This paper introduces in detail artificial neural network, Kalman filters, pupil orientation and active distinguish, the 4 detection arithmetics in eye-tracking system.

Eye-Tracking technology is used in some fields like engineering psychology and human computer interaction design.

Experiment proved that this algorithm can well support real-time eye-tracking as an i.

The experiment adopted the technology of eye movement tracking and the visual search tasks,and 16 participants were tested.

To evaluate the effect of optical ablation zone decentration after LASIK with active eye tracking system.;

Referring to cortex prosthesis or optic nerve prosthesis, when conducting a mapping evaluation on simulated phosphenes, it is necessary to control the experimenters’eye movement and design an eye tracking algorithm which could track the real-time eye movements effectively.

A new real-time eye tracking algorithm is presented that works well under variable and realistic lighting conditions and various face orientations.

The main works of eye detection, eye feature extraction and eye tracking presented in this paper are as follows:Eye detection and eye feature extraction under visible light condition:After face detection using Adaboost face classifier, we detection eyes in region corresponds to the first rectangular feature of AdaBoost face classifier using AdaBoost eye classifier.

The development and application of eye tracking technology are discussed in this paper.

In order to resolve the problem of fast head moving,nonlinear eye tracking and facial fatigue expression detection,a new scheme of driver fatigue detection was proposed based on unscented Kalman filter(UKF) and eye tracking.

Nonintrusive methods for eye tracking are important to locomotive driver fatigue detection.