Using Neural Networks with Differential Evolution Learning for Face Recognition

被引：0

作者：

Huang, Shih-Yen ^{[1
]}

Lin, Cheng-Jian ^{[1
]}

机构：

[1] Natl Chin Yi Univ Technol, Dept Comp Sci & Informat Engn, Taichung, Taiwan

来源：

2014 INTERNATIONAL SYMPOSIUM ON COMPUTER, CONSUMER AND CONTROL (IS3C 2014) | 2014年

关键词：

Face Recognition; Gabor Wavelets; Principal Component Analysis; Differential Evolution; Multilayer Neural Networks;

D O I：

10.1109/IS3C.2014.104

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we present an innovative method that combines two-dimensional texture and three-dimensional (3D) images surface feature vectors. Next, we use Gabor wavelets extracting local features at different scales and orientations by two-dimensional facial images. Next, we combine the texture with the three-dimensional (3D) images surface feature vectors based on principal component analysis (PCA) to obtain feature vectors from grey and facial surface images. We also propose a differential evolution (DE) algorithm for face recognition based on multilayer neural networks as an identification model. In ours experimental results demonstrate for the recognition different face poses and facial expressions method was efficiency.

引用

页码：376 / 379

页数：4

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