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引用本文:何文志,周化钢.基于TrackingJS库+百度云人脸识别课程签到系统设计与实现[J].软件工程,2024,27(7):6-11.【点击复制】
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基于TrackingJS库+百度云人脸识别课程签到系统设计与实现
何文志1, 周化钢2
(1.广西智尚数字科技有限公司, 广西 南宁 530025;
2.南宁学院信息工程学院, 广西 南宁 530299)
1623519982@qq.com; zhouhuagang@unn.edu.cn
摘 要: 为了重点解决课程签到作弊问题,文章设计了一款基于TrackingJS库+百度云人脸识别课程签到系统。首先,将课程签到细分为3种方式,分别是线下课签到、线上课签到、公开课签到。其中,线下课签到是最严格的签到管理制度,以确保每一位学员的真实到场,并明确禁止任何形式的代签行为。其次,系统前端采用TrackingJS人脸识别动态抓取库,后端调用百度云人脸识别接口,以及基于教师端的手机Web App签到功能设计,实现低成本、防作弊的课程签到功能。最后,采用Nginx+tomcat+Redis+MySQL技术优化系统架构,解决签到高峰阻塞问题。本设计实现了一个可靠且简单易用的,包括线上、线下及公开课的课程签到系统。
关键词: 签到系统;课程签到;人脸识别;TrackingJS;百度云人脸识别API
中图分类号: TP315    文献标识码: A
基金项目: 南宁学院科研基金项目“基于智慧教育的在线课程管理系统”(2023KY231)
Design and Implementation of Course Attendance System Based on TrackingJS Library and Baidu Cloud Face Recognition
HE Wenzhi1, ZHOU Huagang2
(1.Guangxi Zhi Shang Digital Tech Ltd., Nanning 530025, China;
2.School of In f ormation Engineering, Nanning University, Nanning 530299, China)
1623519982@qq.com; zhouhuagang@unn.edu.cn
Abstract: In order to address the issue of cheating in class attendance, this paper proposes to design a course attendance system based on the TrackingJS library and Baidu Cloud face recognition. Firstly, the course attendance is subdivided into three modes, including offline class attendance, online class attendance, and public class attendance. Among them, offline class attendance is the strictest attendance management system to ensure the presence of each student and explicitly prohibit any form of proxy attendance. Secondly, the system front-end utilizes the TrackingJS face recognition dynamic capture library, the back-end calls the Baidu Cloud face recognition interface, and the mobile Web App attendance function is designed for the teacher-end, so to realize low-cost, anti-cheating class attendance function. Lastly, Nginx+ tomcat+Redis+MySQL technologies are used to optimize the system architecture to address peak attendance blocking issues. A reliable, user-friendly course attendance system for online, offline, and public classes has been designed and implemented.
Keywords: attendance system; class attendance; face recognition; TrackingJS; Baidu Cloud face recognition API


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