Abstract:
The direction of a person’s eye gaze is a critical information. In our research
presented the estimating of a person’s eye gaze tracking by our system using both head
and eye cues which helps in a number of applications such as estimating the maturity
level of a driver by estimating eye gaze fixations. Observing the concentration level of
students during live classes, Detecting interest level of people while watching
advertisements. To accomplished this research we divide our work into small parts
such as we first extract features of image using computer vision and digital images
processing concepts which include some major techniques such as template matching,
eye comer detection, handled noise in iipages and tried to smooth the image in order
to reduce noise with the help of different filters.. After feature detection we created our
model :with the help of machine learning with data set of eye gaze which gives
gaze coordinates, eye lid difference, horizontal and vertical head movement fetched
from the camera. Finally, in the.end we.test and evaluated our results and improved
system accuracy according to the results.
