{"title":"基于马赛克图案和bp神经网络的人脸鲁棒识别","authors":"M. Kosugi","doi":"10.1109/NNSP.1992.253683","DOIUrl":null,"url":null,"abstract":"The backpropagation network (BPN) is applied to human face recognition. A mosaic pattern transformed from the central part of a human face image is put into the BPN for personal identification. This combination succeeds in recognition of hundreds of people with robustness not only for defocused or noisy images but also for images of different face expressions or different ages. Hidden units of the BPN extract peculiar and delicate features of the face, which cannot be obtained from existing statistical methods. A few hidden units can especially select only men or women. Moreover, a BPN with an additional unit for processing unfamiliar faces is proposed.<<ETX>>","PeriodicalId":438250,"journal":{"name":"Neural Networks for Signal Processing II Proceedings of the 1992 IEEE Workshop","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Robust identification of human face using mosaic pattern and BPN\",\"authors\":\"M. Kosugi\",\"doi\":\"10.1109/NNSP.1992.253683\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The backpropagation network (BPN) is applied to human face recognition. A mosaic pattern transformed from the central part of a human face image is put into the BPN for personal identification. This combination succeeds in recognition of hundreds of people with robustness not only for defocused or noisy images but also for images of different face expressions or different ages. Hidden units of the BPN extract peculiar and delicate features of the face, which cannot be obtained from existing statistical methods. A few hidden units can especially select only men or women. Moreover, a BPN with an additional unit for processing unfamiliar faces is proposed.<<ETX>>\",\"PeriodicalId\":438250,\"journal\":{\"name\":\"Neural Networks for Signal Processing II Proceedings of the 1992 IEEE Workshop\",\"volume\":\"80 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neural Networks for Signal Processing II Proceedings of the 1992 IEEE Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NNSP.1992.253683\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neural Networks for Signal Processing II Proceedings of the 1992 IEEE Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NNSP.1992.253683","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robust identification of human face using mosaic pattern and BPN
The backpropagation network (BPN) is applied to human face recognition. A mosaic pattern transformed from the central part of a human face image is put into the BPN for personal identification. This combination succeeds in recognition of hundreds of people with robustness not only for defocused or noisy images but also for images of different face expressions or different ages. Hidden units of the BPN extract peculiar and delicate features of the face, which cannot be obtained from existing statistical methods. A few hidden units can especially select only men or women. Moreover, a BPN with an additional unit for processing unfamiliar faces is proposed.<>