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An Evaluation of Data Costs for Optical Flow

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Pattern Recognition (GCPR 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8142))

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Abstract

Motion estimation in realistic outdoor settings is significantly challenged by cast shadows, reflections, glare, saturation, automatic gain control, etc. To allow robust optical flow estimation in these cases, it is important to choose appropriate data cost functions for matching. Recent years have seen a growing trend toward patch-based data costs, as they are already common in stereo. Systematic evaluations of different costs in the context of optical flow have been limited to certain cost types, and carried out on data without challenging appearance. In this paper, we contribute a systematic evaluation of various pixel- and patch-based data costs using a state-of-the-art algorithmic testbed and the realistic KITTI dataset as basis. Akin to previous findings in stereo, we find the Census transformation to be particularly suitable for challenging real-world scenes.

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Author information

Authors and Affiliations

  1. Photogrammetry and Remote Sensing, ETH Zurich, Switzerland

    Christoph Vogel & Konrad Schindler

  2. Department of Computer Science, TU Darmstadt, Germany

    Stefan Roth

Authors
  1. Christoph Vogel
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  2. Stefan Roth
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  3. Konrad Schindler
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Editor information

Editors and Affiliations

  1. Faculty of Mathematics and Computer Science, Saarland University, Campus E1.7, 66041, Saarbrücken, Germany

    Joachim Weickert

  2. Faculty of Mathematics and Computer Science, Saarland University, Campus E1.3, 66041, Saarbrücken, Germany

    Matthias Hein

  3. Computer Vision and Multimodal Computing, Max-Planck-Institute for Informatics, Campus E 1.4, 66123, Saarbrücken, Germany

    Bernt Schiele

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Vogel, C., Roth, S., Schindler, K. (2013). An Evaluation of Data Costs for Optical Flow. In: Weickert, J., Hein, M., Schiele, B. (eds) Pattern Recognition. GCPR 2013. Lecture Notes in Computer Science, vol 8142. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40602-7_37

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  • DOI: https://doi.org/10.1007/978-3-642-40602-7_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40601-0

  • Online ISBN: 978-3-642-40602-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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