laboratory of Machine Perception, Peking University, Beijing, 100871, China

    Mei Yu & Feng Shao

Authors
  1. Gangyi Jiang
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  2. Mei Yu
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  3. Feng Shao
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  4. You Yang
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  5. Haitao Dong
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Editor information

Editors and Affiliations

  1. DGA/D4S/MRIS, 94114, Arcueil, France

    Jacques Blanc-Talon

  2. Ghent University, 9000, Gent, Belgium

    Wilfried Philips

  3. CSIRO ICT Centre, 1710, Sydney, NSW, Australia

    Dan Popescu

  4. University of Antwerp, 2610, Wilrijk, Belgium

    Paul Scheunders

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© 2006 Springer-Verlag Berlin Heidelberg

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Jiang, G., Yu, M., Shao, F., Yang, Y., Dong, H. (2006). Fast Multi-view Disparity Estimation for Multi-view Video Systems. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2006. Lecture Notes in Computer Science, vol 4179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11864349_45

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  • DOI: https://doi.org/10.1007/11864349_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44630-9

  • Online ISBN: 978-3-540-44632-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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