A real time automatic access control system based on face and eye corners detection, face recognition and speaker identification

We have recently developed a real time automatic access control system using both face and voice identification. We show that combining these two modalities achieves high recognition accuracy, especially in difficult recognition scenarios. Our system also supports online training of the user models, i.e, a person who has not been registered in the database can be added on the spot in real time. This system is composed of a face and eye corners detection module, a face recognition module, a speaker identification module and a user interface module. We present the algorithm of each module with more emphasis on our information maximization based face and eye corners detection and the user interface design. We discuss some issues related to the integration of components into the total system. We report the experimental results of the system performance together with comparison with those of some other systems.