从社交媒体照片中收集人脸进行生物识别分析

Giordano Benitez Torres, Michael C. King
{"title":"从社交媒体照片中收集人脸进行生物识别分析","authors":"Giordano Benitez Torres, Michael C. King","doi":"10.1109/ISTAS50296.2020.9462173","DOIUrl":null,"url":null,"abstract":"The accuracy of automatic face recognition has increased significantly over the last decade. Technology developers actively try to improve their tools and algorithms; for this to occur, there is a need for high-quality datasets with a large number of images to test and develop new techniques. Online social networks provide a vast digital media resource, given the volume of traffic that goes through its infrastructure. The content within it varies but is predominately flooded by images. In this era where selfies are the norm, we examine a collection method employed to harvest face data from the subject’s images via the web. We then show how it can be processed and organized so that it is useful for biometric applications. In addition, this experiment demonstrates how restrictions put in place by social media platforms are inadequate in the protection of their user’s data.","PeriodicalId":196560,"journal":{"name":"2020 IEEE International Symposium on Technology and Society (ISTAS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Harvesting Faces from Social Media Photos for Biometric Analysis\",\"authors\":\"Giordano Benitez Torres, Michael C. King\",\"doi\":\"10.1109/ISTAS50296.2020.9462173\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The accuracy of automatic face recognition has increased significantly over the last decade. Technology developers actively try to improve their tools and algorithms; for this to occur, there is a need for high-quality datasets with a large number of images to test and develop new techniques. Online social networks provide a vast digital media resource, given the volume of traffic that goes through its infrastructure. The content within it varies but is predominately flooded by images. In this era where selfies are the norm, we examine a collection method employed to harvest face data from the subject’s images via the web. We then show how it can be processed and organized so that it is useful for biometric applications. In addition, this experiment demonstrates how restrictions put in place by social media platforms are inadequate in the protection of their user’s data.\",\"PeriodicalId\":196560,\"journal\":{\"name\":\"2020 IEEE International Symposium on Technology and Society (ISTAS)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Symposium on Technology and Society (ISTAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISTAS50296.2020.9462173\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Symposium on Technology and Society (ISTAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISTAS50296.2020.9462173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

在过去的十年中,自动人脸识别的准确性有了显著的提高。技术开发人员积极尝试改进他们的工具和算法;为了实现这一点,需要具有大量图像的高质量数据集来测试和开发新技术。考虑到通过其基础设施的流量,在线社交网络提供了巨大的数字媒体资源。它的内容各不相同,但主要是图片泛滥。在这个自拍成为常态的时代,我们研究了一种通过网络从被摄者的图像中收集面部数据的收集方法。然后,我们展示如何处理和组织它,使其对生物识别应用程序有用。此外,这个实验表明,社交媒体平台在保护用户数据方面的限制是不够的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Harvesting Faces from Social Media Photos for Biometric Analysis
The accuracy of automatic face recognition has increased significantly over the last decade. Technology developers actively try to improve their tools and algorithms; for this to occur, there is a need for high-quality datasets with a large number of images to test and develop new techniques. Online social networks provide a vast digital media resource, given the volume of traffic that goes through its infrastructure. The content within it varies but is predominately flooded by images. In this era where selfies are the norm, we examine a collection method employed to harvest face data from the subject’s images via the web. We then show how it can be processed and organized so that it is useful for biometric applications. In addition, this experiment demonstrates how restrictions put in place by social media platforms are inadequate in the protection of their user’s data.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
The Historical and Ideological Chasm between Engineering and Development Sustainability means inclusivity: engaging citizens in early stage smart city development Taiwan’s Ability to Reduce the Transmission of COVID-19: A Success Story Tesseract Optimization for Data Privacy and Sharing Economics Using Open Source Licensing to Regulate the Assembly of LAWS: A Preliminary Analysis
×
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