Lip Posture Estimation using Kinematically Constrained Mixture Models
P. H. Kelly, E. A. Hunter, K. Kreutz-Delgado, R. Jain
Center for Information Engineering
Dept. of Electrical and Computer Engineering
University of California
San Diego M/C 04079500 Gilman Dr. La Jolla
CA 92093 USA
A novel approach for estimating 3D lip posture from monocular video sequences is presented. The lips are modeled as a four body closed kinematic chain with each body possessing translational, rotational and prismatic (to account for deformations) degrees of freedom. Geometric constraints relating these bodies to each other, and to the face as a whole, are used to constrain the space of possible lip postures recovered from each image. These constraints are used with the recently proposed Expectation Constrained Maximization algorithm to estimate the lip posture from video frames that have been processed (using a color segmentation algorithm described here) to identify lip regions.
Keywords:
Face Tracking and Analysis, EM Algorithm, Mixture Models, Video Analysis, Kinematic Constraints
