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Fast Motion Estimation Using Spatio-temporal Correlations

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Advances in Artificial Reality and Tele-Existence (ICAT 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4282))

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Abstract

Motion Estimation (ME) is an important part of video encoding systems, since it can significantly affect the output quality of an encoded sequences. However, ME requires a significant part of the encoding time, because ME is a combination of techniques such as motion starting point, motion search pattern, etc. For this reason, low complexity motion estimation algorithms are viable solutions. In this paper, we propose a motion estimation algorithm to find the most accurate motion vectors(MVs) with the aim to maximize the encoding speed as well as the image quality. The proposed algorithm takes advantage of spatio-temporal correlations to decide the search pattern and the search start point adaptively and to avoid unnecessary motion vector search. Experiments show that the speedup improvement of the proposed algorithm over Motion Vector Field Adaptive Search Technique (MVFAST) and Predictive Motion Vector Fiekd Adaptive Search Technique (PMVFAST) can be up to 1.5 ~ 8 times faster while maintaining very similar image quality.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Chonnam National University, 300 Youngbong-dong, Buk-gu, Kwangju, 500-757, Korea

    Hyo Sun Yoon, Jae Myeong Yoo, Toan Nguyen Dinh, Hwa Jeong Son, Mi Seon Park & Guee Sang Lee

Authors
  1. Hyo Sun Yoon
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  2. Jae Myeong Yoo
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  3. Toan Nguyen Dinh
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  4. Hwa Jeong Son
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  5. Mi Seon Park
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  6. Guee Sang Lee
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Editor information

Editors and Affiliations

  1. State Key Lab of CAD and CG, Zhejiang University, Hangzhou, P.R. China

    Zhigeng Pan

  2. Mixed Reality Lab, National University of Singapore, Singapore

    Adrian Cheok

  3. Upper Austria University of Applied Science and Digital Media, Hagenberg, Austria

    Michael Haller

  4. Department of Computer Science, University of Durham, South Road, DH1 3LE, Durham, UK

    Rynson W. H. Lau

  5. Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi Kohoku-ku, 223-8522, Yokohama, Japan

    Hideo Saito

  6. College of Information Engineering, Zhejiang University of Technology, 310032, Hangzhou, P.R. China

    Ronghua Liang

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© 2006 Springer-Verlag Berlin Heidelberg

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Yoon, H.S., Yoo, J.M., Dinh, T.N., Son, H.J., Park, M.S., Lee, G.S. (2006). Fast Motion Estimation Using Spatio-temporal Correlations. In: Pan, Z., Cheok, A., Haller, M., Lau, R.W.H., Saito, H., Liang, R. (eds) Advances in Artificial Reality and Tele-Existence. ICAT 2006. Lecture Notes in Computer Science, vol 4282. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11941354_56

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  • DOI: https://doi.org/10.1007/11941354_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-49776-9

  • Online ISBN: 978-3-540-49779-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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