REAL TIME AGE INVARIANT FACE RECOGNITION - OSMAN ALI, AMAL SERALKHATEM (2015)
Aging variation poses an interesting challenge for the task of automatic face recognition. Most face recognition studies that have addressed this problem focused on age estimation or aging simulation. Designing an appropriate feature representation and an effective matching tramework for age invariant face recognition remains an open problem. ln this research study, a novel age-invariant face recognition framework that is built based on two face biometric traits is proposed. The first trait is a set of anthropometric measurements acquired from the lip-nose complex. Lip-nose complex measurements have been known in several physiological studies to be discriminative among different ethnicities and among different genders within the same ethnicity. The second trait is based on extracting features of the periocular region using two robust descriptors, namely local binary pattems rotation invariant descriptor (LBPV) and GIST descriptors.