计算机工程与应用2017，Vol.53Issue(3)：164-168,5.DOI:10.3778/j.issn.1002-8331.1506-0183
一种自适应加权HOG特征的人脸识别算法
Face recognition based on adaptively weighted HOG
摘要
Abstract
This paper proposes a novel approach for face recognition based on Adaptively Weighted Histograms of Oriented Gradients(AW-HOG)to solve the issues of low face recognition rate in complex environments. Firstly, AW-HOG feature is available by fusing the weighting map and the traditional HOG feature of the sub-images divided from the original whole face images. And the weighting map is adaptively computed on account of the contribution of each sub-image. After that, the dimensions of AW-HOG features are reduced by Principal Component Analysis(PCA)and the final classifi-cation features are generated. Finally, Support Vector Machine(SVM)is utilized in face classification and recognition using the final features. Experimental results based on Yale B and AR standard face databases demonstrate that the proposed approach not only obviously enhances face recognition rate in complex environments but also has certain robust-ness to the influence of light and expression.关键词
人脸识别/梯度方向直方图/主成分分析/自适应加权/支持向量机Key words
face recognition/Histograms of Oriented Gradients(HOG)/Principal Component Analysis(PCA)/adaptively weighted/Support Vector Machine(SVM)分类
信息技术与安全科学引用本文复制引用
胡丽乔,仇润鹤..一种自适应加权HOG特征的人脸识别算法[J].计算机工程与应用,2017,53(3):164-168,5.基金项目
上海市教委科研创新重点项目(No.12ZZ059). （No.12ZZ059）
