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In this paper, we propose an approach to track the progression of eye-gazewhile reading a block of text on computer screen. The proposed approach willhelp to accurately quantify reading, e.g., identifying the lines of text thatwere read/skipped and estimating the time spent on each line, based oncommercially available inexpensive eye-tracking devices. The proposed approachis based on a novel Slip Kalman filter that is custom designed to track theprogression of reading. The performance of the proposed method is demonstratedusing 25 pages eye-tracking data collected using a commercial desk-mountedeye-tracking device.

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