Eye tracking system using particle filters
Ricardo Rezende Campos, Cristina P. Santos, João Silva Sequeira · 2013
The process of eye tracking has been subject of intensive research during the last years. The main aim consists in the determination of the point of gaze or the eye movement relative to the head. In this work, we use a static video camera to realize the tracking of the eyes movement mainly due to its important features such as low cost, fully automated and easy application. The proposed approach encompasses a solution to the problems of eye detection and eye tracking. Our eye detection method employs a set of cascaded Haar classifiers that enable the fast recognition of eye regions in a real-time sequence of images. On the other hand, the eye tracking method uses particle filtering that is robust in clutter environments and allows the fusion of sensor data as well as the tracking of nonlinear systems. The results demonstrate that the eye tracking system is capable of robustly track the eyes under variable light conditions and under several different face orientations.