Eyes are the most important features of the human face. So effective usage of eye movements as a communication technique in user-to-computer interfaces can find place in various application areas.Eye tracking and the information provided by the eye features have the potential to become an interesting way of communicating with a computer in a human-computer interaction (HCI) system. So with this motivation, designing a real-time eye feature tracking software is the aim of this project.So far there has been a lot of work on eye detection and before the project, the previous methods were carefully studied to determine the implemented method. We can classify studies related to eye into two main categories as listed below:
Special Equipment Based Approaches

These type of studies use the necessary equipment which will give a signal of some sort which is proportional to the position of the eye in the orbit. Various methods that are current in use are Electrooculography, Infra-Red Oculography, Scleral search coils. These methods are completely out of our project.
Image Based Approaches

Image based approaches perform eye detections on the images. Most of the image based methods try to detect the eyes using the features of the eyes. Methods used so far are knowledge-based methods, feature-based methods (color, gradient), simple template matching, appearance methods. Another interesting method is Deformable template matching which is based on matching a geometrical eye template on an eye image by minimizing the energy of the geometrical model.The implemented project is on three components:
Face detection: Performs scale invariant face detection
Eye detection: Both eyes are detected as a result of this step
Eye feature extraction: Features of eyes are extracted at the end of this step
Face Detection

Two different methods were implemented in the project. They are:
Continuously Adaptive Means-Shift Algorithm
Haar Face Detection method..