Abstract
The prediction of eye direction detection is the one of the popular research topic in human computer interaction area. This paper defines eye gaze detection by using Discrete Cosine Transform. Actually, determining the position of eyes is difficult to estimate the location of gaze which is more challenging. The database of the suggested research is organized as gaze directions of right, left and centre. The database is created with varied ages of images. In this paper, Discrete Cosine Transform has been applied to the image database and the effect of image compression is tested by using back propagation neural networks.
Highlights
In human body, every organ has its own importance, eyes provide communication with the world [1]
With the development of techniques, like virtual reality and human computer interaction (HCI), gaze tracking support that it is very useful in practical applications [2]
The nature of eye movements has been considered like a biometric pattern in some HCI researches [5,6]
Summary
Every organ has its own importance, eyes provide communication with the world [1]. In researcher's work area, the direction of eye is estimated and classified by using different techniques in recent years. Monitoring of eye-gaze movements is frequently studied on HCI, usability testing, visual systems, psychology and many other areas. The nature of eye movements has been considered like a biometric pattern in some HCI researches [5,6]. Three different approaches are used for monitoring eye gaze and eye movements detection. These are user views from normal sensor cameras using image processing techniques on image based methods or to the skin region around the eye based on the measurement of electric field with sensors installed with electro holographic methods or infrared light source [7]. Purpose of this research is just focusing on obtaining real gaze positioning
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