Sadi Vural


Title New empirical techniques for infallible 3D Face recognition in harshly environments

Although face recognition is very convenient and the most natural biometrics technology, it is widely known that face recognition is error-prone and heavily affected by environmental factors such as light, camera, face pose and so on. However, there are several methods to have a perfect face recognition in outdoor environments. First of all, failure factors of Face recognition will be explained. These will be given from the perspective of camera/image and subject of interest. After then, methodologies to have a error-free face recognition in unconstraint environments will be given by examples. Some knowhow and techniques based on the empirical studies will be explained so that these enhance the use of face recognition widely in our society. Some interesting ideas on how Face recognition will contribute our daily life will be also shared.


Sadi Vural received his B.S. degree in Electronics Engineering from Istanbul University, Istanbul, Turkey in 1997 and the M.S. degree in Information Science Engineering from Ritsumeikan University, Shiga, Japan in 2000. He received his Ph.D. degree from the Department of Systems Innovation, Graduate School of Engineering Science at Osaka University, Osaka, Japan in 2011. He is doing face recognition research as Visiting Assoc. Professor at Osaka University. He is also working for the Ayonix Corporation, Tokyo, Japan, since of 2007. His current interests include face detection, face recognition, 3d Face feature extraction, neuro-brain recognition, gender and age estimation.