Autonomous face recognition [Elektronische Ressource] / von Mou, Dengpan

Autonomous Face Recognition Dissertation zur Erlangung des akademischen Grades eines Doktor-Ingenieurs (Dr.-Ing.) der Fakultät für Ingenieurwissenschaften der Universität Ulm von Mou, Dengpan aus China 1. Gutachter: Prof. Dr.-Ing. Albrecht Rothermel 2. Gutachter: Prof. Dr. Heiko Neumann Amtierender Dekan: Prof. Dr.-Ing. Hans-Jörg Pfleiderer Datum der Promotion: 22. August, 2005 2005 II Abstract As a booming technology, face recognition has been studied for many years and is expected to be widely used in daily identification systems, communication systems, public security systems, and in law enforcement systems. Most state-of-the-art machine learning systems are based on the supervised learning theory and image processing techniques, which require separate pre-training procedure for enrolling every new face and updating existing faces. Therefore, an additional human supervisor is normally required. Users’ cooperation is expected as well during the training phase. However, a human vision system is far more intelligent. It has no difficulty to automatically memorize the faces they have interacted with for future recognition. All the enrollments, updates, and comparisons have been done completely in the brain without any outside assistance.