We present a statistical, colour-based technique for lip tracking intended to support personal verification. The lips are automatically localised in the original image by exploiting grey-level gradient projections as well as chromaticity models to find the mouth area in an automatically segmented region corresponding to the face area. A B-spline, initially with an elliptic shape is then generated to start up tracking. Tracking proceeds by estimating new lip contour positions according to a statistical chromaticity model for the lips. These measurements are used together with a Lagrangian formulation of contour dynamics to update the new spline control points. The method has been tested on the M2VTS database, where lips were accurately tracked on sequences of speaking subjects consisting of more than hundred frames. The tracker can be used to perform feature extraction from the mouth area as well as for model detection for personal verification applications.
['M. U. Ramos Sánchez', 'J. Matas', 'Josef Kittler']
Statistical chromaticity-based lip tracking with B-splines