Automatic age estimation based on facial aging patterns


Generate a file for use with external citation management software. In contrast to other facial variations, aging variation presents several unique characteristics which make age estimation a challenging task. Published by Elsevier B. JavaScript is disabled on your browser. Download full text in PDF Download. Didn't get the message? Please review our privacy policy.
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Automatic age estimation based on facial aging patterns

In contrast to other facial variations, aging variation presents several unique characteristics which make age estimation a challenging task. Views Read View source View history. In contrast to other facial variations, aging variation presents several unique characteristics which make age estimation a challenging task. Advanced Search Include Citations Disambiguate. Experimental results based on publicly available datasets prove that this method outperformed previous approaches reported in the literature and also performed better than widely used classification methods. Most age estimation methodologies described in the literature use information from the overall face.
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CiteSeerX — Automatic Age Estimation Based on Facial Aging Patterns

In most cases, these works may not be reposted without the explicit permission of the copyright holder. The proper aging pattern for a previously unseen face image is determined by the projection in the subspace that can reconstruct the face image with minimum reconstruction error, while the position of the face image in that aging pattern will then indicate its age. Suo use a three-level hierarchical face model as the basis for age estimation. Kwon and Lobo use two main types of features: Advanced Search Include Citations.
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Automatic age estimation based on facial aging patterns
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Automatic age estimation based on facial aging patterns
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Automatic Age Estimation Based on Facial Aging Patterns

Automatic age estimation based on facial aging patterns



Description: This material is presented to ensure timely dissemination of scholarly and technical work. In this section typical approaches described in the literature are briefly presented. Future research efforts in age estimation should include efforts for generating suitable datasets to support both the training and comparative evaluation of different age estimation approaches reported in the literature. Age progression algorithms often require information related to the current age of a person, hence an accurate facial age estimation system can play a key role in developing automatic age progression systems, supporting in that way age-invariant identity verification. The proper aging pattern for a previously unseen face image is determined by the projection in the subspace that can reconstruct the face image with minimum reconstruction error, while the position of the face image in that aging pattern will then indicate its age.

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Views: 2060 Date: 30.12.2016 Favorited: 5 favorites

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