A simultaneous estimation of rigid and non-rigid face motion

Face motion is composed of rigid motion and non-rigid motion. The rigid motion occurs from movements of the human head and the non-rigid motion derives from human's facial expression. In this paper, we present a technique for estimating these rigid/non-rigid motions of the human face simultaneously. First, we test whether the face motion is rigid. If it is rigid motion, we estimate the translation and rotation parameters over the image sequences. Otherwise, the non-rigid motion parameters based on the spring-mass damper model are estimated using optical flow. We separate the rigid motion parameters from the non-rigid parameters for parameters decoupling, so that we can estimate the face motion more accurately and more efficiently. We describe the details of our methods and show their efficacy with experiments.