Existing literature compares various biometric modalities of the face for human identification. The common criterion used for comparison is the recognition rate of different face...
The purpose of Face localization is to determine the coordinates of a face in a given image. It is a fundamental research area in computer vision because it serves, as a necessary...
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
In this paper a completely automatic face recognition system is presented. The method works on color images: after having localized the face and the facial features, it determines...
Real-world face recognition systems often have to face the single sample per person (SSPP) problem, that is, only a single training sample for each person is enrolled in the datab...