Face recognition using Gabor features and support vector machines

被引：0

作者：

Li, YF ^{[1
]}

Ou, ZY ^{[1
]}

Wang, GQ ^{[1
]}

机构：

[1] Dalian Univ Technol, Key Lab Precis & Non Tradit Machining Technol, Minist Educ, Dalian, Peoples R China

来源：

ADVANCES IN NATURAL COMPUTATION, PT 2, PROCEEDINGS | 2005年 / 3611卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a face recognition algorithm by using Gabor wavelet transform for facial features extraction and Support Vector Machines (SVM) for face recognition, Gabor wavelets coefficients are used to represent local facial features. The implementations of our algorithm are as follows: Firstly, facial feature points are located roughly by using a set of node templates. Secondly, Gabor wavelet coefficients are extracted at every facial feature point, and all the Gabor wavelet coefficients are catenated to represent a face image. Lastly, SVM classifiers are used for face recognition. The experimental results demonstrate the effectiveness of our face recognition algorithm.

引用

页码：119 / 122

页数：4

共 6 条

[1]

[Anonymous], 1998, MSRTR9814 MICR RES

[2] TWO-DIMENSIONAL SPECTRAL-ANALYSIS OF CORTICAL RECEPTIVE-FIELD PROFILES [J].