A Feature-Based Algorithm for Recognizing Gestures on Portable Computers

  • Mi Gyung Cho
  • Am Sok Oh
  • Byung Kwan Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3043)


Pen gestures are a promising feature of pen-based user interface. Recently, as the supply of pen-based portable computers such as PDAs has increased, so has the usage of them. But they have not yet been fully exploited. In this paper we proposed a new gesture set which consists of eight gestures for editing electronic ink data and a feature-based recognition algorithm to identify gestures. We implemented GesEdit, the gesture-allowed ink editor on PDAs, to verify the proposed algorithm. A variety of experiments involving twenty users showed that the gesture recognition rate reached 99.6%. In addition, they showed that the algorithm was efficient as much portable devices as desktop computers.


Recognition Rate Recognition Algorithm Gesture Recognition High Recognition Rate Average Recognition Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Aref, W., Barbara, B.: Supporting Electronic Ink Database. Information Systems 24, 303–326 (1999)CrossRefGoogle Scholar
  2. 2.
    Lopresti, D., Ma, M.Y., Wang, P.S.P., Crisman, J.D.: Ink Matching of Cursive Chinese Handwritten Annotations. International Journal of Pattern Recognition and Artificial Intelligence 12, 119–141 (1998)CrossRefGoogle Scholar
  3. 3.
    Lopresti, D.P.: Ink as Multimedia Data. In: Proceedings of the Fourth International Conference on Informaion, Systems, Analysis and Synthesis, pp. 122–128 (1998)Google Scholar
  4. 4.
    Hong, J.I., Landay, J.A.: SATIN: A Toolkit for informal ink-based applications. CHI Letters: UIST 2(2), 63–72 (2000)Google Scholar
  5. 5.
    Burnett, M.M., Gottfried, H.J.: Graphical definitions: expanding spreadsheet languages through direct manipulation and gestures. ACM Tansactions on Computer-Human Interaction 5(1), 1–33 (1998)CrossRefGoogle Scholar
  6. 6.
    Long, A.C.: Improving Gestures and Interaction Techniques for Pen-Based User Interfaces. In: ACM CHI 1998, pp. 58–59 (1998)Google Scholar
  7. 7.
    Christian, A.: Quill: A Gesture Design Tool for Pen-Based User Interfaces, Ph.D Thesis, University of California, Berkeley (2001) Google Scholar
  8. 8.
    Avraham, D., et al.: Guided Gesture Support in the Paper PDAs. In: ACM UIST 2001, pp. 197–198 (2001)Google Scholar
  9. 9.
    Damm, C.H., Hansen, K.M., Thomsen, M.: Tool support for cooperative object-oriented design: Gesture based modeling on an electronic whiteboard. CHI Letters: Human Factors in Computing Systems 2(1), 518–525 (2000)Google Scholar
  10. 10.
    Rubine, D.: Specifying gestures by example. ACM SIGGRAPH 25, 329–337 (1991)CrossRefGoogle Scholar
  11. 11.
    Lipcomb, J.: A trainable gesture recognizer. Pattern Recognition 24(9), 895–907 (1991)CrossRefGoogle Scholar
  12. 12.

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Mi Gyung Cho
    • 1
  • Am Sok Oh
    • 1
  • Byung Kwan Lee
    • 2
  1. 1.Dept. of Multimedia EngineeringTongmyong University of ITBusanSouth Korea
  2. 2.Dept. of Computer EngineeringKwandong UniversityKwangwonDoSouth Korea

Personalised recommendations