An Ensemble Method of Global and Local Representation for Face Recognition
To aim at the challenge of face recognition to uncontrolled situations,an ensemble method of global and local representation for face recognition is presented in this paper.shearlets transform is firstly employed to decompose a image into subimages.Then directional information is utilized along with conventional scaling and translation parameters,global feature of a face image is extracted by principle component analysis.Thirdly,local feature of a face image is extracted by a deep convolutional neural network.Finally,an ensemble of global and local feature is performed by weighted score.Experimental results on two challenge face databases show that the proposed method achieved higher face recognition accuracy than art-ofthe-state methods.Hence,the ensemble of global and local feature is more potential features for the design of efficient face recognition system.
face recognition Shearlets transform deep convolution PCA ensemble
Zhiyong Zeng
College of Mathematics and Informatics,Fujian Normal University,350117,China
国际会议
深圳
英文
94-100
2018-01-21（万方平台首次上网日期，不代表论文的发表时间）