Hitoshi Imaoka, H. Hashimoto, Koichi Takahashi, Akinori F. Ebihara, Jianquan Liu, Akihiro Hayasaka, Yusuke Morishita, K. Sakurai
{"title":"The future of biometrics technology: from face recognition to related applications","authors":"Hitoshi Imaoka, H. Hashimoto, Koichi Takahashi, Akinori F. Ebihara, Jianquan Liu, Akihiro Hayasaka, Yusuke Morishita, K. Sakurai","doi":"10.1017/ATSIP.2021.8","DOIUrl":null,"url":null,"abstract":"Biometric recognition technologies have become more important in the modern society due to their convenience with the recent informatization and the dissemination of network services. Among such technologies, face recognition is one of the most convenient and practical because it enables authentication from a distance without requiring any authentication operations manually. As far as we know, face recognition is susceptible to the changes in the appearance of faces due to aging, the surrounding lighting, and posture. There were a number of technical challenges that need to be resolved. Recently, remarkable progress has been made thanks to the advent of deep learning methods. In this position paper, we provide an overview of face recognition technology and introduce its related applications, including face presentation attack detection, gaze estimation, person re-identification and image data mining. We also discuss the research challenges that still need to be addressed and resolved.","PeriodicalId":44812,"journal":{"name":"APSIPA Transactions on Signal and Information Processing","volume":" ","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2021-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1017/ATSIP.2021.8","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"APSIPA Transactions on Signal and Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/ATSIP.2021.8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 9
Abstract
Biometric recognition technologies have become more important in the modern society due to their convenience with the recent informatization and the dissemination of network services. Among such technologies, face recognition is one of the most convenient and practical because it enables authentication from a distance without requiring any authentication operations manually. As far as we know, face recognition is susceptible to the changes in the appearance of faces due to aging, the surrounding lighting, and posture. There were a number of technical challenges that need to be resolved. Recently, remarkable progress has been made thanks to the advent of deep learning methods. In this position paper, we provide an overview of face recognition technology and introduce its related applications, including face presentation attack detection, gaze estimation, person re-identification and image data mining. We also discuss the research challenges that still need to be addressed and resolved.