Abstract
A key issue with state-of-the-art mobile eye trackers, particularly
during long-term recordings in daily life, is the need for cumbersome
and time consuming (re)calibration. To reduce this burden, in this
paper we investigate the feasibility of adapting the calibration
obtained for one user to another. Calibration adaptation is automatically
performed using a light-weight linear translation. We compare three
different methods to compute the translation: "multi-point", where
all calibration-points are used, "1-point", and "0-point" that uses
only an external parameter. We evaluate these methods in a 6-participant
user study in a controlled laboratory setting by measuring the error
in visual angle between the predicted gaze point and the true gaze
point. Our results show that, averaged across all participants, the
best adapted calibration is only 0.8\textdegree (mean) off the
calibration obtained for that specific user. We also show the potential
of the 1-point and 0-point methods compared to the time-consuming
multi-point computation.
