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Spatio-Temporal Handwriting Imitation

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Computer Vision – ECCV 2020 Workshops (ECCV 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12539))

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Abstract

Most people think that their handwriting is unique and cannot be imitated by machines, especially not using completely new content. Current cursive handwriting synthesis is visually limited or needs user interaction. We show that subdividing the process into smaller subtasks makes it possible to imitate someone’s handwriting with a high chance to be visually indistinguishable for humans. Therefore, a given handwritten sample will be used as the target style. This sample is transferred to an online sequence. Then, a method for online handwriting synthesis is used to produce a new realistic-looking text primed with the online input sequence. This new text is rendered and style-adapted to the input pen. We show the effectiveness of the pipeline by generating in- and out-of-vocabulary handwritten samples that are validated in a comprehensive user study. Additionally, we show that also a typical writer identification system can partially be fooled by the created fake handwritings.

\(^*\)Both samples are synthesized.

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Notes

  1. 1.

    Code and models available below https://github.com/M4rt1nM4yr/spatio-temporal_handwriting_imitation.

  2. 2.

    https://forms.gle/MGCPk5UkxnR23FqT9.

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Authors and Affiliations

  1. Pattern Recognition Lab, Friedrich–Alexander-Universität Erlangen–Nürnberg, Erlangen, Germany

    Martin Mayr, Martin Stumpf, Anguelos Nicolaou, Mathias Seuret, Andreas Maier & Vincent Christlein

Authors
  1. Martin Mayr
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  2. Martin Stumpf
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  3. Anguelos Nicolaou
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  4. Mathias Seuret
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  5. Andreas Maier
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  6. Vincent Christlein
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Corresponding author

Correspondence to Martin Mayr .

Editor information

Editors and Affiliations

  1. University of Clermont Auvergne, Clermont Ferrand, France

    Adrien Bartoli

  2. Università degli Studi di Udine, Udine, Italy

    Andrea Fusiello

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Mayr, M., Stumpf, M., Nicolaou, A., Seuret, M., Maier, A., Christlein, V. (2020). Spatio-Temporal Handwriting Imitation. In: Bartoli, A., Fusiello, A. (eds) Computer Vision – ECCV 2020 Workshops. ECCV 2020. Lecture Notes in Computer Science(), vol 12539. Springer, Cham. https://doi.org/10.1007/978-3-030-68238-5_38

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  • DOI: https://doi.org/10.1007/978-3-030-68238-5_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-68237-8

  • Online ISBN: 978-3-030-68238-5

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