3D Facial Expression Reconstruction from Video via SFM and Dynamic Texture Mapping

We propose an automatic approach to reconstruct realistic 3D facial expressions from un-calibrated monocular video sequences with little constraint.By the approach,the affine rectified optical flow method is first used to track facial features automatically aligned with ASM algorithm in the first frame.Secondly,3D personalized face model and 3D expressions are reconstructed by shape from motion algorithm with the help of a generic face.At last,dynamic texture mapping is applied instead of traditional static texture mapping to generate more realistic facial appearance.Furthermore,eigenface based image compression method is adopted to save the storage space while the image quality is well maintained.Experiments show that our approach can be applied to generate quite realistic 3D facial expressions while keeping high performance in both time and space domains.