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Age-Invariant Face Recognition

Authors
Park, UnsangTong, YiyingJain, Anil K.
Issue Date
5월-2010
Publisher
IEEE COMPUTER SOC
Keywords
Face recognition; facial aging; aging modeling; aging simulation; 3D face model
Citation
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, v.32, no.5, pp.947 - U194
Indexed
SCIE
SCOPUS
Journal Title
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Volume
32
Number
5
Start Page
947
End Page
U194
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/116561
DOI
10.1109/TPAMI.2010.14
ISSN
0162-8828
Abstract
One of the challenges in automatic face recognition is to achieve temporal invariance. In other words, the goal is to come up with a representation and matching scheme that is robust to changes due to facial aging. Facial aging is a complex process that affects both the 3D shape of the face and its texture (e. g., wrinkles). These shape and texture changes degrade the performance of automatic face recognition systems. However, facial aging has not received substantial attention compared to other facial variations due to pose, lighting, and expression. We propose a 3D aging modeling technique and show how it can be used to compensate for the age variations to improve the face recognition performance. The aging modeling technique adapts view-invariant 3D face models to the given 2D face aging database. The proposed approach is evaluated on three different databases (i.g., FG-NET, MORPH, and BROWNS) using FaceVACS, a state-of-the-art commercial face recognition engine.
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