Most face recognition algorithms use a “distancebased” approach: gallery and probe images are projected into a low dimensional feature space and decisions about matching are b...
Recently many Automatic Face Recognition (AFR) systems were developed for applications with unspecific persons, which is different from conventional pattern recognition problems wh...
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
The lack of adequate training samples and the considerable variations observed in the available image collections due to aging, illumination and pose variations are the two key te...
Jie Wang, Kostas N. Plataniotis, Juwei Lu, Anastas...
The accuracy of automated face recognition systems is greatly affected by intraclass variations between enrollment and identification stages. In particular, changes in lighting con...