Contour Tracking in Clutter: A Subset Approach
International Journal of Computer Vision
Adaptive mouth segmentation using chromatic features
Pattern Recognition Letters
Effective Tracking through Tree-Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic lip contour extraction from color images
Pattern Recognition
Lip contour segmentation using kernel methods and level sets
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Lip reading based on sampled active contour model
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
A local region based approach to lip tracking
Pattern Recognition
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This paper describes a novel approach for visual speech recognition. The shape of the mouth is modelled by an active shape model which is derived from the statistics of a training set and used to locate, track and parameterise the speaker's lip movements. The extracted parameters representing the lip shape are modelled as continuous probability distributions and their temporal dependencies are modelled by hidden Markov models. We present recognition tests performed on a database of a broad variety of speakers and illumination conditions. The system achieved an accuracy of 85.42% for a speaker independent recognition task of the first four digits using lip shape information only.