{"title":"A simple two steps algorithm for face recongition","authors":"Ming Zhao, Hu Jie","doi":"10.1109/ISIC.2012.6449698","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a very simple face recognition method. This method first exploits a linear combination of all the training samples to express the test sample. Then it evaluates the capability of each class in expressing the test sample and assigns the test sample to the class that has the strongest capability. Using the expression result, the proposed method can classify the testing sample with a high accuracy. though the proposed method exploits only one training sample per class to perform classification, it might obtain a better performance than the nearest feature space (NFS) method.","PeriodicalId":393653,"journal":{"name":"2012 International Conference on Information Security and Intelligent Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Information Security and Intelligent Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIC.2012.6449698","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we propose a very simple face recognition method. This method first exploits a linear combination of all the training samples to express the test sample. Then it evaluates the capability of each class in expressing the test sample and assigns the test sample to the class that has the strongest capability. Using the expression result, the proposed method can classify the testing sample with a high accuracy. though the proposed method exploits only one training sample per class to perform classification, it might obtain a better performance than the nearest feature space (NFS) method.