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InvisibleEye: Fully Embedded Mobile Eye Tracking Using Appearance-Based Gaze Estimation

Julian Steil, Marc Tonsen, Yusuke Sugano, Andreas Bulling

ACM SIGMOBILE Mobile Computing and Communications Review, 23(2), pp. 30-34, 2019.


Abstract

Despite their potential for a range of exciting new applications, mobile eye trackers suffer from several fundamental usability problems. InvisibleEye is an innovative approach for mobile eye tracking that uses millimetre-size RGB cameras that can be fully embedded into normal glasses frames, as well as appearance-based gaze estimation to directly estimate gaze from the eye images. Through evaluation on three large-scale, increasingly realistic datasets, we show that InvisibleEyes can achieve a person-specific gaze estimation accuracy of up to 2.04° using three camera pairs with a resolution of only 3x3 pixels.

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BibTeX

@article{steil19_sigmobile, author = {Steil, Julian and Tonsen, Marc and Sugano, Yusuke and Bulling, Andreas}, title = {InvisibleEye: Fully Embedded Mobile Eye Tracking Using Appearance-Based Gaze Estimation}, journal = {ACM SIGMOBILE Mobile Computing and Communications Review}, year = {2019}, volume = {23}, number = {2}, pages = {30-34} }