  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 then 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.
