Estimating Human Age by Manifold Analysis of Face Pictures and Regression on Aging Features
Estimating Human Age by Manifold Analysis of Face Pictures and Regression on Aging Features
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DOI：
10.1109/icme.2007.4284917
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发表时间：
2007-07
期刊：
影响因子：
--
通讯作者：
Yun Fu;Ye Xu;Thomas S. Huang
中科院分区：
文献类型：
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作者：
Yun Fu;Ye Xu;Thomas S. Huang
最近对人脸的广泛研究揭示了通过人脸图像分析自动估计年龄的重要潜在应用。由于年龄发展的时间特征，衰老人脸图像呈现出低维分布的序列模式。通过对人脸图像的流形分析，提出了一种新的年龄估计框架。利用流形学习方法寻找足够的嵌入空间，利用多元线性回归函数对低维流形数据进行建模。在大型年龄数据库上的实验结果验证了该框架的有效性。据我们所知，这是第一个涉及多种年龄估计方法的工作。
Extensive recent studies on human faces reveal significant potential applications of automatic age estimation via face image analysis. Due to the temporal features of age progression, aging face images display sequential pattern of low-dimensional distribution. Through manifold analysis of face pictures, we developed a novel age estimation framework. The manifold learning methods are applied to find a sufficient embedding space and model the low-dimensional manifold data with a multiple linear regression function. Experimental results on a large size age database demonstrate the effectiveness of the framework. To our best knowledge, this is the first work involving the manifold ways of age estimation.