Numerical recipes: the art of scientific computing
Numerical recipes: the art of scientific computing
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking and Learning Graphs on Image Sequences of Faces
ICANN 96 Proceedings of the 1996 International Conference on Artificial Neural Networks
Detection and Tracking of Facial Features in Video Sequences
MICAI '00 Proceedings of the Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Affine Real-Time Face Tracking Using a Wavelet Network
RATFG-RTS '99 Proceedings of the International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
A graphical model based solution to the facial feature point tracking problem
Image and Vision Computing
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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.