Fig. 3

Quantification of iTracker’s Error without and with calibration. a Error in distinguishing between gaze towards eye and mouth of a face on screen (Task 2; Fig. 1c). Points were classified by which feature they were closest to. Shown is the proportion of wrongly assigned frames for each subject. Following calibration, both accuracy and variance improve. b Results for Task 3, which was similar to Task 2, but with an enlarged face in which eyes and mouth are further apart (Figure 1d). Performance appears more variable than for Task 2, but after post-processing with the linear calibration method very good accuracy and robustness is achieved. c Participants traced out the outline of a circle (Task 4; Fig. 1e). Shown is the mean Euclidean distance between the prediction and the true outline of the circle for each subject. Again calibration reduces variance and improves accuracy