Accurate Face Reconstruction through Anisotropic Fitting and Eye Correction

Abstract

Fitting a facial template model to 3D-scanner data is a powerful technique for generating face avatars, in particular in the presence of noisy and incomplete measurements. Consequently, there are many approaches for the underlying non-rigid registration task, and these are typically composed from very similar algorithmic building blocks. By providing a thorough analysis of the different design choices, we derive a face matching technique tailored to high quality reconstructions from high resolution scanner data. We then extend this approach in two ways: An anisotropic bending model allows us to more accurately reconstruct facial details. A simultaneous constrained fitting of eyes and eye lids improves the reconstruction of the eye region considerably.