Usability evaluation of eye tracking on an unmodified common tablet

Authors:
Corey Holland;Atenas Garza;Elena Kurtova;Jose Cruz;Oleg Komogortsev
Affiliations:
Texas State University, San Marcos, USA;Texas State University, San Marcos, USA;Texas State University, San Marcos, USA;Texas State University, San Marcos, USA;Texas State University, San Marcos, USA
Venue:
CHI '13 Extended Abstracts on Human Factors in Computing Systems
Year:
2013

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Abstract

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.