The 3D face analyzer project targets at reliable recognition of facial attributes on 2.5D or 3D face models, thus making use of face shape, texture and landmarks at the same time. While developing 3D analysis-based techniques directly aiming at recognition of facial attributes, we also want to make forward knowledge on some underlying fundamental issues, e.g. stability of discrete geometric measures and descriptions (curvature, distance, etc.) across variations in terms of model resolution and precision, 3D non-rigid surface registration and matching in the presence of noisy data. Another important aim of the project is the collection of significantly representative datasets of 3D face models in facial expressions, age and gender for the purpose of training and testing.