Statistical estimators for use in automatic lip segmentation

The past decade has seen a considerable increase in interest in the field of facial feature extraction. The primary reason for this is the variety of uses, in particular of the mouth region, in communicating important information about an individual which can in turn be used in a wide array of applications. The shape and dynamics of the mouth region convey the content of a communicated message, useful in applications involving speech processing as well as man-machine user interfaces. The mouth region can also be used as a parameter in a biometric verification system. Extraction of the mouth region from a face often uses lip contour processing to achieve these objectives. Thus, solving the problem of reliably segmenting the lip region given a talking face image is critical. This paper compares the use of statistical estimators, both robust and non-robust, when applied to the problem of automatic lip region segmentation. It then compares the results of the two systems with a state-of-the art method for lip segmentation.