基于深度学习的人脸图像年龄估计

Age Estimation of Face Images Based on Deep Learning

人脸图像能够表现大量生物学上的复杂信息,从人脸图像中对人物的年龄进行估计有助于机器视觉在安防、预测等方面的应用。本文提出了一种新的深度神经网络,利用卷积神经网络对人脸图像进行特征提取,结合多层自编码器实现对不同年龄层的分类。同时对提取的人脸特征进行统计,分析随人物衰老变化较大的神经元。在FG-NET数据集上获得了较高准确率。

Face images can represent a large amount of complex biological information.Estimating the age of human from face images is helpful for the application of machine vision in security,prediction and so on.In this paper,a new depth neural network is proposed,which uses convolution neural network to extract features from face images and combines with multi-layer self-encoder to classify different age levels.At the same time,the extracted facial features are counted and the neurons which change greatly with the aging of the characters are analyzed.High accuracy is obtained on FG-NET dataset.