[2017]
Exploration of smooth pursuit eye movements for gaze calibration in games.
Master Thesis. Lancaster University
Eye tracking offers opportunities to extend novel interfaces and promises new ways of interaction for gameplay. However, gaze has been found challenging to use in dynamic interfaces involving motion. Moving targets are hard to select with state of the art gaze input methods and gaze estimation requires calibration in order to be accurate when offering a successful interaction experience. Smooth pursuit eye movements have been used to solve this new paradigm, but there is not enough information on the behavior of the eyes when performing such eye movement. In this work, we tried to understand the relationship between gaze and motion when performing smooth pursuit movements through the integration of calibration within a videogame. In our first study, we propose to leverage the attentive gaze behavior of the eyes during gameplay for implicit and continuous re-calibration. We demonstrated this with GazeBall, a retro-inspired version of Atari’s BreakOut game in which we continually calibrate gaze based on the ball’s movement and the player’s inevitable ocular pursuit on the ball. Continuous calibration enabled the extension of the game with a gaze-based ‘power-up’. In the evaluation of GazeBall, we show that our approach is effective in maintaining highly accurate gaze input over time, while re-calibration remains invisible to the player. GazeBall raised awareness on the lack of information about smooth pursuits for interaction. Therefore,
in our second study, we focused on gaining more understanding of the behavior of the eyes. By testing different motion directions and speeds we found anticipatory predictions during gaze trajectory that indicates that the common reaction of the eyes when a moving target is present is not only following but trying to predict and advance the displayed movement.