skip to main content
10.1145/2556288.2557056acmconferencesArticle/Chapter ViewAbstractPublication PageschiConference Proceedingsconference-collections
research-article

Probabilistic palm rejection using spatiotemporal touch features and iterative classification

Published:26 April 2014Publication History

ABSTRACT

Tablet computers are often called upon to emulate classical pen-and-paper input. However, touchscreens typically lack the means to distinguish between legitimate stylus and finger touches and touches with the palm or other parts of the hand. This forces users to rest their palms elsewhere or hover above the screen, resulting in ergonomic and usability problems. We present a probabilistic touch filtering approach that uses the temporal evolution of touch contacts to reject palms. Our system improves upon previous approaches, reducing accidental palm inputs to 0.016 per pen stroke, while correctly passing 98% of stylus inputs.

Skip Supplemental Material Section

Supplemental Material

pn0583-file3.mp4

mp4

47.9 MB

p2009-sidebyside.mp4

mp4

109.8 MB

References

  1. Boring, S., Ledo, D., Chen, X., Marquadt, N., Tang, A. and Greenberg, S. The fat thumb: using the thumb's contact size for single-handed mobile interaction. In Proc. MobileHCI '12, 39--48. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Bamboo Paper. Wacom. http://bamboopaper.wacom.com.Google ScholarGoogle Scholar
  3. Camilleri, M., Malige, A., Fujimoto, J., Rempei, D. (2013). Touch Displays: the effects of palm rejection technology on productivity, comfort, biomechanics, and positioning. In Ergonomics. Taylor & Francis Group.Google ScholarGoogle Scholar
  4. ClearPadTM Series 3. http://synaptics.com/solutions/products/clearpadGoogle ScholarGoogle Scholar
  5. EMR® Technology. Wacom. http://www.wacomcomponents.com/english/technology/emr.html.Google ScholarGoogle Scholar
  6. Ewerling, P., Kulik, A, Froehlich, B. Finger and hand detection for multi-touch interfaces based on maximally stable extremal regions. In Proc. ITS '12, 173--182. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Gu, J., Heo, S., Han, J., Kim, S. and Lee, G. LongPad: a touchpad using the entire area below the keyboard of a laptop computer. In Proc. CHI '13, 1421--1430. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Hall, M. A. Correlation-based Feature Subset Selection for Machine Learning. Ph.D. Thesis, 1998. Hamilton, New Zealand.Google ScholarGoogle Scholar
  9. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P. and Witten, I. H. The WEKA data mining software: an update. SIGKDD Explorations, 11(1), 10--18. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Hinckley, K. and Sinclair, M. Touch-Sensing Input Devices. In Proc. CHI '99, 223--230. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Hinckley, K., Wigdor, D., (2012). Input Technologies and Techniques (Chapter 9). In The Human-Computer Interaction Handbook, 3rd Edition, published by Taylor & Francis.Google ScholarGoogle ScholarCross RefCross Ref
  12. Hinckley, K., Yatani, K., Pahud, M., Coddington, N., Rodenhouse, J., Wilson, A., Benko, H., and Buxton, B. Pen + touch = new tools. In Proc. UIST '10, 27--36. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. iPen 2. Cregle Inc. http://www.cregle.com/pages/pressure-sensitive-stylus-for-your-imac-and-ipad.Google ScholarGoogle Scholar
  14. Jot Touch. Adonit. http://adonit.net/jot/touchGoogle ScholarGoogle Scholar
  15. Liang, R., Cheng, K., Su, C., Weng, C., Chen, B. and Yang, D. GaussSense: attachable stylus sensing using magnetic sensor grid. In Proc. UIST '12, 319--326. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. MyNote Pen. http://mynote.eu/mynotepen-en.html.Google ScholarGoogle Scholar
  17. Notability Ginger Labs. http://www.gingerlabs.com.Google ScholarGoogle Scholar
  18. Penultimate. Evernote. http://evernote.com/penultimate.Google ScholarGoogle Scholar
  19. Quinlan, J. R. C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Rogers, S., Williamson, J., Stewart, C. and Murray-Smith, R. AnglePose: robust, precise capacitive touch tracking via 3D orientation estimation. In Proc. CHI '12, 2575--2584. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Schwarz J., Hudson S., Mankoff, J. and Wilson, A.D. A framework for robust and flexible handling of inputs with uncertainty. In Proc. UIST '10, 47--56. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Steimle, J. (2012). Survey of Pen-and-Paper Computing. In Pen-and-Paper User Interfaces (pp. 19--65). Springer Berlin Heidelberg.Google ScholarGoogle ScholarCross RefCross Ref
  23. Vogel, D., Cudmore, M., Casiez, G., Balakrishnan, R. and Keliher, L. Hand occlusion with tablet-sized direct pen input. In Proc. CHI '09, 557--566. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Wang, F. and Ren, F. Empirical evaluation for finger input properties in multi-touch interaction. In Proc. CHI '10, 1063--1072. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Wang, F., Cao, X., Ren, X. and Irani, P. Detecting and leveraging finger orientation for interaction with directtouch surfaces. In Proc. UIST '09, 23--32. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Probabilistic palm rejection using spatiotemporal touch features and iterative classification

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
      April 2014
      4206 pages
      ISBN:9781450324731
      DOI:10.1145/2556288

      Copyright © 2014 ACM

      Permission to make digital or hard copies of all or part 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 components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 26 April 2014

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

      Acceptance Rates

      CHI '14 Paper Acceptance Rate465of2,043submissions,23%Overall Acceptance Rate6,199of26,314submissions,24%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader