Face Detection and Facial Expression Recognition with Deep Learning
Face detection and facial expression recognition have many potential benefits in healthcare, automotive, gaming, and many other industries. In this project, we implemented a face detection model using Detectron2 and several different machine learning algorithms such as k-nearest neighbors (”KNN”), multi-layer perceptron (”MLP”), and convolutional neural net (”CNN”) for the facial expression recognition. Our models are trained on two separate imagebased data sets. We were able to achieve a 70% AP50 with our face detection model and our best facial expression recognition model achieved an accuracy of 65%.