Characterizing the Influence of Motion Parameters on Performance when Acquiring Moving Targets
Abstract
Current pointing techniques provide no adequate way to select very small objects whose movements are fast and unpredictable, and theoretical tools –such as Fitts' law– do not model unpredictable motion. To inform the design of appropriate selection techniques, we studied how users performed when selecting moving objects in a 2D environment. We propose to characterize selection performance as a function of the predictability of the moving targets, based on three parameters: the speed (S) of the target, the frequency (F) at which the target changes direction, and the amplitude (A) of those direction changes. Our results show that for a given speed, selection is relatively easy when A and F are both low or high, and difficult otherwise.
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