Quality-Based Score Normalization and Frame Selection for Video-Based Person Authentication

This paper addresses the incorporation of quality measures to videobased person authentication. A theoretical framework to incorporate quality measures in biometric authentication is exposed. Two different quality-based score normalization techniques are derived from this theoretical framework. Furthermore, a quality-based frame selection technique and a new face image quality measure are also presented. The ability of this quality measure and the proposed quality-based score normalization techniques and quality-based frame selection technique to improve verification performance is experimentally evaluated in a video-based face verification experiment on the BANCA Database.