Estimating the Perceived Difficulty of Pen Gestures

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.
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Communication dans un congrès
Pedro Campos; Nicholas Graham; Joaquim Jorge; Nuno Nunes; Philippe Palanque; Marco Winckler. 13th International Conference on Human-Computer Interaction (INTERACT), Sep 2011, Lisbonne, Portugal. Springer, Lecture Notes in Computer Science, LNCS-6947 (Part II), pp.89-106, 2011, Human-Computer Interaction – INTERACT 2011. 〈10.1007/978-3-642-23771-3_9〉
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Radu Vatavu, Daniel Vogel, Géry Casiez, Laurent Grisoni. Estimating the Perceived Difficulty of Pen Gestures. Pedro Campos; Nicholas Graham; Joaquim Jorge; Nuno Nunes; Philippe Palanque; Marco Winckler. 13th International Conference on Human-Computer Interaction (INTERACT), Sep 2011, Lisbonne, Portugal. Springer, Lecture Notes in Computer Science, LNCS-6947 (Part II), pp.89-106, 2011, Human-Computer Interaction – INTERACT 2011. 〈10.1007/978-3-642-23771-3_9〉. 〈inria-00638385〉

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