  Neural network based algorithms has shown success in many applications. In
image processing, Convolutional Neural Networks (CNN) can be trained to
categorize facial expressions of images of human faces. In this work, we create
a system that masks a student's face with a emoji of the respective emotion.
Our system consists of three building blocks: face detection using Histogram of
Gradients (HoG) and Support Vector Machine (SVM), facial expression
categorization using CNN trained on FER2013 dataset, and finally masking the
respective emoji back onto the student's face via homography estimation. (Demo:
https://youtu.be/GCjtXw1y8Pw) Our results show that this pipeline is
deploy-able in real-time, and is usable in educational settings.
