计算机工程与应用Issue(5)：142-146,5.DOI:10.3778/j.issn.1002-8331.1308-0288
典型相关分析融合全局和局部特征的人脸识别
Face automatic recognition algorithm based on canonical correlation analysis fusion global and local features
韩越祥1
作者信息
- 1. 浙江工业职业技术学院，浙江 绍兴 312000
- 折叠
摘要
Abstract
In order to improve the recognition rate of face image, a novel face recognition method is proposed based on sub-pattern and canonical correlation analysis. The global and local features are extracted, and the redundant information between the features is eliminated, and then the face images are divided in sub models to avoid small sample, nonlinear problems, and the recognition results are corrected by voting method to increase stability of the algorithm, three face data sets are used to test the performance of the algorithm. The simulation results show that, SUB-CCA improves the recogni-tion rate of face image compared with other algorithms.关键词
人脸识别/典型相关分析/子模式/主成分分析Key words
face recognition/canonical correlation analysis/sub-pattern/Principal Component Analysis(PCA)分类
信息技术与安全科学引用本文复制引用
韩越祥..典型相关分析融合全局和局部特征的人脸识别[J].计算机工程与应用,2014,(5):142-146,5.
