Online Modeling and Tracking of Pose-Varying Faces in Video
We propose a face mosaicing approach to model both the facial appearance and geometry from pose-varying videos, and apply it in face tracking and recognition. The basic idea is that by approximating the human head as a 3D ellipsoid, multi-view face images can be back projected onto the surface of the ellipsoid, and the surface texture map is decomposed into an array of local patches. During the online modeling process, the position and pose of the first frame is assumed to be known for a given video sequence. For each frame in the sequence, the algorithm estimates the face-position and pose, and generates a texture map, which is further utilized in updating the mosaic model.