论文标题
EDBB-DEMO：在线教育平台的生物识别和行为分析
edBB-Demo: Biometrics and Behavior Analysis for Online Educational Platforms
论文作者
论文摘要
我们提出了EDBB-DEMO，这是AI驱动的研究平台的演示者，用于远程教育中的学生监测。 EDBB平台旨在研究与数字平台中用户识别和行为理解相关的挑战。该平台已开发用于数据收集，从键盘，鼠标，网络摄像头，麦克风，智能手表和脑电图频段等各种传感器中获取信号。在学生会议期间，从传感器捕获的信息以多模式学习框架进行建模。演示者包括：i）在无监督的环境中生物识别用户身份验证； ii）基于远程视频分析的人类行动识别； iii）来自网络摄像头视频的心率估计；和iv）面部表达分析的注意水平估计。
We present edBB-Demo, a demonstrator of an AI-powered research platform for student monitoring in remote education. The edBB platform aims to study the challenges associated to user recognition and behavior understanding in digital platforms. This platform has been developed for data collection, acquiring signals from a variety of sensors including keyboard, mouse, webcam, microphone, smartwatch, and an Electroencephalography band. The information captured from the sensors during the student sessions is modelled in a multimodal learning framework. The demonstrator includes: i) Biometric user authentication in an unsupervised environment; ii) Human action recognition based on remote video analysis; iii) Heart rate estimation from webcam video; and iv) Attention level estimation from facial expression analysis.
