Idiosyncratic Feature-Based Gaze Mapping

Abstract

It is argued that polynomial expressions that are normally used for remote, video-based, low cost eye tracking systems, are not always ideal to accommodate individual differences in eye cleft, position of the eye in the socket, corneal bulge, astigmatism, etc. A procedure to identify a set of polynomial expressions that will provide the best possible accuracy for a specific individual is proposed.  It is also proposed that regression coefficients are recalculated in real-time, based on a subset of calibration points in the region of the current gaze and that a real-time correction is applied, based on the offsets from calibration targets that are close to the estimated point of regard.

It was found that if no correction is applied, the choice of polynomial is critically important to get an accuracy that is just acceptable.  Previously identified polynomial sets were confirmed to provide good results in the absence of any correction procedure.  By applying real-time correction, the accuracy of any given polynomial improves while the choice of polynomial becomes less critical.  Identification of the best polynomial set per participant and correction technique in combination with the aforementioned correction techniques, lead to an average error of 0.32° (sd = 0.10°) over 134 participant recordings.

The proposed improvements could lead to low-cost systems that are accurate and fast enough to do reading research or other studies where high accuracy is expected at framerates in excess of 200 Hz.