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Multi-Pose Face Recognition Using Hybrid Face Features Descriptor
This paper presents a multi-pose face recognition approach using hybrid face
features descriptors (HFFD). The HFFD is a face descriptor containing of rich
discriminant information that is created by fusing some frequency-based
features extracted using both wavelet and DCT analysis of several different
poses of 2D face images. The main aim of this method is to represent the
multi-pose face images using a dominant frequency component with still having
reasonable achievement compared to the recent multi-pose face recognition
methods. The HFFD based face recognition tends to achieve better performance
than that of the recent 2D-based face recognition method. In addition, the
HFFD-based face recognition also is sufficiently to handle large face
variability due to face pose variations