摘要
随着科技的发展,智能设备产生的大量数据给云计算处理方式带来了巨大的压力,进行快速、有效地人脸识别的技术要求日益迫切。本文基于边缘计算,采用Qt+OpenCV技术设计了人脸识别系统,实现了人脸识别模块在ARM开发板上运行,完成了边缘端及服务器端的开发,优先在移动设备所处的边缘端对图像进行处理,并结合了AdaBoost算法进行识别。该系统可以减少图像目标识别的计算成本、减少网络数据泄露的风险、增强服务响应能力。
With the development of science and technology,large amount of data generated by intelligent devices has brought great pressure to cloud computing processes.There is an urgent demand for fast and effective face recognition technology.This paper,based on edge computing,proposes a new face recognition system by using Qt+OpenC technology.The new system enables face recognition module to run on the ARM development board and the both edge end and server end are completed.Images are firstly processed on the edge end of mobile devices,then recognized through AdaBoost algorithm.The system can reduce the computing cost of image target recognition,lower the risk of network data leakage,and improve service response.
作者
刘思
马靖瑜
袁倩
吴粉侠
LIU Si;MA Jingyu;YUAN Qian;WU Fenxia(School of Computer Science,Xianyang Normal University,Xianyang712000,China)
出处
《软件工程》
2020年第12期40-42,共3页
Software Engineering
基金
2019年度咸阳师范学院大学生创新创业训练计划省级项目(S201910722046).
