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Proceedings Paper

Age estimation of facial image based on convolution neural network
Author(s): Xiaodong Meng; Yifeng Wang; Haihong Zheng
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Paper Abstract

Age is an inherent biological characteristic of human and is reflected in facial images to a certain extent. A method for estimating age from a facial image by combining CNN (Convolution Neural Network) with SVR (Support Vector Regression) is proposed. First, a deep CNN is trained to automatically extract age features from facial images and classify them into variant age groups. Then different SVRs are trained for each age group to estimate the age of a facial image. The experimental results show that a lower MAE (Mean Absolute Error) of age estimation on MORPH database is obtained.

Paper Details

Date Published: 21 July 2017
PDF: 5 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042002 (21 July 2017); doi: 10.1117/12.2281756
Show Author Affiliations
Xiaodong Meng, Xidian Univ. (China)
Yifeng Wang, Xidian Univ. (China)
Haihong Zheng, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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