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AccPen: Using Smartphone with Accelerometer to Interact as Pen

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Published:21 April 2018Publication History

ABSTRACT

Smartphone has become a commodity device that makes life convenient whereas its capability of user interaction is often limited by its small touch screen. Employing built-in accelerometer to reconstruct gesture motions is considered as a promising solution for gesture interaction. However, the inability to separate unintentional movement from gesture motion, which often misleads the gesture recognition systems, limits the application of those acceleration-based methods. We present AccPen, a method that using smartphone as a pen for gesture interaction on physical surfaces, such as walls and tables. We utilize the high frequency portion of acceleration signals caused by friction when using the AccPen to write on physical surfaces to detect intentional gestures and reconstruct a representation of the gesture trajectory for gesture recognition. We conduct a study with 10 participants and present robust gesture recognition with an average accuracy of 92.22% across surfaces of desktops, wall, and paper.

References

  1. Agrawal S, Constandache I, Gaonkar S, et al. 2011. Using mobile phones to write in air. International conference on mobile systems, applications, and services, 15--28. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. G. Laput, R. Xiao, and C. Harrison. 2016. ViBand: High-Fidelity Bio-Acoustic Sensing Using Commodity Smartwatch Accelerometers. Proceedings of the 29th Annual Symposium on User Interface Software and Technology, 321--333. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. T. Miyagawa, Y. Yonezawa, K. Itoh, and M. Hashimoto. 2014. Handwritten pattern reproduction using 3D pen acceleration and angular velocity. The transactions of the Institute of Electronics, Information and Communication Engineers. 83: 1137--1140.Google ScholarGoogle Scholar
  4. J. A. Ward, P. Lukowicz, G. Troster, and T. E Starner. 2006. Activity recognition of assembly tasks using body-worn microphones and accelerometers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(10), 1553--1567. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Wobbrock, Jacob O., Andrew D. Wilson, and Yang Li. 2007. Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes. User interface software and technology, 159--168. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. AccPen: Using Smartphone with Accelerometer to Interact as Pen

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    • Published in

      cover image ACM Other conferences
      ChineseCHI '18: Proceedings of the Sixth International Symposium of Chinese CHI
      April 2018
      172 pages
      ISBN:9781450365086
      DOI:10.1145/3202667

      Copyright © 2018 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: 21 April 2018

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      Overall Acceptance Rate17of40submissions,43%
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