Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

Visual Similarity of Pen Gestures

A. Chris Long, James A. Landay, Lawrence A. Rowe and Joseph Michiels

EECS Department
University of California, Berkeley
Technical Report No. UCB/CSD-99-1069
1999

http://www.eecs.berkeley.edu/Pubs/TechRpts/1999/CSD-99-1069.pdf

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.


BibTeX citation:

@techreport{Long:CSD-99-1069,
    Author = {Long, A. Chris and Landay, James A. and Rowe, Lawrence A. and Michiels, Joseph},
    Title = {Visual Similarity of Pen Gestures},
    Institution = {EECS Department, University of California, Berkeley},
    Year = {1999},
    URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/1999/6234.html},
    Number = {UCB/CSD-99-1069},
    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.}
}

EndNote citation:

%0 Report
%A Long, A. Chris
%A Landay, James A.
%A Rowe, Lawrence A.
%A Michiels, Joseph
%T Visual Similarity of Pen Gestures
%I EECS Department, University of California, Berkeley
%D 1999
%@ UCB/CSD-99-1069
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/1999/6234.html
%F Long:CSD-99-1069