CamType: assistive text entry using gaze with an off-the-shelf webcam

Abstract

As modern assistive technology advances, eye-based text entry systems have been developed to help a subset of physically challenged people to improve their communication ability. However, speed of text entry in early eye-typing system tends to be relatively slow due to dwell time. Recently, dwell-free methods have been proposed which outperform the dwell-based systems in terms of speed and resilience, but the extra eye-tracking device is still an indispensable equipment. In this article, we propose a prototype of eye-typing system using an off-the-shelf webcam without the extra eye tracker, in which the appearance-based method is proposed to estimate people’s gaze coordinates on the screen based on the frontal face images captured by the webcam. We also investigate some critical issues of the appearance-based method, which helps to improve the estimation accuracy and reduce computing complexity in practice. The performance evaluation shows that eye typing with webcam using the proposed method is comparable to the eye tracker under a small degree of head movement.