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Estimation of 2-D Motion Fields from Image Sequences with Application to Motion-Compensated Processing

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Motion Analysis and Image Sequence Processing

Part of the book series: The Springer International Series in Engineering and Computer Science ((SECS,volume 220))

Abstract

In this chapter we are concerned with the estimation of 2-D motion from time-varying images and with the application of the computed motion to image sequence processing. Our goal for motion estimation is to propose a general formulation that incorporates object acceleration, nonlinear motion trajectories, occlusion effects and multichannel (vector) observations. To achieve this objective we use Gibbs-Markov models linked together by the Maximum A Posteriori Probability criterion which results in minimization of a multiple-term cost function. The specific applications of motion-compensated processing of image sequences are prediction, noise reduction and spatiotemporal interpolation.

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Authors and Affiliations

  1. INRS-Télécommunications, Verdun, Québec, Canada, H3E 1H6

    E. Dubois & J. Konrad

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  1. E. Dubois
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  2. J. Konrad
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Editors and Affiliations

  1. Eastman Kodak Company, Rochester, NY, 14650-1816, USA

    M. Ibrahim Sezan

  2. Department of Electrical Engineering, Delft University of Technology, Delft, 2600 GA, The Netherlands

    Reginald L. Lagendijk

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© 1993 Springer Science+Business Media New York

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Dubois, E., Konrad, J. (1993). Estimation of 2-D Motion Fields from Image Sequences with Application to Motion-Compensated Processing. In: Sezan, M.I., Lagendijk, R.L. (eds) Motion Analysis and Image Sequence Processing. The Springer International Series in Engineering and Computer Science, vol 220. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-3236-1_3

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  • DOI: https://doi.org/10.1007/978-1-4615-3236-1_3

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-6422-1

  • Online ISBN: 978-1-4615-3236-1

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