Usability evaluation of eye tracking on an unmodified common tablet
Corey D. Holland, Atenas Garza, Elena Kurtova, Jose F. De la Cruz, Oleg V. Komogortsev · 2013
This paper describes the design, implementation, and usability evaluation of a neural network based eye tracking system on an unmodified common tablet and discusses the challenges and implications of neural networks as an eye tracking component on a mobile platform. We objectively and subjectively evaluate the usability and performance tradeoffs of calibration, one of the fundamental components of eye tracking. The described system obtained an average spatial accuracy of 3.95° and an average temporal resolution of 0.65 Hz during trials. Results indicate that an increased neural network training set may be utilized to increase spatial accuracy, at the cost of greater physical effort and fatigue.