Locating and Tracking Facial Landmarks Using Gabor Wavelet Networks

A new approach for locating and tracking facial landmarks in video sequences is introduced in this paper. Our method is based on Gabor wavelet networks, an effective technique that represents a discrete face template as a linear combination of 2D Gabor wavelet functions. This wavelet representation allows positioning of facial landmarks (e.g. eyes, nose and mouth), even in the presence of glasses, beard and different facial expressions. The feature tracking is robust to homogeneous illumination changes and affine deformations of the face image. Moreover, the tracking appraoch considers the overall geometry of the face, thus being robust to deformations such as eye blinking and smile, which is usually a critical situation to most local-based traditional methods.

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