Evaluation of implicit 3D modeling for pose invariant face recognition

In this paper, we describe and evaluate an approach that uses implicit models of facial features to cope with the problem of recognizing faces under varying pose. The underlying recognition process attaches a parameterized model to every enrolled image that allows the parameter controlled transformation of the stored biometric template into miscellaneous poses within a wide range. We also propose a method for accurate automatic landmark localization in conjunction with pose estimation, which is required by the latter approach. The approach is extensible to other problems in the domain of face recognition for instance facial expression. In the experimental section we present an analysis with respect to accuracy and compare the computational effort with the one of a standard approach.