摘要
针对现有课堂考勤系统检测率低和数据查询不便的问题,给出一种人脸识别的无感知课堂考勤系统。采用Android开发平台,首先,通过OkHttp3技术将前端采集的图像传入服务器;其次,调取数据库MySQL中某班级人员信息,通过改进的Fust人脸检测算法筛选出每位学生人脸图像,利用类内相似度值和类间相似度值生成VIPLFaceNet人脸识别阈值,对筛选出的人脸图像进行识别,得出考勤结果;最后,将考勤结果传入前端,管理员可以访问服务器进行考勤数据查询。实验结果表明:改进的Fust人脸检测算法召回率与VIPLFaceNet人脸识别算法识别率分别可达90.18%、98.79%。
Aiming at the low detection rate of the existing classroom attendance system and the inconvenience of data query, a non-perceptual classroom attendance system based on face recognition is proposed and designed. Using the Android development platform, the image collected by the front-end was first transferred to the server through OkHttp3 technology. Then the information of the class in the database MySQL was retrieved. Then the face image of each student was filtered through the improved Fust face detection algorithm, and the similarity value within the class and similarity value between the class generated VIPLFaceNet face recognition threshold, which recognized the screened face images and obtained the attendance result. Finally, the attendance result was sent to the front end,the administrator could access the server to query attendance data. The experimental results showed that the recall rate of the improved Fust face detection algorithm and the recognition rate of the VIPLFaceNet face recognition algorithm could reach 90.18% and 98.79% respectively.
作者
刘晓龙
顾梅花
LIU Xiaolong;GU Meihua(School of Electronics and Information, Xi’an Polytechnic University, Xi’an 710048, China)
出处
《西安工程大学学报》
CAS
2021年第1期81-87,共7页
Journal of Xi’an Polytechnic University
基金
国家自然科学基金青年科学基金(61901347)。
