Image processing for eye detection and classification of the gaze direction

The vision has many sensors responsible for capturing information that is sent to the brain. The gaze reflects its attention, intention and interest of the brain towards the outside world. Therefore, the detection of the gaze direction is a promising alternative for the simulation programs, virtual reality applications and human-machine special communication. Cheaper devices to capture images and increase the power processing of personal computers motivate studies that allow human-machine interactivity. The application of techniques to detect the gaze direction has the possibility of improving significantly the interaction between people with motor deficiency and personal computers. The objective of this work is to provide a system that uses techniques of digital image processing to classify the gaze direction. The results show the complexity and efficiency of a system that performs not only the acquisition of images but also their classification by using artificial neural networks.