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- W3203943230 abstract "Aging variation poses an interesting challenge for the task of automatic facerecognition. Most face recognition studies that have addressed this problem focusedon age estimation or aging simulation. Designing an appropriate featurerepresentation and an effective matching tramework for age invariant face recognitionremains an open problem. ln this research study, a novel age-invariant facerecognition framework that is built based on two face biometric traits is proposed. Thefirst trait is a set of anthropometric measurements acquired from the lip-nosecomplex. Lip-nose complex measurements have been known in several physiologicalstudies to be discriminative among different ethnicities and among different genderswithin the same ethnicity. The second trait is based on extracting features of theperiocular region using two robust descriptors, namely local binary pattems rotationinvariant descriptor (LBPV) and GIST descriptors." @default.
- W3203943230 created "2021-10-11" @default.
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- W3203943230 date "2015-06-01" @default.
- W3203943230 modified "2023-09-23" @default.
- W3203943230 title "REAL TIME AGE INVARIANT FACE RECOGNITION" @default.
- W3203943230 hasPublicationYear "2015" @default.
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