Expression Compensation for Face Recognition Using a Polar Geodesic Representation

This paper addresses the problem of face recognition in the presence of deformation due to expressions. Facial motion is considered as an isometric mapping between surfaces, which allows preservation of geodesic distance between facial points. Subject to this assumption, we propose a novel technique which integrates 2D and 3D information to establish a new deformation invariant representation of the face. The 3D surface is used to define a polar geodesic coordinate space which is independent of the intrinsic geometry of the face. The corresponding color image is embedded in this space and serves as the recognition data. A preceding stage of hierarchical diffeomorphic grid-based image warping before the recognition process combined with a lip segmentation technique are also employed to increase the overall performance of the algorithm