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Locally Adjusted Robust Regression for Human Age Estimation

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4 Author(s)
Guodong Guo ; Dept. of Comput. Sci., North Carolina Central Univ., Durham, NC ; Yun Fu ; Huang, T.S. ; Dyer, C.R.

Automatic human age estimation has considerable potential applications in human computer interaction and multimedia communication. However, the age estimation problem is challenging. We design a locally adjusted robust regressor (LARR) for learning and prediction of human ages. The novel approach reduces the age estimation errors significantly over all previous methods. Experiments on two aging databases show the success of the proposed method for human aging estimation.

Published in:

Applications of Computer Vision, 2008. WACV 2008. IEEE Workshop on

Date of Conference:

7-9 Jan. 2008