|Table of Contents|

Age Estimation Based on Deep Learning MPCANet(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2017年01期
Page:
20-
Research Field:
·数学与计算机科学·
Publishing date:

Info

Title:
Age Estimation Based on Deep Learning MPCANet
Author(s):
Zheng Depeng; Du Jixiang; Zhai Chuanmin
School of Computer Science and Technology,Huaqiao University,Xiamen 361021,China
Keywords:
deep learning; age estimation; multi principal component analysis network(MPCANet)
PACS:
TP391
DOI:
10.3969/j.issn.1001-4616.2017.01.004
Abstract:
This paper investigates deep learning techniques for age estimation based on the multi principal component analysis network(MPCANet). A new framework for age feature extraction based on deep learning model with convolutional neural network(CNN)is built. The MPCANet is a variation of principal component analysis network(PCANet),which is recently proposes deep learning algorithms. The MPCANet model architecture components:(1)the use of Multi cascaded principal component analysis(PCA)in the convolution filter layer;(2)the nonlinear process layer by binary hashing; and(3)the use of block histogram in the feature pooling layer. We use K-SVR(Kernel function Support Vector Regression,K-SVR)for age estimation. Experimental results on two datasets(FG-NET and MORPH)show that the proposed approach is significantly better than the state-of-the-art.

References:

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