Towards Improved Saccade Landing Position Estimation Using Velocity Profile Methods

Algorithms for predicting the trajectories of saccadic eye movements offer considerable potential for improving the performance of gaze-contingent rendering systems. Amongst previously introduced techniques, several methods have been proposed which involve fitting a window of trajectory data obtained at the saccade onset to a model kinematic profile. This extended abstract describes progress towards addressing limitations of recently proposed methods for profile-based predictions using eye velocity information. Namely, we explore a new model suitable for describing the known skewness of the velocity profiles of large saccades based upon the Wald distribution.