Nonlinear manifold learning for visual speech recognition
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Accurate, Real-Time, Unadorned Lip Tracking
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Level Set Based Shape Prior Segmentation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Visual speech recognition using active shape models and hidden Markov models
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02
Automatic Lip Tracking: Bayesian Segmentation and Active Contours in a Cooperative Scheme
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Nonlinear color space and spatiotemporal MRF for hierarchical segmentation of face features in video
IEEE Transactions on Image Processing
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This paper proposes a novel method for segmenting lips from face images or video sequences. A non-linear learning method in the form of an SVM classifier is trained to recognise lip colour over a variety of faces. The pixel-level information that the trained classifier outputs is integrated effectively by minimising an energy functional using level set methods, which yields the lip contour(s). The method works over a wide variety of face types, and can elegantly deal with both the case where the subjects' mouths are open and the mouth contour is prominent, and with the closed mouth case where the mouth contour is not visible.