DocumentCode
3744344
Title
Facial age estimation using artificial neural network and robust feature extraction
Author
Nasim Borzue;Karim Faez
Author_Institution
Dep. of Electrical, Computer, IT, Biomedical Engineering, Qazvin branch, Islamic Azad University, Qazvin, Iran
fYear
2015
Firstpage
34
Lastpage
37
Abstract
Aging is the process of changing the status of human body which human face shows the most important changes. One of the most challenges of age estimation methods is feature extraction which the feature extraction method is failed to extract full informative feature vector elements in the case of deformation, scaling,... in image. So, a feature extractor which is robust against to the situations is necessary. This paper proposes a new method of age estimation where Pseudo Zernike Moment (PZM). The task of age prediction in the proposed method is performed using Artificial Neural Network (ANN) with the type of Multi-Layer Perceptron. The proposed method is evaluated on FG-NET dataset and the results prove the ability of the proposed method .
Keywords
"Feature extraction","Face","Estimation","Support vector machines","Active appearance model","Training","Aging"
Publisher
ieee
Conference_Titel
Biomedical Engineering (ICBME), 2015 22nd Iranian Conference on
Type
conf
DOI
10.1109/ICBME.2015.7404112
Filename
7404112
Link To Document