Spatio-Temporal Handwriting Imitation

Mayr M, Stumpf M, Nicolaou A, Seuret M, Maier A, Christlein V (2020)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2020

Pages Range: 528-543

Event location: Online

ISBN: 978-3-030-68238-5


DOI: 10.1007/978-3-030-68238-5_38

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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.

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How to cite


Mayr, M., Stumpf, M., Nicolaou, A., Seuret, M., Maier, A., & Christlein, V. (2020). Spatio-Temporal Handwriting Imitation. In Springer, Cham (Eds.), Proceedings of the European Conference on Computer Vision (pp. 528-543). Online.


Mayr, Martin, et al. "Spatio-Temporal Handwriting Imitation." Proceedings of the European Conference on Computer Vision, Online Ed. Springer, Cham, 2020. 528-543.

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