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Spatiotemporally adaptive estimation and segmentation of OF-fields

  • Conference paper
  • First Online: 01 January 2006
  • pp 86–102
  • Cite this conference paper
Computer Vision — ECCV’98 (ECCV 1998)
Spatiotemporally adaptive estimation and segmentation of OF-fields
  • H. -H. Nagel1,2 &
  • A. Gehrke1 

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1407))

Included in the following conference series:

  • European Conference on Computer Vision
  • 404 Accesses

  • 39 Citations

Abstract

A grayvalue structure tensor provides knowledge about a local grayvalue variation. This knowledge can be used to devise a spatiotemporally adaptive optic flow estimation process. Such an adaptive estimation lowers the level at which the resulting optic flow (OF) field is disturbed by noise and estimation artefacts. This in turn substantially simplifies the analysis of remaining — often subtle — effects which easily jeopardize a ‘naive’ segmentation approach. Appropriate treatment of such effects eventually results in a basically simple, but nevertheless surprisingly robust segmentation approach. Various stages of this approach are illustrated by examples for the extraction of moving vehicle images from a digitized road intersection video-sequence.

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Author information

Authors and Affiliations

  1. Institut für Algorithmen und Kognitive Systeme, Fakultät für Informatik der Universität Karlsruhe (TH), Postfach 6980, D-76128, Karlsruhe, Germany

    H. -H. Nagel & A. Gehrke

  2. Fraunhofer-Institut für Informations- und Datenverarbeitung (IITB), Fraunhoferstr. 1, D-76131, Karlsruhe, Germany

    H. -H. Nagel

Authors
  1. H. -H. Nagel
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  2. A. Gehrke
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Hans Burkhardt Bernd Neumann

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© 1998 Springer-Verlag Berlin Heidelberg

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Nagel, H.H., Gehrke, A. (1998). Spatiotemporally adaptive estimation and segmentation of OF-fields. In: Burkhardt, H., Neumann, B. (eds) Computer Vision — ECCV’98. ECCV 1998. Lecture Notes in Computer Science, vol 1407. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0054735

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  • DOI: https://doi.org/10.1007/BFb0054735

  • Published: 26 May 2006

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64613-6

  • Online ISBN: 978-3-540-69235-5

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Keywords

  • Optic Flow
  • Finite Impulse Response
  • Small Eigenvalue
  • Adaptive Estimation
  • Edge Segment

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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