Enhanced Continuous Face Recognition Algorithm for Bandwidth Constrained Network in Real Time Application

Sumayyah Dzulkifly, Hazleen Aris, Tiagrajah V. Janahiraman
{"title":"Enhanced Continuous Face Recognition Algorithm for Bandwidth Constrained Network in Real Time Application","authors":"Sumayyah Dzulkifly, Hazleen Aris, Tiagrajah V. Janahiraman","doi":"10.1145/3386762.3386778","DOIUrl":null,"url":null,"abstract":"Current advancement in technologies enables improvements in terms of general welfare and security to be made. These days, biometric recognition is highly regarded as one of the safest and unique ways to verify, authenticate and provide access to the users. One known biometric recognition type is face. Face recognition (FR) is widely used for a number of reasons, ranging from verification purpose or to enabling access. While numerous studies on FR algorithm are carried out, there are still few researches that elaborate on the real-time application of the proposed algorithms. In this paper, the development of an FR algorithm meant for real-time application is described. The algorithm is developed based on the Discrete Krawtchouk Moment (DKM), which is known for its wide application in FR. Our work extends other work in this area by having an algorithm that is able to perform the recognition swiftly without consuming a lot of network bandwidth. Evaluation performed using two different types of camera of different resolutions confirms the ability of the proposed algorithm to fulfil its objectives.","PeriodicalId":147960,"journal":{"name":"Proceedings of the 2020 The 9th International Conference on Informatics, Environment, Energy and Applications","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 The 9th International Conference on Informatics, Environment, Energy and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3386762.3386778","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Current advancement in technologies enables improvements in terms of general welfare and security to be made. These days, biometric recognition is highly regarded as one of the safest and unique ways to verify, authenticate and provide access to the users. One known biometric recognition type is face. Face recognition (FR) is widely used for a number of reasons, ranging from verification purpose or to enabling access. While numerous studies on FR algorithm are carried out, there are still few researches that elaborate on the real-time application of the proposed algorithms. In this paper, the development of an FR algorithm meant for real-time application is described. The algorithm is developed based on the Discrete Krawtchouk Moment (DKM), which is known for its wide application in FR. Our work extends other work in this area by having an algorithm that is able to perform the recognition swiftly without consuming a lot of network bandwidth. Evaluation performed using two different types of camera of different resolutions confirms the ability of the proposed algorithm to fulfil its objectives.
增强连续人脸识别算法在带宽约束网络中的实时应用
目前技术的进步使一般福利和安全得以改善。如今,生物识别被认为是验证、认证和向用户提供访问权限的最安全、唯一的方法之一。一种已知的生物识别类型是人脸。人脸识别(FR)被广泛使用的原因有很多,从验证目的到允许访问。虽然对FR算法进行了大量的研究,但对所提出算法的实时应用进行阐述的研究仍然很少。本文描述了一种用于实时应用的FR算法的开发。该算法是基于离散克劳楚克矩(DKM)开发的,该算法以其在FR中的广泛应用而闻名。我们的工作扩展了该领域的其他工作,通过具有能够快速执行识别而不消耗大量网络带宽的算法。使用不同分辨率的两种不同类型的相机进行的评估证实了所提出的算法实现其目标的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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