{"title":"基于PLS和HMM的人脸识别","authors":"Y. Hu, Benyong Liu","doi":"10.1109/CCPR.2009.5343968","DOIUrl":null,"url":null,"abstract":"In this paper, a face recognition scheme is proposed, wherein face images are preprocessed based on pixel averaging and energy normalization, and features are extracted successively with fast Fourier transform and the partial least squares for dimensionality reduction, and classification results are obtained by a classifier based on hidden Markov model. Some experimental results on the Olivetti Research Laboratory face database are presented to show the feasibility of the presented scheme.","PeriodicalId":354468,"journal":{"name":"2009 Chinese Conference on Pattern Recognition","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Face Recognition Based on PLS and HMM\",\"authors\":\"Y. Hu, Benyong Liu\",\"doi\":\"10.1109/CCPR.2009.5343968\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a face recognition scheme is proposed, wherein face images are preprocessed based on pixel averaging and energy normalization, and features are extracted successively with fast Fourier transform and the partial least squares for dimensionality reduction, and classification results are obtained by a classifier based on hidden Markov model. Some experimental results on the Olivetti Research Laboratory face database are presented to show the feasibility of the presented scheme.\",\"PeriodicalId\":354468,\"journal\":{\"name\":\"2009 Chinese Conference on Pattern Recognition\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Chinese Conference on Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCPR.2009.5343968\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Chinese Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCPR.2009.5343968","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, a face recognition scheme is proposed, wherein face images are preprocessed based on pixel averaging and energy normalization, and features are extracted successively with fast Fourier transform and the partial least squares for dimensionality reduction, and classification results are obtained by a classifier based on hidden Markov model. Some experimental results on the Olivetti Research Laboratory face database are presented to show the feasibility of the presented scheme.
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