AN ALGORITHM TO COUNTERACT EYE JITTER IN GAZE-CONTROLLED INTERFACES

Abstract

One of the major concerns in developing efficient gaze-controlled user interfaces is inherent eye jitter, which presents a key limitation on the pointing accuracy achievable with an eye tracker. To counteract eye jitter, we developed a grab-and-hold algorithm. The efficiency of the algorithm was tested experimentally in a target acquisition task. Results suggest that the grab-and-hold algorithm affords a dramatic 57% reduction in error rates overall. The reduction is as much as 68% for targets subtending 0.35 degrees of visual angle. However, there is a cost which surfaces as a slight increase in movement time (10%). These findings indicate that measures like the algorithm presented here have the potential of making eye gaze a more suitable input modality.