Lip segmentation with the presence of beards

Lip image analysis has attracted much interest in recent years because some important speech information is contained in the shape and movement of the lip. To extract such information from the images, accurate and robust lip region segmentation is of vital importance. However, most of the current lip segmentation methods fail to provide accurate results if the person has a beard. We propose a "one object, multiple background" clustering method to solve the problem. Since the non-lip region becomes inhomogeneous in the presence of a beard, multiple background clusters can produce better fitting to a rather complex background region than a single cluster. Spatial information in terms of the physical distance towards the lip center is incorporated to enhance the differentiation between the lip and background region. Experimental results demonstrate that our algorithm provides accurate lip segmentation results for images with beards.