Smartphone eye tracking toolbox: accurate gaze recovery on mobile displays

Abstract

Human Interaction with mobile devices has recently been estab-lished as application field in eye tracking research. Current technologies for gaze recovery on mobile displays cannot enable fully natural interaction with the mobile device: users are condi-tioned to interact with tightly mounted displays or distracted by markers in their view. We propose a novel approach that cap-tures point-of-regards (PORs) with eye tracking glasses (ETG) and then uses computer vision methodology for the robust local-ization of the smartphone in the head camera video. We present an integrated software package, i.e., the Smartphone Eye Track-ing Toolbox (SMET) that enables accurate gaze recovery on mobile displays with heat mapping of recent attention. We re-port the performance of the computer vision approach and demonstrate it with various natural interaction scenarios using the SMET Toolbox, enable ROI settings on the mobile display and show results from eye movement analysis, such as, ROI dwell time and statistics on eye gaze event (saccades, fixations).