This project is the implementation of the paper "ExpresSense: Exploring a Standalone Smartphone to Sense Engagement of Users from Facial Expressions Using Acoustic Sensing", which has been accepted to CHI 2023
Multi-task Learning for Student Mental State Recognition from Facial Expressions in-the-wild
Real-time emotion and engagement detection system using OpenCV and TensorFlow, featuring deep-learning face detection, emotion recognition, engagement scoring (0–100), CSV logging, and time-series visualization. Edge-ready and fully offline.
Add a description, image, and links to the engagement-detection topic page so that developers can more easily learn about it.
To associate your repository with the engagement-detection topic, visit your repo's landing page and select "manage topics."