International audienceWe show that users are consistent in their assessments of the articulation difficulty of multi-touch gestures, even under the many degrees of freedom afforded by multi-touch input, such as (1) various number of fingers touching the surface, (2) various number of strokes that structure the gesture shape, and (3) single-handed and bimanual input. To understand more about perceived difficulty, we characterize gesture articulations captured under these conditions with geometric and kinematic descriptors computed on a dataset of 7,200 samples of 30 distinct gesture types collected from 18 participants. We correlate the values of the objective descriptors with users' subjective assessments of articulation difficulty and report path length, production time, and gesture size as the highest correlators (max Pearson's r=.95). We also report new findings about multi-touch gesture input, e.g., gestures produced with more fingers are larger in size and take more time to produce than single-touch gestures; bimanual articulations are not only faster than single- handed input, but they are also longer in path length, present more strokes, and result in gesture shapes that are deformed horizontally by 35% in average. We use our findings to outline a number of 14 guidelines to assist multi-touch gesture set design, recognizer development, and inform gesture-to-function mappings through the prism of the user-perceived difficulty of gesture articulation

Abstract. Multi-touch gestures are often thought by application designers for a one-to-one mapping between gestures and commands, which does not take into account the high variability of user gestures for actions in the physical world; it can also be a limitation that leads to very simplistic interaction choices. Our motivation is to make a step toward many-to-one mappings between user gestures and commands, by understanding user gestures variability for multi-touch systems; for doing so, we set up a user study in which we target symbolic gestures on tabletops. From a first phase study we provide qualitative analysis of user gesture variability; we derive this analysis into a taxonomy of user gestures, that is discussed and compared to other existing taxonomies. We introduce the notion of atomic movement; such elementary atomic movements may be combined throughout time (either sequentially or in parallel), to structure user gesture. A second phase study is then performed with specific class of gesture-drawn symbols; from this phase, and according to the provided taxonomy, we evaluate user gesture variability with a fine grain quantitative analysis. Our findings indicate that users equally use one or two hands, also that more than half of gestures are achieved using parallel or sequential combination of atomic movements. We also show how user gestures distribute over different movement categories, and correlate to the number of fingers and hands engaged in interaction. Finally, we discuss implications of this work to interaction design, practical consequences on gesture recognition, and potential applications.

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