Estimating the perceived difficulty of pen gestures

  • Authors:

  • Radu-Daniel Vatavu;Daniel Vogel;Géry Casiez;Laurent Grisoni

  • Affiliations:

  • University Stefan cel Mare of Suceava, Romania;LIFL, INRIA Lille & University of Lille, France and Mount Allison University, Canada;LIFL, INRIA Lille & University of Lille, France;LIFL, INRIA Lille & University of Lille, France

  • Venue:
  • INTERACT'11 Proceedings of the 13th IFIP TC 13 international conference on Human-computer interaction - Volume Part II
  • Year:
  • 2011

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Abstract

Our empirical results show that users perceive the execution difficulty of single stroke gestures consistently, and execution difficulty is highly correlated with gesture production time. We use these results to design two simple rules for estimating execution difficulty: establishing the relative ranking of difficulty among multiple gestures; and classifying a single gesture into five levels of difficulty. We confirm that the CLC model does not provide an accurate prediction of production time magnitude, and instead show that a reasonably accurate estimate can be calculated using only a few gesture execution samples from a few people. Using this estimated production time, our rules, on average, rank gesture difficulty with 90% accuracy and rate gesture difficulty with 75% accuracy. Designers can use our results to choose application gestures, and researchers can build on our analysis in other gesture domains and for modeling gesture performance.