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Optical Flow Computation with Locally Quadratic Assumption

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Computer Analysis of Images and Patterns (CAIP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9256))

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Abstract

The purpose of this paper is twofold. First, we develop a quadratic tracker which computes a locally quadratic optical flow field by solving a model-fitting problem for each point in its local neighbourhood. This local method allows us to select a region of interest for the optical flow computation. Secondly, we propose a method to compute the transportation of a motion field in long-time image sequences using the Wasserstein distance for cyclic distributions. This measure evaluates the motion coherency in an image sequence and detects collapses of smoothness of the motion vector field in an image sequence.

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Author information

Authors and Affiliations

  1. School of Advanced Integration Science, Chiba University, Chiba, Japan

    Tomoya Kato & Hayato Itoh

  2. Institute of Management and Information Technologies, Chiba University, Yayoi-cho 1-33, Inage-ku, Chiba, 263-8522, Japan

    Atsushi Imiya

Authors
  1. Tomoya Kato
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  2. Hayato Itoh
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  3. Atsushi Imiya
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Corresponding author

Correspondence to Atsushi Imiya .

Editor information

Editors and Affiliations

  1. University of Malta, Msida, Malta

    George Azzopardi

  2. University of Groningen, Groningen, The Netherlands

    Nicolai Petkov

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Kato, T., Itoh, H., Imiya, A. (2015). Optical Flow Computation with Locally Quadratic Assumption. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9256. Springer, Cham. https://doi.org/10.1007/978-3-319-23192-1_19

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  • DOI: https://doi.org/10.1007/978-3-319-23192-1_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23191-4

  • Online ISBN: 978-3-319-23192-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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