A neural network based real-time gaze tracker

Authors:
Nischal M. Piratla;Anura P. Jayasumana
Affiliations:
Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO;Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO
Venue:
Journal of Network and Computer Applications
Year:
2002

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Abstract

A real-time gaze-tracking system that estimates the user's eye gaze and computes the window of focused view on a computer monitor has been developed. This artificial neural network based system can be trained and customized for an individual. Unlike existing systems in which skin color features and/or other mountable equipment are needed, this system is based on a simple non-intrusive camera mounted on the monitor. Gaze point is accurately estimated within a 1 in. on a 19-in. monitor with a CCD camera having a 640 × 480 image resolution. The system performance is independent of user's forward and backward as well as upward and downward movements. The gaze-tracking system implementation and the factors affecting its performance are discussed and analyzed in detail. The features and implementation methods that make this system real-time are also explained.