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Fast Local Estimation of Optical Flow Using Variational and Wavelet Methods

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Computer Analysis of Images and Patterns (CAIP 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2124))

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Abstract

We present a framework for fast (linear time) local estimation of optical flow in image sequences. Starting from the commonly used brightness constancy assumption, a simple differential technique is derived in a first step. Afterwards, this approach will be extended by the application of a nonlinear diffusion process to the flow field in order to reduce smoothing at motion boundaries. Due to the ill-posedness of the determination of optical flow from the related differential equations, a Wavelet-Galerkin projection method is applied to regularize and linearize the problem.

The author is supported by the Deutsche Forschungsgemeinschaft (DFG) within the Graduiertenkolleg 357, “Effiziente Algorithmen und Mehrskalenmethoden”.

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Author information

Authors and Affiliations

  1. Institut für Informatik und Praktische Mathematik, Christian-Albrecht-Universität Kiel, Preußerstraße 1-9, 24105, Kiel, Germany

    Kai Neckeis

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  1. Kai Neckeis
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Editor information

Editors and Affiliations

  1. Faculty of Electronics and Information Technology Institute of Radioelectronics, Warsaw University of Technology, ul. Nowowiejska 15/19, 00-665, Warsaw, Poland

    Władysław Skarbek

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© 2001 Springer-Verlag Berlin Heidelberg

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Neckeis, K. (2001). Fast Local Estimation of Optical Flow Using Variational and Wavelet Methods. In: Skarbek, W. (eds) Computer Analysis of Images and Patterns. CAIP 2001. Lecture Notes in Computer Science, vol 2124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44692-3_43

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  • DOI: https://doi.org/10.1007/3-540-44692-3_43

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42513-7

  • Online ISBN: 978-3-540-44692-7

  • eBook Packages: Springer Book Archive

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