Visual Similarity of Pen Gestures

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

This paper aims to determine which gestures users perceive as similar and develop a computational model for predicting perceived similarity of gestures. The primary contribution appears to be for gesture designers, however the paper contributes several new features for gesture recognition, as well as a model for gesture similarity.

Two studies were performed to hep gather data on perception of similarity between gestures. First, 21 participants were asked to view 364 triads of sketches and identify the sketch that was least like the others for each triad. To determine the similarity, MDS was run on the collected data. A regression analysis was then run to determine which of the geometric features correlated with the similarity. The features examined consisted of the Rubine features, and several additional features (mostly logarithmic interpretations) inspired by work done by Attneave, a psychology researcher.

A second trial was conducted with 20 participants and was designed to examine specific aspects of the features identified in the first study. The data from study 1 was used to predict the results of study 2. The derived model predicted accurately about 70% of the time between study 1 and 2. Further, the correlation between prediction of trial 1 and the data from trial two was about 56%.

This paper illustrates that there are several significant factors which affect the perception of similarity between pen gestures. Unsurprisingly, features which take into consideration the logarithmic nature of some perceptual processes provide great benefit to gesture recognition.