{"title":"基于pca的人脸识别中两种预处理技术的比较","authors":"I. Ciocoiu, B. Valmar","doi":"10.1109/SCS.2003.1227004","DOIUrl":null,"url":null,"abstract":"We present a comparative analysis of the recognition performances of 2 different preprocessing techniques for face recognition application. The specific methods are projection-combined principal component analysis ((PC)2A) and eigenhills, which are compared against standard eigenface method. Recognition performances are computed using different distance measures and number of training images on the Olivetti database.","PeriodicalId":375963,"journal":{"name":"Signals, Circuits and Systems, 2003. SCS 2003. International Symposium on","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A comparison between two preprocessing techniques in PCA-based face recognition\",\"authors\":\"I. Ciocoiu, B. Valmar\",\"doi\":\"10.1109/SCS.2003.1227004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a comparative analysis of the recognition performances of 2 different preprocessing techniques for face recognition application. The specific methods are projection-combined principal component analysis ((PC)2A) and eigenhills, which are compared against standard eigenface method. Recognition performances are computed using different distance measures and number of training images on the Olivetti database.\",\"PeriodicalId\":375963,\"journal\":{\"name\":\"Signals, Circuits and Systems, 2003. SCS 2003. International Symposium on\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Signals, Circuits and Systems, 2003. SCS 2003. International Symposium on\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCS.2003.1227004\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signals, Circuits and Systems, 2003. SCS 2003. International Symposium on","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCS.2003.1227004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A comparison between two preprocessing techniques in PCA-based face recognition
We present a comparative analysis of the recognition performances of 2 different preprocessing techniques for face recognition application. The specific methods are projection-combined principal component analysis ((PC)2A) and eigenhills, which are compared against standard eigenface method. Recognition performances are computed using different distance measures and number of training images on the Olivetti database.
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