Estimation of user interest using time delay features between proactive content presentation and eye movements

Abstract

Human-machine interaction still lacks smoothness and naturalness despite the widespread utilization of intelligent systems and emotive agents. In order to improve the interaction, this work proposes an approach to estimate user's interest based on the relationships between dynamics of user's eye movements, more precisely the endogenous control mode of saccades, and machine's proactive visual content presentation. Under a specially-designed presentation phase to make the user express the endogenous saccades, we analyzed delays between the saccades and the presentation events. As a result, we confirmed that the delay while the user's gaze is maintained on the previous presented content regardless of the next event, called resistance, is a good indicator of the interest estimation (70% success, upon 20 experiments). It showed higher accuracy than the conventional interest estimation based on gaze duration.