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This paper presents a method to detect the eye shape using recurrent neural network. The key idea is to train a recurrent neural network to detect the eye contour in an eye image. The eye image is decomposed into a series of eye profiles using Log-polar transform. An eye profile exists and contains a part of the eye contour. The eye profile is considered as a time series signal. A recurrent neural network is trained to predict the locations of the eye contour based on some inputs and some previous output statuses. The experimental results verified that the recurrent network is able to detect the eye shape under different lighting conditions, scales and rotations angles. Moreover, the proposed method outperforms the conventional methods in high accuracy and low detection time.

Eye Shape Detection in Log-Polar Domain Using Recurrent Neural Network