Visual similarity of pen gestures

  • Authors:
  • A. Chris Long, Jr.;James A. Landay;Lawrence A. Rowe;Joseph Michiels

  • Affiliations:
  • Department of Electrical Engineering and Computer Science, University of California at Berkeley, Berkeley, CA;Department of Electrical Engineering and Computer Science, University of California at Berkeley, Berkeley, CA;Department of Electrical Engineering and Computer Science, University of California at Berkeley, Berkeley, CA;Department of Electrical Engineering and Computer Science, University of California at Berkeley, Berkeley, CA

  • Venue:
  • Proceedings of the SIGCHI conference on Human Factors in Computing Systems
  • Year:
  • 2000

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Abstract

Pen-based user interfaces are becoming ever more popular. Gestures (i.e., marks made with a pen to invoke a command) are a valuable aspect of pen-based UIs, but they also have drawbacks. The challenge in designing good gestures is to make them easy for people to learn and remember. With the goal of better gesture design, we performed a pair of experiments to determine why users find gestures similar. From these experiments, we have derived a computational model for predicting perceived gesture similarity that correlates 0.56 with observation. We will incorporate the results of these experiments into a gesture design tool, which will aid the pen-based UI designer in creating gesture sets that are easier to learn and more memorable.