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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 37))

Abstract

Humans produce handwriting samples in their every-day life activity. Handwriting can be collected on-line, thanks to digitizing tablets, or off-line by scanning paper sheets. One question is whether such handwriting data can tell about individual style, health or emotional state of the writer. We will try to answer this question by presenting related works conducted on on-line and off-line data. We will show that pieces of off-line handwriting may be useful for recognizing a writer or a handwriting style. We will also show that anxiety can be recognized as an emotion from on-line handwriting and drawings using a non parametric approach such as random forests.

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Correspondence to Laurence Likforman-Sulem .

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Likforman-Sulem, L., Esposito, A., Faundez-Zanuy, M., Clémençon, S. (2015). Extracting Style and Emotion from Handwriting. In: Bassis, S., Esposito, A., Morabito, F. (eds) Advances in Neural Networks: Computational and Theoretical Issues. Smart Innovation, Systems and Technologies, vol 37. Springer, Cham. https://doi.org/10.1007/978-3-319-18164-6_34

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  • DOI: https://doi.org/10.1007/978-3-319-18164-6_34

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18163-9

  • Online ISBN: 978-3-319-18164-6

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