A comparative study of machine learning and deep learning algorithms for recognizing facial emotions

This article compares the performance of three algorithms for Facial Emotion Recognition (FER). The algorithms chosen include one machine learning model - SupportVector Machine (SVM) and two deep learning models - Convolutional Neural Network (CNN) and VGG16. All three algorithms were implemented using Python and evaluated on FER2013 dataset. The metrics used for comparison were testing accuracy, training time and the size of the weights file. The best performing algorithm from the study is used to implement FER in real time on a live video stream. The implementation details are presented and results are discussed.