Improving the Usability of Remote Eye Gaze Tracking for Human-Device Interaction

Abstract

This paper presents a novel single-point calibration-based remote eye gaze tracking (REGT) method. The proposed method consists primarily of two steps. First, a user calibration database (UCDB) that contains user-specific data associated with multiple calibration points (CPs) is constructed for a certain number of users. Second, for new users, the candidate calibrated data are retrieved from the UCDB by simply requesting the users to look at a single CP on the screen center (SC). Experimental results show that the proposed REGT method with single-point calibration demonstrates a highly competitive accuracy compared with conventional methods employing multipoint calibration.(1)