基于一种改进NMF算法的人脸年龄估计方法

基于人脸图像的年龄自动估计是人脸识别领域的一个重要研究方向,同时也是一个难点。对此,提出了一种改进的NMF算法来实现人脸年龄估计,该算法首先对NMF分解的基图像进行判别分析,保留最具判别力的基图像来构造子空间,然后将整体训练集图像向得到的子空间进行投影,并用RBF(radial basis function)神经网络进行训练和测试,提取包含在大多数人脸图像上的年龄信息来进行年龄估计,实验结果表明,该算法获得了较好的测试结果。

Age Estimation of Facial Images Based on an Improved Non-negative Matrix Factorization Algorithm

Automatic age estimation based on facial images is important but challenging in face recognition research. An improved NMF (Non-negative Matrix Factorization) algorithm was proposed to implement the age estimation of facial images,which employs linear discriminative analysis in the features derived from NMF,keeps down the base images that have the best discriminate ability to form a new subspace. Then,after projecting the whole training sets images to the obtained subspace,the RBF neural networks was used to extract the aging information contained in most facial images to estimate age information. Finally,experimental results demonstrate that it is an effective method.