@article {IOPORT.05970279,
    author       = {Efraty, Boris and Bilgazyev, Emil and Shah, Shishir and Kakadiaris, Ioannis A.},
    title        = {Profile-based 3D-aided face recognition.},
    year         = {2012},
    journal      = {Pattern Recognition},
    volume       = {45},
    number       = {1},
    issn         = {0031-3203},
    pages        = {43-53},
    publisher    = {Elsevier Science Ltd. (Pergamon), Oxford},
    doi          = {10.1016/j.patcog.2011.07.010},
    abstract     = {Summary: This paper presents a framework for automatic face recognition based on a silhouetted face profile (URxD-PV). Previous research has demonstrated the high discriminative potential of this biometric. Compared to traditional approaches in profile-based recognition, our approach is not limited to only standard side-view faces. We propose to explore the feature space of profiles under various rotations with the aid of a 3D face model. In the enrollment mode, 3D data of subjects are acquired and used to create profiles under different rotations. The features extracted from these profiles are used to train a classifier. In the identification mode, the profile is extracted from the side-view image and its metadata is matched with the gallery metadata. We validate the accuracy of URxD-PV using data from publicly available databases.},
    identifier   = {05970279},
}