Eyes Segmentation Applied to Gaze Direction and Vigilance Estimation

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Abstract

An efficient algorithm to iris segmentation and its application to automatic and non-intrusive gaze tracking and vigilance estimation is presented and discussed. A luminance gradient technique is used to fit the irises from face images. A robust preprocessing which mimics the human retina is used in such a way that a robust system to luminance variations is obtained and contrast enhancement is achieved. The validation of the proposed algorithm is experimentally demonstrated by using three well-known test databases: the FERET database, the Yale database and the Cohn-Kanade database. Experimental results confirm the effectiveness and the robustness of the proposed approach to be applied successfully in gaze direction and vigilance estimation.