Hand-held portable devices have received only little attention as a platform in the eye tracking community so far. This is mainly due to their -- until recently -- limited sensing capabilities and processing power. In this work-in-progress paper we present the first prototype eye gesture recognition system for portable devices that does not require any additional equipment. The system combines techniques from image processing, computer vision and pattern recognition to detect eye gestures in the video recorded using the built-in front-facing camera. In a five-participant user study we show that our prototype can recognise four different continuous eye gestures in near real-time with an average accuracy of 60% on an Android-based smartphone (17.6% false positives) and 67.3% on a laptop (5.9% false positives). This initial result is promising and underlines the potential of eye tracking and eye-based interaction on portable devices.
['Vytautas Vaitukaitis', 'Andreas Bulling']
Eye gesture recognition on portable devices