GazeLib: A Low Cost Implementation of Real-time Gaze Tracking Framework

Abstract

Eye gaze reflects a person’s attention over time, which is a powerful cue for determining what might be interesting. Therefore, eyes have not only indispensable meaning for human communication, but also great potential to build human computer interaction in a more natural and direct mode. Ironically, most available gaze trackers are either driven by specific design operating software or high end hardware. High costs have always been the barrier prohibiting wide spread of gaze tracking technology. Moreover, the majority gaze trackers are adopted corneal reflection tracking technique which actively illuminates the eye region by infrared light requiring quasi-stable lighting conditions to operate. In addition, potential eye hazards maybe arise from long period or close proximity IR exposure. To solve these problems, a robust hybrid method integrates model and feature based tracking approaches is proposed in this project. The core of the proposed method is applying Active Shape Model fitting technique to locate facial features. Eye features are then extracted by sophisticated image processing including filtering and eclipse fitting. Towards a framework available to public, the proposed framework is packed in programming library and available in an open-source package.Evaluation experiments show that system prototype is capable to perform real-time remote gaze tracking under several lighting conditions with low-cost and off-the-shelf webcams while maintaining acceptable accuracy.The proposed method has significantly improved the usability, reduced the cost of using gaze tracking technology, which is an important step to make it enter the mass market.