{"title":"低频眼动追踪数据的生物特征识别方法评价","authors":"Elena N. Cherepovskaya, A. Lyamin","doi":"10.1109/SAMI.2017.7880288","DOIUrl":null,"url":null,"abstract":"During the last decade many information systems started applying various biometric identification modules. This type of identification is secure and provides a real possibility to protect a system from an unapproved access. The paper presents a newly developed biometric identification approach that is suitable for many biometric signals. This work describes an evaluation of the approach on low-frequency eye tracking data that had been collected using 30Hz eye tracker as well as a MATLAB library realizing the approach that had been developed.","PeriodicalId":105599,"journal":{"name":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"An evaluation of biometrie identification approach on low-frequency eye tracking data\",\"authors\":\"Elena N. Cherepovskaya, A. Lyamin\",\"doi\":\"10.1109/SAMI.2017.7880288\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"During the last decade many information systems started applying various biometric identification modules. This type of identification is secure and provides a real possibility to protect a system from an unapproved access. The paper presents a newly developed biometric identification approach that is suitable for many biometric signals. This work describes an evaluation of the approach on low-frequency eye tracking data that had been collected using 30Hz eye tracker as well as a MATLAB library realizing the approach that had been developed.\",\"PeriodicalId\":105599,\"journal\":{\"name\":\"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAMI.2017.7880288\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMI.2017.7880288","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An evaluation of biometrie identification approach on low-frequency eye tracking data
During the last decade many information systems started applying various biometric identification modules. This type of identification is secure and provides a real possibility to protect a system from an unapproved access. The paper presents a newly developed biometric identification approach that is suitable for many biometric signals. This work describes an evaluation of the approach on low-frequency eye tracking data that had been collected using 30Hz eye tracker as well as a MATLAB library realizing the approach that had been developed.