Kalman filtering in the design of eye-gaze-guided computer interfaces

In this paper, we design an Attention Focus Kalman Filter (AFKF) - a framework that offers interaction capabilities by constructing an eye-movement language, provides real-time perceptual compression through Human Visual System (HVS) modeling, and improves system's reliability. These goals are achieved by an AFKF through identification of basic eye-movement types in real-time, the prediction of a user's perceptual attention focus, and the use of the eye's visual sensitivity function and eye-position data signal de-noising.