Morphable Models for Training a Component-based Face Recognition System

In this chapter we present a system for face recognition that combines two recent advances in computer graphics and computer vision: 3D morphable models and component-based recognition. By fitting a morphable model to a triplet of face images we generate a 3D head model for each person in our face database. The 3D models are rendered under varying pose and illumination conditions to build a large set of synthetic images. We then train a component-based face recognition system on these synthetic images. At runtime, the face recognition module is preceded by a hierarchical face detector resulting in a system that can detect and identify faces in video images at about 4 Hz. The system achieved a recognition rate which was significantly higher than that of a comparable global face recognition system trained on the same data. Finally, we address the problem of how to automatically determine the size and shape of facial components for face identification. 0.