Iris Detection for Gaze Tracking Using Video Frames

The computation of gaze direction is important in modern interactive systems. The displays in real-time monitoring systems depend on spatial and temporal characteristics of eye movement. Research studies indicate the requirement for efficient and novel techniques in human computer interaction. A strong need for gaze tracking methods that eliminate initial setup and attune procedure is required. The pupil, iris and eye corners provide parametric data to determine gaze direction. Gaze tracking algorithm is initiated by iris localization. The approach of iris detection using frames captured from the video is significant for feature based gaze tracking. In this paper, the procedures for face and eye detection in visible light are discussed. The novel method discussed in this paper identify single face image appropriate for gaze tracking by elimination of multiple and non-face images. Iris detection is performed using Hough gradient method. The correctness rate of iris detection obtained is 95%.