Extended multi-spectral face recognition across two different age groups: an empirical study

N. Vetrekar, Ramachandra Raghavendra, A. Gaonkar, G. Naik, R. Gad
{"title":"Extended multi-spectral face recognition across two different age groups: an empirical study","authors":"N. Vetrekar, Ramachandra Raghavendra, A. Gaonkar, G. Naik, R. Gad","doi":"10.1145/3009977.3010026","DOIUrl":null,"url":null,"abstract":"Face recognition has attained a greater importance in bio-metric authentication due to its non-intrusive property of identifying individuals at varying stand-off distance. Face recognition based on multi-spectral imaging has recently gained prime importance due to its ability to capture spatial and spectral information across the spectrum. Our first contribution in this paper is to use extended multi-spectral face recognition in two different age groups. The second contribution is to show empirically the performance of face recognition for two age groups. Thus, in this paper, we developed a multi-spectral imaging sensor to capture facial database for two different age groups (≤ 15years and ≥ 20years) at nine different spectral bands covering 530nm to 1000nm range. We then collected a new facial images corresponding to two different age groups comprises of 168 individuals. Extensive experimental evaluation is performed independently on two different age group databases using four different state-of-the-art face recognition algorithms. We evaluate the verification and identification rate across individual spectral bands and fused spectral band for two age groups. The obtained evaluation results shows higher recognition rate for age groups ≥ 20years than ≤ 15years, which indicates the variation in face recognition across the different age groups.","PeriodicalId":93806,"journal":{"name":"Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing","volume":"16 1","pages":"78:1-78:8"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. Indian Conference on Computer Vision, Graphics & Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3009977.3010026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

Face recognition has attained a greater importance in bio-metric authentication due to its non-intrusive property of identifying individuals at varying stand-off distance. Face recognition based on multi-spectral imaging has recently gained prime importance due to its ability to capture spatial and spectral information across the spectrum. Our first contribution in this paper is to use extended multi-spectral face recognition in two different age groups. The second contribution is to show empirically the performance of face recognition for two age groups. Thus, in this paper, we developed a multi-spectral imaging sensor to capture facial database for two different age groups (≤ 15years and ≥ 20years) at nine different spectral bands covering 530nm to 1000nm range. We then collected a new facial images corresponding to two different age groups comprises of 168 individuals. Extensive experimental evaluation is performed independently on two different age group databases using four different state-of-the-art face recognition algorithms. We evaluate the verification and identification rate across individual spectral bands and fused spectral band for two age groups. The obtained evaluation results shows higher recognition rate for age groups ≥ 20years than ≤ 15years, which indicates the variation in face recognition across the different age groups.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
扩展多光谱人脸识别在两个不同年龄组:一个实证研究
人脸识别由于其在不同距离上识别个体的非侵入性而在生物特征认证中获得了更大的重要性。基于多光谱成像的人脸识别由于其能够捕获跨光谱的空间和光谱信息,最近获得了主要的重要性。我们在本文中的第一个贡献是在两个不同年龄组中使用扩展的多光谱人脸识别。第二个贡献是实证地展示了两个年龄组的人脸识别性能。因此,在本文中,我们开发了一种多光谱成像传感器,用于在530nm至1000nm范围内的9个不同光谱波段捕获两个不同年龄组(≤15岁和≥20岁)的面部数据库。然后,我们收集了两个不同年龄组的168个人的新面部图像。广泛的实验评估在两个不同年龄组的数据库上独立进行,使用四种不同的最先进的人脸识别算法。我们评估了两个年龄组的单个光谱带和融合光谱带的验证和识别率。得到的评价结果显示,≥20岁年龄组的识别率高于≤15岁年龄组,说明不同年龄组的人脸识别存在差异。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Novel Multi-Scale Residual Dense Dehazing Network (MSRDNet) for Single Image Dehazing✱ Robust Brain State Decoding using Bidirectional Long Short Term Memory Networks in functional MRI. ICVGIP 2018: 11th Indian Conference on Computer Vision, Graphics and Image Processing, Hyderabad, India, 18-22 December, 2018 Towards semantic visual representation: augmenting image representation with natural language descriptors Adaptive artistic stylization of images
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1