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Abstract:

The presented work is motivated by the problem of local motion estimation via robust regression with linear models. In order to increase the robustness of the motion estimates we propose a novel Robust Local Optical Flow approach based on a modified Hampel estimator. We show the deficiencies of the least squares estimator used by the standard KLT tracker when the assumptions made by Lucas/Kanade are violated. We propose a strategy to adapt the window sizes to cope with the Generalized Aperture Problem...

Related Publications

2016

2014

  • Tobias Senst, Thilo Borgmann, Ivo Keller, Thomas Sikora
    Cross based Robust Local Optical Flow
    21th IEEE International Conference on Image Processing, Paris,France, 27.10.2014 - 30.10.2014, pp. 1967-1971
    ISBN: 978-1-4799-5750-7 DOI:10.1109/ICIP.2014.7025394
    Details BibTeX

2013

2012

2011

Description

We provide binaries of the RLOF feature tracker in order to help other researchers to compare their results or to use our work as a module for their research. The files contain a binary package for the Windows operating system.

The documentation is included in the RLOF package (/Doc/html/index.html) or available online by the following link:

[Documentation] [1]

 Current versions are available:

  • Windows Visual Studio 2008 [x86/x64]
  • Windows Visual Studio 2010 [x86/x64]
  • Windows Matlab [x86/x64]

[README] [2]

[List of people who downloaded the RLOFLib] [3]

To receive the code, please fill out this form:

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Terms of use

All code is provided for research purposes only and without any warranty. Any commercial use is prohibited. By using the code in your research work, you should cite the respective paper.

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