Calibration-Free Eye Gaze Direction Detection with Gaussian Processes

In this paper we present a solution for eye gaze detection from a wireless head mounted camera designed for children aged between 6 months and 18 months. Due to the constraints of working with very young children, the system does not seek to be as accurate as other state-of-the-art eye trackers, however it requires no calibration process from the wearer. Gaussian Process Regression and Support Vector Machines are used to analyse the raw pixel data from the video input and return an estimate of the child's gaze direction. A confidence map is used to determine the accuracy the system can expect for each coordinate on the image. The best accuracy so far obtained by the system is 2.34$^{circ}$ on adult subjects, tests with children remain to be done.