Lip Contour Segmentation Using Kernel Methods and Level Sets

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.

• Type: Conference
• Year: 2007
• Where: ISVC
• Authors: A. Khan, William J. Christmas, Josef Kittler
• Keywords: ISVC 2007, Mouth Contour, Non-linear Learning Method, Trained Classifier Outputs