Markerless Reconstruction and Synthesis of Dynamic Facial Expressions
In this paper we combine methods from the field of computer vision with surface editing techniques to generate animated faces, which are all in full correspondence to each other. The inputs for our system are synchronized video streams from multiple cameras. The system produces a sequence of triangle meshes with fixed connectivity, representing the dynamics of the captured face. By carefully taking all requirements and characteristics into account we decided for the proposed system design: We deform an initial face template using movements estimated from the video streams. To increase the robustness of the reconstruction, we use a morphable model as a shape prior to initialize a surfel fitting technique which is able to precisely capture face shapes not included in the morphable model. In the deformation stage, we use a 2D mesh-based tracking approach to establish correspondences over time. We then reconstruct positions in 3D using the same surfel fitting technique, and finally use the reconstructed points to robustly deform the initially reconstructed face.
This paper is an extended version of our paper "Markerless Reconstruction of Dynamic Facial Expressions" which was published 2009 at 3-D Digital Imaging and Modeling. Besides describing the reconstruction of human faces in more detail we demonstrate the applicability of the tracked face template for automatic modeling and show how to use deformation transfer to attenuate expressions, blend expressions or how to build a statistical model, similar to a morphable model, on the dynamic movements.