Can we beat the mouse with MAGIC?
Ribel Fares, Shaomin Fang, Oleg V. Komogortsev · 2013
MAGIC pointing techniques combine eye tracking with manual input. Since the mouse performs exceptionally well in a desktop setting, previous research on MAGIC pointing either resulted in minor improvements, or the techniques were applied to alternative devices or environments. We design Animated MAGIC, a novel, target-agnostic MAGIC pointing technique, for the specific goal of beating the mouse in a desktop setting. To improve the eye-tracking accuracy, we develop a dynamic local calibration method that uses each selection as a local calibration point. We compare Animated MAGIC to mouse-only and Conservative MAGIC, one of the two original MAGIC pointing methods, in a Fitts' Law experiment. We conduct a user questionnaire to evaluate the usability of the interaction methods. Results suggest that Dynamic Local Calibration improves eye-tracking accuracy and, consequently, MAGIC pointing performance. Powered with Dynamic Local Calibration, Animated MAGIC outperformed mouse-only by 8% in terms of throughput. Both MAGIC pointing methods reduced the amount of hand movement by more than half.