English

edBB-Demo: Biometrics and Behavior Analysis for Online Educational Platforms

Human-Computer Interaction 2022-12-06 v2 Computer Vision and Pattern Recognition

Abstract

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.

Keywords

Cite

@article{arxiv.2211.09210,
  title  = {edBB-Demo: Biometrics and Behavior Analysis for Online Educational Platforms},
  author = {Roberto Daza and Aythami Morales and Ruben Tolosana and Luis F. Gomez and Julian Fierrez and Javier Ortega-Garcia},
  journal= {arXiv preprint arXiv:2211.09210},
  year   = {2022}
}

Comments

Accepted in "AAAI-23 Conference on Artificial Intelligence (Demonstration Program)"

R2 v1 2026-06-28T06:04:41.853Z