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Visual Coin-Tracking: Tracking of Planar Double-Sided Objects

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Pattern Recognition (DAGM GCPR 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11824))

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Abstract

We introduce a new video analysis problem – tracking of rigid planar objects in sequences where both their sides are visible. Such coin-like objects often rotate fast with respect to an arbitrary axis producing unique challenges, such as fast incident light and aspect ratio change and rotational motion blur. Despite being common, neither tracking sequences containing coin-like objects nor suitable algorithm have been published.

As a second contribution, we present a novel coin-tracking benchmark containing 17 video sequences annotated with object segmentation masks. Experiments show that the sequences differ significantly from the ones encountered in standard tracking datasets. We propose a baseline coin-tracking method based on convolutional neural network segmentation and explicit pose modeling. Its performance confirms that coin-tracking is an open and challenging problem.

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Notes

  1. 1.

    Hence the problem name.

  2. 2.

    Available at http://cmp.felk.cvut.cz/coin-tracking.

  3. 3.

    Code and weights available at https://github.com/tensorflow/models/.

  4. 4.

    Available at https://github.com/facebookresearch/faiss.

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Acknowledgements

This work was supported by Toyota Motor Europe HS, by CTU student grant SGS17/185/OHK3/3T/13 and Technology Agency of the Czech Republic project TH0301019.

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Authors and Affiliations

  1. CMP Visual Recognition Group, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic

    Jonáš Šerých & Jiří Matas

Authors
  1. Jonáš Šerých
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  2. Jiří Matas
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Correspondence to Jonáš Šerých .

Editor information

Editors and Affiliations

  1. TU Dortmund University, Dortmund, Germany

    Gernot A. Fink

  2. University of Hamburg, Hamburg, Germany

    Simone Frintrop

  3. University of Münster, Münster, Germany

    Xiaoyi Jiang

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Šerých, J., Matas, J. (2019). Visual Coin-Tracking: Tracking of Planar Double-Sided Objects. In: Fink, G., Frintrop, S., Jiang, X. (eds) Pattern Recognition. DAGM GCPR 2019. Lecture Notes in Computer Science(), vol 11824. Springer, Cham. https://doi.org/10.1007/978-3-030-33676-9_22

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  • DOI: https://doi.org/10.1007/978-3-030-33676-9_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33675-2

  • Online ISBN: 978-3-030-33676-9

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