Event driven Camera based Eye Tracking

This study proposes a general diagnostic approach based on a camera based eye-tracking technique and a discrete Kalman filter as an iris tracker. In an event driven scenario, the proposed iris-tracking method is used to locate and track the subject’s eye movement and gesture by comparing it to a set of classified normal and typical gestures. The database is based on available videos as well as a number of experiments conducted with normal subjects. Proposed approach Utilized feature based methods of face, such as skin color while detection of the eyes utilized a histogram-based approach and SVM was used as a two-class classifier to divide region into eyes and noneyes patterns. Based on the results, the proposed approach provide an efficient eye detection and tracking method with an average of 99.1% accuracy. KEYWORD Eye detection, Iris tracking, Kalman filter.