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Conservative Motion Estimation from Multi-image Sequences

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Advances in Visual Computing (ISVC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6453))

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Abstract

Motion estimation in image sequences is a fundamental problem for digital video coding. In this paper, we present a new approach for conservative motion estimation from multi-image sequences. We deal with a system in which most of the motions in the scene are conservative or near-conservative in a certain temporal interval with multi-image sequences. Then a single conservative velocity field in this temporal range can across several successive frames. This system can be proved to be fully constrained or over-constrained when the number of frames is greater than two. A framework with displaced frame difference (DFD) equations, spatial velocity modeling, a nonlinear least-squares model, and Gauss-Newton and Levenberg-Marguardt algorithms for solving the nonlinear system is developed. The proposed algorithm is evaluated experimentally with two standard test image sequences. All successive frames except the last one (used for reference frame) in this conservative system can be synthesized by the motion-compensated prediction and interpolation based on the estimated motion field. This framework can estimate large scale motion field that across more than two successive frames if most of the motions in the scene in the temporal interval are conservative or near-conservative and has better performance than the block matching algorithm.

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Author information

Authors and Affiliations

  1. Remote Sensing Division, U. S. Naval Research Laboratory, Code 7233, 4555 Overlook Ave. S.W., Washington, D.C., 20375, USA

    Wei Chen

Authors
  1. Wei Chen
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, 89557, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, 94035, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. The Chinese University of Hong Kong, Shatin, Hong Kong, China

    Ronald Chung

  6. Dyna Vox Systems, Pittsburgh, PA, USA

    Riad Hammoud

  7. King Saud University, Riyadh, Saudi Arabia

    Muhammad Hussain

  8. Hewlett Packard Labs, Paolo Alto, CA, USA

    Tan Kar-Han

  9. The Ohio State University, Columbus, OH, USA

    Roger Crawfis

  10. Virtual Reality Lab, EPFL, Lausanne, Switzerland

    Daniel Thalmann

  11. NASA Ames Research Center, Clifton Park, NY, USA

    David Kao

  12. Kitware, Clifton Park, NY, USA

    Lisa Avila

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© 2010 Springer-Verlag Berlin Heidelberg

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Chen, W. (2010). Conservative Motion Estimation from Multi-image Sequences. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17289-2_41

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  • DOI: https://doi.org/10.1007/978-3-642-17289-2_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17288-5

  • Online ISBN: 978-3-642-17289-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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