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Neural network based algorithms has shown success in many applications. Inimage processing, Convolutional Neural Networks (CNN) can be trained tocategorize facial expressions of images of human faces. In this work, we createa 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 ofGradients (HoG) and Support Vector Machine (SVM), facial expressioncategorization using CNN trained on FER2013 dataset, and finally masking therespective emoji back onto the student's face via homography estimation. (Demo:https://youtu.be/GCjtXw1y8Pw) Our results show that this pipeline isdeploy-able in real-time, and is usable in educational settings.

Real-Time Facial Expression Emoji Masking with Convolutional Neural Networks and Homography