Deep age estimation by fusing facial information
LI Yun-fei
LU Zhao-yang
LI Jing
Abstract：The paper presents a new mode of solution for deep age estimation by facial features auxiliary,which fuses the traditional facial information with the convolutional neural network(CNN)to achieve the age estimation,in order to reinforce the generalization ability of system model. The solution estimates age from image pixels directly,which makes the locally aligned face image block generated by the key points of the face as the input of the CNN.The system improves the performance significantly by using the multi-scale CNN network structure. At the same time,it apply the traditional method to strengthen the information of facial areas. The experiments on MORPH AlbumⅡillustrate the superiorities of the proposed method over other state-of-the-art methods.
Keywords：age estimationfacial features auxiliaryconvolutional neural networkmulti-scalemulti-task
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 1236-1243 )