Three-Dimensional Head Tracking and Facial Expression Recovery Using an Anthropometric Muscle-Based Active Appearance Model

This paper describes a novel 3-D model-based tracking algorithm allowing the real-time recovery of 3-D position, orientation, and facial expressions of a moving head. The method uses a 3-D anthropometric muscle-based active appearance model (3-D AMB AAM), a feature-based matching algorithm, and an extended Kalman filter (EKF) pose and expression estimator. Our model is an extension of the classical 2-D AAM and uses a generic 3-D wireframe model of the face based on two sets of controls: the anatomically motivated muscle actuators to model facial expressions and the statistically based anthropometrical controls to model different facial types.