Visual Similarity of Pen Gestures (Paper Report)

Bibliography:

A. Chris Long, Jr., James A. Landay, Lawrence A. Rowe, and Joseph Michiels. 2000. Visual similarity of pen gestures. In Proceedings of the SIGCHI conference on Human Factors in Computing Systems (CHI '00). ACM, New York, NY, USA, 360-367. DOI=10.1145/332040.332458 http://doi.acm.org/10.1145/332040.332458

Link:

http://dl.acm.org/citation.cfm?id=332458

Summary:

This paper intended to find out why some gestures were similar while others were not in order to facilitate gesture design. Similar gestures may be easier to learn and remember. The gestures evaluated were single-stroke and iconic, similar to the Apple Newton MessagePad. Psychology research in the area of similarity of geometric shapes revealed that similarity could vary linearly or logarithmically based on such measurements such as area, width, height, tilt, ...etc, but the similarity metrics used not only differed from person to person, but could also differ from shape to shape.

Multi-dimensional scaling looks at a data set and tries to reduce the dimensionality of the set so that distances reflect the similarity and dissimilarity of the objects. When using MDS, the number of dimensions, the distance metric, and the meaning of the axes, are some of the issues that must be decided.

Two experiments were run with two different sets of gestures and two different sets of subjects. The first set of gestures were designed to be as different as possible from each other. Display of animated gestures were used instead of having the subjects draw them in order to have more participants and gestures even though drawing them would give more context in usage. Using regression analysis on the geometric features they were able to create a model to predict similarity of gestures. The second experiment used three sets of similar gestures and a fourth set containing gestures from the previous set. The second experiment was not as successful at predicting similarity.

Comments:

I thought this paper could be very helpful in gesture design and designing experiments for effective gesture design. The fact that many of the features of Rubine's paper were used could signify their importance in gesture classification. It was surprising that the second experiment did not do as well as the first.

Ideas for Research:

I was thinking of extending this experiment into 3D gestures in VR environments.