Eye-gaze tracking system by haar cascade classifier
Yunyang Li, Xin Xu, Nan Mu, Li Chen · 2016
Human can quickly and effortlessly focus on a few most interesting points in an image. Different observers tend to have the same fixations towards the same scene. In order to predict observer's fixations, eye gaze information can be used to reveal human attention and interest. This paper presents a real-time eye gaze tracking system. Haar cascade classifier is used to calculate the position of eye gaze based on the rectangular features of human eye. Then this position is adopted to match the space coordinates of screen representing where an observer is looking. The experimental results from different kinds of scenes validate the effectiveness of our system.