A new method to estimate rotation angle of a 3D eye model from single camera

Abstract

A challenge of current research concerning eye motion estimation is to estimate motion of a three-dimensional (3D) eye model from a two-dimensional (2D) eye image. This paper proposed a new method to estimate rotation angle of 3D eye model from a 2D eye image by angular orientation identification technique. Real eye movement is captured from a camera mounting on a side of a binocular. A camera focuses on an eye. This method consists of three steps: 1) pupil extraction from a 2D image, 2) ellipse fitting technique, and 3) angular orientation identification. First, 3D eye model orients related real 2D eye image movement. Pupil is extracted to measure its shape in second step. Second, ellipse fitting technique is used to construct complete shape of pupil. Lengths of major and minor axis are computed from ellipse shape. Finally, angular orientation of 3D eye is estimated from major and minor axis length. Rotation angle is defined from lookup table of lengths of ellipse axis and rotation angle. To evaluate the estimation model, computational result will be compared with manual measurement. Rotation angle is varied from -50 degrees to +50 degrees in yaw and roll axis with step of three degrees. Precision of the mathematical model to simulate 3D eye model orientation in roll and yaw direction are 99.53% and 99.29%, respectively. The advantage of this method over other methods is that eye motion in 3D space can be estimated from only one camera.