Research on Face Recognition Algorithm in Embedded System

X. Tian, Haobo Long
{"title":"Research on Face Recognition Algorithm in Embedded System","authors":"X. Tian, Haobo Long","doi":"10.1109/IICSPI48186.2019.9096027","DOIUrl":null,"url":null,"abstract":"As a friendly biometric method, face recognition has the advantages of not easy to forge, easy to obtain, and high accuracy. The paper builds a development environment for embedded face recognition. In terms of hardware, the embedded development board and camera of the ARM architecture are chosen; in terms of software, the open source Linux operating system is chosen. The virtual machine was installed on the PC, the cross-compilation environment was established, and the kernel, driver and other related ports were transplanted on the development board, which established a stable running environment for the design and development of the face recognition application. An embedded system pooling-patch algorithm based on deep learning pooling operation and Deep ID algorithm is proposed. Experiments on the ORL face database and the face image library of our lab members show that the method not only has a high recognition rate but also takes a short time.","PeriodicalId":318693,"journal":{"name":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IICSPI48186.2019.9096027","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

As a friendly biometric method, face recognition has the advantages of not easy to forge, easy to obtain, and high accuracy. The paper builds a development environment for embedded face recognition. In terms of hardware, the embedded development board and camera of the ARM architecture are chosen; in terms of software, the open source Linux operating system is chosen. The virtual machine was installed on the PC, the cross-compilation environment was established, and the kernel, driver and other related ports were transplanted on the development board, which established a stable running environment for the design and development of the face recognition application. An embedded system pooling-patch algorithm based on deep learning pooling operation and Deep ID algorithm is proposed. Experiments on the ORL face database and the face image library of our lab members show that the method not only has a high recognition rate but also takes a short time.
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
嵌入式系统人脸识别算法研究
人脸识别作为一种友好的生物识别方法,具有不易伪造、易获取、准确性高等优点。本文构建了嵌入式人脸识别的开发环境。硬件方面,选用ARM架构的嵌入式开发板和摄像头;在软件方面,选择开源的Linux操作系统。在PC上安装虚拟机,建立交叉编译环境,并在开发板上移植内核、驱动程序等相关端口,为人脸识别应用的设计开发建立了稳定的运行环境。提出了一种基于深度学习池化操作和deep ID算法的嵌入式系统池化补丁算法。在ORL人脸数据库和实验室成员的人脸图像库上进行的实验表明,该方法不仅识别率高,而且耗时短。
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
The Analysis and Design of System of Experimental Consumables Based on Django and QR code Analysis and Research on the Characteristics of Boiled Yolk based on Hyperspectral Remote Sensing Images Density Peaks Spatial Clustering by Grid Neighborhood Search Modeling of Superheated Steam Temperature Characteristics Based on Fireworks Algorithm Optimized Extreme Learning Machine Fusion Chaotic Prediction Model for Bearing Performance by Computer Technique
×
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