Estimating Gaze Duration Error with Eye Tracking Data
Published in , 2023
Recommended citation: Hawkins, John. (2023) "Estimating Gaze Duration Error with Eye Tracking Data" Proceedings of the 2023 5th International Conference on Image, Video and Signal Processing Pages 70-75, Mar 25, 2023
Abstract
Eye tracking applications produce a series of gaze fixation points that can be attributed to objects within a subject’s field of vision. Error is typically measured on the basis of individual gaze fixation point measurements. These applications are often used to infer a gaze duration metric from a series of fixation measurements. There is no direct method for inferring the error in a gaze duration measurement from an error in fixation points.
In this work we develop an algorithm for estimating the error distribution of gaze duration measurement through Monte Carlo simulation using the content of an eye tracking calibration log file. We provide this algorithm in an open source application to allow researchers to understand the error in their gaze duration measurements. We use this application to conduct experiments on the expected error bounds for different duration measurements across a fixed session length for a simulated advertising area of interest study on a mobile device. The results indicate that error in gaze duration estimation is sensitive to fixation error beyond a bound that will depend on the size of interest and the session length.