An effective face verification algorithm to fuse complete features in convolutional neural network - 文章详情页

作者：

Ma, Y. (Ma, Y..) | He, J. (He, J..) | Wu, L. (Wu, L..) | Qi, W. (Qi, W..)

收录：

Scopus

摘要：

Face　verification　for　on　line　application　is　a　difficult　problem　and　many　researchers　have　tried　to　solve　it　by　convolutional　neural　network.　Among　of　them,　most　works　used　the　last-hidden　layer　as　the　feature　of　face,　and　abandoned　the　features　in　the　lower　layers　which　indicate　local　information.　To　remedy　this,　we　extract　features　of　all　layers　in　the　convolutional　neural　net-work,　and　fuse　these　features　together　after　dimensionality　reduction　with　PCA.　Then　these　features　are　utilized　for　face　verification　with　neural　network　classifier.　Experiment　results　show　that　complete　features　can　improve　the　verification　rate　effectively　than　using　the　last-hidden　layer　only.　©　Springer　International　Publishing　Switzerland　2016.

关键词：

Convolutional neural network; Deep learning; Face verification; Principle component analysis

作者机构：

[ 1 ] [Ma, Y.]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [He, J.]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 3 ] [Wu, L.]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 4 ] [Qi, W.]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China

通讯作者信息：

[Wu, L.]School of Electronic Information and Control Engineering, Beijing University of TechnologyChina

电子邮件地址：

lfwu@bjut.edu.cn

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