Real-time iris detection on rotated faces

Abstract

Real-time face and iris detection on video sequences has been used to study the eye function and in diverse applications such as drowsiness detection, virtual keyboard interfaces, face recognition and multimedia retrieval. A non-invasive real time iris detection method was developed and consists of three stages: coarse face detection, fine face detection and iris detection. Anthropometric templates are used in these three stages. Elliptical templates are used to locate the coarse face center. A set of anthropometric templates which are probabilistic maps for the eyebrows, nose and mouth are used to perform the fine face detection. Face rotations are considered by rotating the anthropometric templates in fixed angles in steps of 10 degrees. Iris position is then determined within the eye region using another template with concentric semi-circles to compute a line integral in the boundary iris-sclera. The position with the maximum value indicates the iris center. The new method was applied on 10 video sequences, with a total of 6470 frames, from different people rotating their faces in the coronal axis. Results of correct face detection on 8 video sequences was 100%, one reached 99.9% and one 98.2%. Results on correct iris detection are above 96% in 9 of the video sequences and one reached 77.8%. The method was implemented in real-time (30 frames per second) with a PC 1.8 GHz.