Yea-Shuan Huang, Y. Tsai, Hong-Hsin Chao, Y. Chien
{"title":"Face recognition for images from the same unknown person","authors":"Yea-Shuan Huang, Y. Tsai, Hong-Hsin Chao, Y. Chien","doi":"10.1109/CCST.2003.1297614","DOIUrl":null,"url":null,"abstract":"This paper mainly introduces (1) a face recognition method by using a newly designed radial basis function (RBF) neural net which can iteratively reduce a purposely defined classification-oriented error function, and (2) a decision-making mechanism by accumulating multiple individual face recognition results of the same unknown targeted person. To experiment on 50 persons (each person has 32 training samples and 100 testing samples), although the recognition rate of individual sample is only 86.5%, a perfect recognition accuracy (i.e. 100% accuracy) has been achieved by accumulating 20 temporal face images. This shows that the proposed approaches can produce various degrees of security to support different face recognition applications.","PeriodicalId":344868,"journal":{"name":"IEEE 37th Annual 2003 International Carnahan Conference onSecurity Technology, 2003. Proceedings.","volume":"165 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE 37th Annual 2003 International Carnahan Conference onSecurity Technology, 2003. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCST.2003.1297614","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper mainly introduces (1) a face recognition method by using a newly designed radial basis function (RBF) neural net which can iteratively reduce a purposely defined classification-oriented error function, and (2) a decision-making mechanism by accumulating multiple individual face recognition results of the same unknown targeted person. To experiment on 50 persons (each person has 32 training samples and 100 testing samples), although the recognition rate of individual sample is only 86.5%, a perfect recognition accuracy (i.e. 100% accuracy) has been achieved by accumulating 20 temporal face images. This shows that the proposed approaches can produce various degrees of security to support different face recognition applications.
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