基于面部特征识别的远程教学辅助系统
Online Teaching Assistant System Based on Facial Feature Recognition

目前网络上的远程教育软件可以提供学生和老师的实时视频和语音，但受限于网络带宽和数据查询不便等问题，教师无法观察到所有学生在课堂中的状态和响应，无法及时根据反馈调整在线课堂教学的教学方式和课堂节奏，只能有限的观察部分学生的信息。针对远程教育中获得学生实时反馈能力低下和学生数据管理不便的问题，给出一种基于面部特征识别的远程教学辅助系统。采用Python框架，首先通过opencv技术将前端采集的图像进行处理，抓取人脸和对齐，数据通过百度企业级人脸识别和人脸检测与属性分析接口，获取面部特征信息，对返回的面部特征信息进行识别，得出状态结果，实时传入学生和教师前端。教师还可以访问数据库进行历史上课状态数据查询。本系统主要是为了给使用远程教育使用者提供一个能够系统的查看和管理大量学生状态信息的远程教学辅助系统。
At present on the network remote education software can provide students and teachers live video and voice, but is limited by the network bandwidth and data query inconvenience, teachers can’t observe the state of all the students in the classroom and response, not timely adjusted according to the feedback online teaching mode of classroom teaching and limited observation only a part of the student’s information. In order to solve the problems of low ability to obtain real-time feedback from students and inconveniences to manage students’ data in Online education, a Online teaching assistant system based on facial feature recognition is proposed. Using Python framework, first of all, through opencv technology will front-end collection of image processing, fetching faces and alignment, the data Baidu enterprise face recognition and face detection and attribute analysis interface, facial features information, the return of facial feature information, which can identify state results, real-time front-end incoming students and teachers. Teachers can also access the database for historical class status data query. This system is mainly for the use of online education users to provide a system to view and manage a large number of students’ state information teaching system.