Small, medium, or large?: estimating the user-perceived scale of stroke gestures

Authors:
Radu-Daniel Vatavu;Géry Casiez;Laurent Grisoni
Affiliations:
University Stefan cel Mare of Suceava, Suceava, Romania;LIFL & INRIA Lille, University of Lille, Villeneuve d'Ascq, France;LIFL & INRIA Lille, University of Lille, Villeneuve d'Ascq, France
Venue:
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Year:
2013

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Abstract

We show that large consensus exists among users in the way they articulate stroke gestures at various scales (i.e., small, medium, and large), and formulate a simple rule that estimates the user-intended scale of input gestures with 87% accuracy. Our estimator can enhance current gestural interfaces by leveraging scale as a natural parameter for gesture input, reflective of user perception (i.e., no training required). Gesture scale can simplify gesture set design, improve gesture-to-function mappings, and reduce the need for users to learn and for recognizers to discriminate unnecessary symbols.