Video Biometrics

R. Chellappa, G. Aggarwal
{"title":"Video Biometrics","authors":"R. Chellappa, G. Aggarwal","doi":"10.1109/ICIAP.2007.132","DOIUrl":null,"url":null,"abstract":"A strong requirement to come up with secure and user- friendly ways to authenticate and identify people, to safeguard their rights and interests, has probably been the main guiding force behind biometrics research. Though a vast amount of research has been done to recognize humans based on still images, the problem is still far from solved for unconstrained scenarios. This has led to an increased interest in using video for the task of biometric recognition. Not only does video provide more information, but also is more suitable for recognizing humans in general surveillance scenarios. Other than the multitude of still frames, video makes it possible to characterize biometrics based on inherent dynamics like gait which is not possible with still images. In this paper, we describe several recent algorithms to illustrate the usefulness of videos to identify humans. A brief discussion on remaining challenges is also included.","PeriodicalId":118466,"journal":{"name":"14th International Conference on Image Analysis and Processing (ICIAP 2007)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"14th International Conference on Image Analysis and Processing (ICIAP 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIAP.2007.132","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

A strong requirement to come up with secure and user- friendly ways to authenticate and identify people, to safeguard their rights and interests, has probably been the main guiding force behind biometrics research. Though a vast amount of research has been done to recognize humans based on still images, the problem is still far from solved for unconstrained scenarios. This has led to an increased interest in using video for the task of biometric recognition. Not only does video provide more information, but also is more suitable for recognizing humans in general surveillance scenarios. Other than the multitude of still frames, video makes it possible to characterize biometrics based on inherent dynamics like gait which is not possible with still images. In this paper, we describe several recent algorithms to illustrate the usefulness of videos to identify humans. A brief discussion on remaining challenges is also included.
视频生物识别技术
提出安全和用户友好的方式来验证和识别人,以维护他们的权利和利益的强烈要求,可能是生物识别研究背后的主要指导力量。尽管已经进行了大量的基于静止图像的人类识别研究,但对于不受约束的场景,这个问题仍然远远没有解决。这使得人们对使用视频进行生物特征识别的兴趣越来越大。视频不仅提供了更多的信息,而且更适合在一般的监控场景中识别人。除了大量的静止帧之外,视频使得基于步态等固有动态特征的生物识别成为可能,这在静止图像中是不可能的。在本文中,我们描述了几个最近的算法来说明视频对识别人类的有用性。还包括对剩余挑战的简要讨论。
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