Hybrid Eye-Tracking on a Smartphone with CNN Feature Extraction and an Infrared 3D Model.

This paper describes a low-cost, robust, and accurate remote eye-tracking system that uses an industrial prototype smartphone with integrated infrared illumination and camera. Numerous studies have demonstrated the beneficial use of eye-tracking in domains such as neurological and neuropsychiatric testing, advertising evaluation, pilot training, and automotive safety. Remote eye-tracking on a smartphone could enable the significant growth in the deployment of applications in these domains.

Accurate Model-Based Point of Gaze Estimation on Mobile Devices.

The most accurate remote Point of Gaze (PoG) estimation methods that allow free head movements use infrared light sources and cameras together with gaze estimation models. Current gaze estimation models were developed for desktop eye-tracking systems and assume that the relative roll between the system and the subjects' eyes (the 'R-Roll') is roughly constant during use. This assumption is not true for hand-held mobile-device-based eye-tracking systems.