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Human Age Estimation With Regression on Discriminative Aging Manifold

Fu, Yun, Huang, Thomas S.·2008·IEEE Transactions on Multimedia

Abstract

Recently, extensive studies on human faces in the human-computer interaction (HCI) field reveal significant potentials for designing automatic age estimation systems via face image analysis. The success of such research may bring in many innovative HCI tools used for the applications of human-centered multimedia communication. Due to the temporal property of age progression, face images with aging features may display some sequential patterns with low-dimensional distributions. In this paper, we demonstrate that such aging patterns can be effectively extracted from a discriminant subspace learning algorithm and visualized as distinct manifold structures. Through the manifold method of analysis on face images, the dimensionality redundancy of the original image space can be significantly reduced with subspace learning. A multiple linear regression procedure, especially with a quadratic model function, can be facilitated by the low dimensionality to represent the manifold space embodying the discriminative property. Such a processing has been evaluated by extensive simulations and compared with the state-of-the-art methods. Experimental results on a large size aging database demonstrate the effectiveness and robustness of our proposed framework.

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Metadata

Authors
Fu, Y., & Huang, T. S.
Venue
IEEE Transactions on Multimedia
Published
2008-06
Volume
10
Issue
4
Pages
578-584
ISSN
1520-9210 (ISSN-L)
OpenAlex
W2118755929
Cited by
422
References
29
FWCI
31.98
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Human Age Estimation With Regression on Discriminative Aging Manifold. https://app.cochat.ai/papers/10.1109/tmm.2008.921847
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Fu, Y., & Huang, T. S. (2008). Human Age Estimation With Regression on Discriminative Aging Manifold. IEEE Transactions on Multimedia. https://doi.org/10.1109/tmm.2008.921847

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