A Novel Slip-Kalman Filter to Track the Progression of Reading Through Eye-Gaze Measurements

Abstract

In this paper, we propose an approach to track the progression of eye-gaze while reading a block of text on computer screen. The proposed approach will help to accurately quantify reading, e.g., identifying the lines of text that were read/skipped and estimating the time spent on each line, based on commercially available inexpensive eyetracking devices. The proposed approach is based on a novel slip Kalman filter that is custom designed to track the progression of reading. The performance of the proposed method is demonstrated using 25 pages eyetracking data collected using a commercial desk-mounted eye-tracking device.

On validating a generic camera‐based blink detection system for cognitive load assessment

“…A remote Gazepoint GP3 eye-tracker (Gazepoint Inc., Vancouver, BC, Canada) with data collection frequency of 60 Hz was used. Previous research shows this as a reliable tool for desktop-based eye-tracking [30][31][32]. The eye-tracker has a graphical user interface which was used for the calibration process.…”