几种分类器在人脸识别中的性能仿真研究

C. Chen, Jia Tang
{"title":"几种分类器在人脸识别中的性能仿真研究","authors":"C. Chen, Jia Tang","doi":"10.1109/FSKD.2012.6233940","DOIUrl":null,"url":null,"abstract":"Classifier is the important content in the face recognition system. This paper uses PCA to extract the face image feature and then compares the recognition performance of several classifiers. Based on ORL and YALE face database, the paper carries out simulation experiment by using minimum distance classifier, nearest-neighbor classifier and K-neighbor classifier respectively. Besides, this paper researches different distance measures' effects on the recognition result of the classifiers, Euclidean distance, Minkowski distance, cosine distance and absolute distance.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Simulation study on the performance of several classifiers in face recognition\",\"authors\":\"C. Chen, Jia Tang\",\"doi\":\"10.1109/FSKD.2012.6233940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Classifier is the important content in the face recognition system. This paper uses PCA to extract the face image feature and then compares the recognition performance of several classifiers. Based on ORL and YALE face database, the paper carries out simulation experiment by using minimum distance classifier, nearest-neighbor classifier and K-neighbor classifier respectively. Besides, this paper researches different distance measures' effects on the recognition result of the classifiers, Euclidean distance, Minkowski distance, cosine distance and absolute distance.\",\"PeriodicalId\":337941,\"journal\":{\"name\":\"International Conference on Fuzzy Systems and Knowledge Discovery\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Fuzzy Systems and Knowledge Discovery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FSKD.2012.6233940\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Fuzzy Systems and Knowledge Discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FSKD.2012.6233940","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

分类器是人脸识别系统的重要内容。本文利用主成分分析法提取人脸图像特征,然后比较几种分类器的识别性能。基于ORL和YALE人脸数据库,分别采用最小距离分类器、最近邻分类器和k近邻分类器进行仿真实验。此外,本文还研究了不同距离度量对分类器识别结果的影响,欧几里得距离、闵可夫斯基距离、余弦距离和绝对距离。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulation study on the performance of several classifiers in face recognition
Classifier is the important content in the face recognition system. This paper uses PCA to extract the face image feature and then compares the recognition performance of several classifiers. Based on ORL and YALE face database, the paper carries out simulation experiment by using minimum distance classifier, nearest-neighbor classifier and K-neighbor classifier respectively. Besides, this paper researches different distance measures' effects on the recognition result of the classifiers, Euclidean distance, Minkowski distance, cosine distance and absolute distance.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信