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abstract

Self-Training System of Calligraphy Brushwork

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Published:06 March 2017Publication History

ABSTRACT

In this paper, we describe a self-training system of brushwork of calligraphy. For writing a well-shaped character, the brushwork should be controlled properly. In the developed system, the motion of the student's brush is measured by Leapmotion sensor, and if the handwriting is not proper, the student's wrist is stimulated by a pressure presentation device at the moment as an instruction of a handwriting. Although the mechanism of the developed pressure presentation device was so simple, it could induce the student to correct the handwriting. The developed system can be an effective instruction device for self-training of calligraphy.

References

  1. Tsuda, N., Ozaki, S., Nakazawa, Y., Moriguchi, T., Nomura, Y. and Kato, N. 2016. Hand Motion Training System by Inducing Pressure Presentation. Proc. of the 12th IASTED international Conference on Biomedical Engineering (BioMed 2016) (Feb. 2016), 8--14.Google ScholarGoogle Scholar
  2. Henmi, K. and Yoshikawa, T. 1998. Virtual lessons and its application to virtual calligraphy system. Proc. of the IEEE International Conference on Robotics and Automation (May 1998), 1275--1280.Google ScholarGoogle Scholar
  3. Hayward, V. 2001. Survey of Haptic Interface Research at McGill University. Proc. Workshop in Interactive Multimodal Telepresence Systems (March 2001), 91--98.Google ScholarGoogle Scholar
  4. Narita, M and Matsumaru, T. 2015. Calligraphy-stroke learning support system using projection. Proceedings - IEEE International Workshop on Robot and Human Interactive Communication (Nov. 2015), 640--645.Google ScholarGoogle Scholar

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  1. Self-Training System of Calligraphy Brushwork

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        • Published in

          cover image ACM Conferences
          HRI '17: Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction
          March 2017
          462 pages
          ISBN:9781450348850
          DOI:10.1145/3029798

          Copyright © 2017 Owner/Author

          Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 6 March 2017

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          • abstract

          Acceptance Rates

          HRI '17 Paper Acceptance Rate51of211submissions,24%Overall Acceptance Rate192of519submissions,37%

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