/attention-monitor

Our solution is a computer vision system that translates facial behavior statistics into an engagement metrics as a feedback to inform a teacher about students’ engagement in an online class.

Primary LanguageJavaScriptApache License 2.0Apache-2.0

Online Classroom Attention Tracker (OCAT)

Online Class Attention Tracker

Client: python main.py --userid 123

python main.py --userid kenghooi --host 10.10.0.106

  • Real time data visualization with PyQtGraph
  • Face landmarks -eye, mouth monitor
  • Head pose estimation
  • Server-side, Client-side data streaming(pub,sub)
  • Post-session Attention Metrics Dashboard
  • face,person detection - attendance
  • human pose estimation - engagement, ergonomics

Contributors

William Ardianto, Kenghooi Teoh, Leonard Loh, Choo Wilson.

Pretrained Weights

References