In this work, different methods are presented to create 3D face models from databases of 3D face scans. The challenge in this endeavour is to balance the limited training data with the high demands of various applications.
The 3D scans stem from various persons showing different expressions, with varying number of points per 3D scan and different numbers of scans per person. This data of posed facial expressions revealed substructures, which are utilised to improve the proposed model. In the process of creating and using the models, for each specifc application objective quality criteria are carefully designed tailored to the task to quantify the quality.
In total four face models built from three databases are compared based on: 3D face synthesis, 3D approximation, person and expression transfer, and 3D reconstruction from 2D.
