Spontaneous Gaze Gesture Interaction in the Presence of Noises and Various Types of Eye Movements

Abstract

Gaze gesture is a desirable technique for a spontaneous and pervasive gaze interaction due to its insensitivity to spatial accuracy. Unfortunately, gaze gesture-based object selection utilizing correlation coefficient is prone to a low object selection accuracy due to presence of noises. In addition, effect of various types of eye movements that present in gaze gesture-based object selection has not been tackled properly. To overcome these problems, we propose a denoising method for gaze gesture-based object selection using First Order IIR Filter and an event detection method based on the Hidden Markov Model. The experimental results show that the proposed method yielded the best object selection accuracy of . The result suggests that a spontaneous gaze gesture-based object selection is feasible to be developed in the presence of noises and various types of eye movements.