[2018]
Smooth-i: smart re-calibration using smooth pursuit eye movements
Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications (ETRA 2018)
Smooth-i is an algorithm that stores gaze calibration points and updates them incrementally when inaccuracies are identified. Smooth-i uses motion matching of smooth pursuit eye movements and known motion on the display to determine when there is a drift in accuracy and use it as input for re-calibration. The aim of the project was to solve the dependency on calibration for eye gaze interaction that can deteriorate over time and affect the usability of the system.
Results on a user study show that Smooth-i is able to manage re-calibration efficiently, updating the calibration profile only when inaccurate data samples are detected.
Authors Team: Argenis Ramírez Gómez, Hans Gellersen