Paper Reading #24: Gesture Avatar: A Technique for Operating Mobile User Interfaces Using Gestures

Reference

Authors and Affiliations

Hao Lü, Computer Science and Engineering DUB Group, University of Washington Seattle, WA 98195

Yang Li, Google Research,1600 Amphitheatre Parkway Mountain View, CA 94043

Presentation: CHI 2011, May 7–12, 2011, Vancouver, BC, Canada.

Summary

Hypothesis

The paper presents gesture avatar and hypothesizes the following about it performance.

1)Gesture Avatar will be slower than Shift on larger targets, but faster on small targets.

2) Gesture Avatar will have fewer errors than Shift.

3) Mobile situations such as walking will decrease the time performance and increase the error rate of Shift, but have little influence on Gesture Avatar.

Contents

The paper presents Gesture Avatar, a novel interaction technique that allows users to operate existing arbitrary user interfaces using gestures. It is hypothesized to leverage the visibility of graphical user interfaces and the casual interaction of gestures.

Due to the low precision of finger input, small user interface components are often difficult to acquire and operate on a mobile device. It is even harder when the user is on the go and unable to pay close attention to the interface. Authors designed and implemented Gesture Avatar, a novel interaction technique that allows users to operate mobile user interfaces using gestures.Gesture Avatar leverages the visibility of graphical user interfaces and the casual interaction of gestures. A user can dynamically associate a gesture shape with an arbitrary GUI widget and then interact with the widget through the drawn gesture, which is conceptually akin to an avatar.

Methods

12 users all right handed and who had experience with touch based devices participated in an experiment which required users to select targets using both methods (Shift and Gesture Avatar). . The variables that were tested were the two different techniques, the state of the user (sitting versus walking), the size of the targets being selected and the number of repeated letters in the selection group. Participants had a practice session where they performed the same type of task as in the real experiment.Half of the participants learned Shift first while the other half learned Gesture Avatar first.

Results

Gesture Avatar was significantly slower than Shift when TargetSize was 20px, but significantly faster than Shift when TargetSize was 10px.There was no significant difference between MobileState being sitting versus walking.

Analysis on Shift and Gesture separately found that for Gesture Avatar, there was no significant difference across all MobileStates and TargetSizes.Gesture Avatar had lower error rates than Shift on all TargetSizes, while there was no significant difference for Gesture Avatar across different TargetSizes.Majority of the people preferred gesture avatar for its easiness to use and better functionality while walking.The number of unique letters had no significant influence on Gesture Avatar.

Discussion

The research was really exciting to me. As a user of smartphone myself, I can see a lot of applications for this technology in small sized tablets and smartphones. It was a cool idea and the design parameters they present to solve the problem of ambiguity on selection was interesting as well. This should be a good tool because there certainly are problems when we try to do things on the go on smartphones. The research seems to be based on android, but I would love to see applications being developed in Windows and Apple platforms as well.