3D head model fitting evaluation protocol on synthetic databases for acquisition system comparison

Automatic face recognition has been integrated in many systems thanks to the improvement of face comparison algorithms. One of the main applications using facial biometry is the identity authentication at border control, which has already been adopted by a lot of airports. In order to proceed to a fast identity control, gates have been developed, to extract the ID document information on the one hand, and to acquire the facial information of the user on the other hand. The design of such gates, and in particular their camera configuration, has a high impact on the output acquisitions and therefore on the quality of the extracted facial features. Since it is very difficult to validate such gates by testing different configurations on real data in exactly the same conditions, we propose a validation protocol based on simulated passages. This method relies on synthetic sequences, which can be generated using any camera configuration with fixed parameters of identities and poses, and can also integrate different lighting conditions. We detail this methodology and present results in terms of geometrical error obtained with different camera configurations, illustrating the impact of the gate design on the 3D head fitting accuracy, and hence on facial authentication performances.