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An Affine Optical Flow Model for Dynamic Surface Reconstruction

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Statistical and Geometrical Approaches to Visual Motion Analysis

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5604))

Abstract

In this paper we develop a differential model for simultaneous estimation of geometry and dynamics of a surface patch. To do so we combine a surface patch model in local 3D coordinates, a pinhole camera grid model and a brightness change model analogous to the brightness constancy constraint equation for optical flow. It turns out to be an extension of the well known affine optical flow model to higher dimensional data sets. Each of the translational and affine components of the optical flow is a term consisting of a mixture of surface patch parameters like its depth, slope, velocities etc. We evaluate the model by comparing estimation results using a simple local estimation scheme to available ground-truth. This simple estimation scheme already allows to get results in the same accuracy range one can achieve using range flow, i.e. a model for the estimation of 3D velocities of a surface point given a measured surface geometry. Consequently the new model allows direct estimation of additional surface parameters range flow is not capable of, without loss of accuracy in other parameters. What is more, it allows to design estimators coupling shape and motion estimation which may yield increased accuracy and/or robustness in the future.

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Author information

Authors and Affiliations

  1. Institute for Chemistry and Dynamics of the Geosphere, ICG-3, Forschungszentrum Jülich GmbH, 52425, Jülich, Germany

    Tobias Schuchert & Hanno Scharr

Authors
  1. Tobias Schuchert
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  2. Hanno Scharr
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Editor information

Editors and Affiliations

  1. Institut für Informatik III, Universität Bonn, Römerstraße 164, 53117, Bonn, Germany

    Daniel Cremers  & Frank R. Schmidt  & 

  2. Institut für Informationsverarbeitung, Leibniz Universität Hannover, Appelstraße 9A, 30167, Hannover, Germany

    Bodo Rosenhahn

  3. Department of Statistics and Psychology, University of California - Los Angeles, 8967 Math Sciences Building, 90095-1554, Los Angeles, CA, USA

    Alan L. Yuille

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Schuchert, T., Scharr, H. (2009). An Affine Optical Flow Model for Dynamic Surface Reconstruction. In: Cremers, D., Rosenhahn, B., Yuille, A.L., Schmidt, F.R. (eds) Statistical and Geometrical Approaches to Visual Motion Analysis. Lecture Notes in Computer Science, vol 5604. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03061-1_4

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  • DOI: https://doi.org/10.1007/978-3-642-03061-1_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03060-4

  • Online ISBN: 978-3-642-03061-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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