Real Time Eye Template Detection and Tracking

There has been a growing interest in the field of facial expression recognition especially in the last two decades. An example of such a system is the improvement of driver carefulness and accident reduction. The driver’s face is tracked while he is driving and he is warned if there seems to be an alerting fact that can result in an accident such as sleepy eyes, or looking out of the road. Furthermore, with a facial feature tracker, it becomes possible to play a synthesized avatar so that it imitates the expressions of the performer. Human-Computer Interaction (HCI) systems may also be enriched by a facial feature tracker. For a user who is incapable of using her hands, a facial expression controller may be a solution to send limited commands to a computer. Eye blinking is one of the prominent areas to solve many real world problems. The process of blink detection consists of two phases. These are eye tracking followed by detection of blink. The work that has been carried out for eye tracking only is not suitable for eye blink detection. Therefore some approaches had been proposed for eye tracking along with eyes blink detection. In this thesis, real time implementation is done to count number of eye blinks in an image sequence. At last after analyzing all these approaches some of the parameters we obtained on which better performance of eye blink detection algorithm depend. This project focuses on automatic eye blink detection in real time. The aim of this thesis is to count the number of eye blinks in a video. This project will be performed on a video database of the facial expressions.