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This paper presents a method to detect the eye contour using recurrent neural network. Log-Polar transform is used to convert the changes of eye rotation and scales into translations. Principal component analysis is applied on the eye RGB color channels in order to obtain a stable texture representation regardless lighting conditions. A recurrent neural network is trained to discern the patterns of the texture values around the eye contour as well as to model the eye contour appearance with different eye states. The experimental results have verified that the recurrent network is able to detect the eye contour robustly. The proposed method outperforms the conventional methods in terms of accuracy and detection time.

Eye Shape Detection Based on Texture Modeling in Log-Polar Domain Using Principal Component Analysis and Recurrent Neural Network