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We propose a system that is capable of detailed analysis of eye region images in terms of the position of the iris, degree of eyelid opening, and the shape, complexity, and texture of the eyelids. The system uses a generative eye region model that parameterizes the fine structure and motion of an eye. The structure parameters represent structural individuality of the eye, including the size and color of the iris, the width, boldness, and complexity of the eyelids, the width of the bulge below the eye, and the width of the illumination reflection on the bulge. The motion parameters represent movement of the eye, including the up-down position of the upper and lower eyelids and the 2D position of the iris. The system first registers the eye model to the input in a particular frame and individualizes it by adjusting the structure parameters. The system then tracks motion of the eye by estimating the motion parameters across the entire image sequence. Combined with image stabilization to compensate for appearance changes due to head motion, the system achieves accurate registration and motion recovery of eyes.
Computer vision, facial image analysis, facial expression analysis, generative eye region model, motion tracking, texture modeling, gradient descent.

T. Moriyama, T. Kanade, J. F. Cohn and J. Xiao, "Meticulously Detailed Eye Region Model and Its Application to Analysis of Facial Images," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 28, no. , pp. 738-752, 2006.
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