Emotion Analysis and Gender Identification Using Partial Face Detection

Emotion plays a vital role in our day to day life. They can drag a human to such a state where he can feel helpless and can make some decisions which are not right for him. So, we design a machine learning model with the help of image processing and computer vision, which can detect the emotion of a person even if his face is partially visible. We are able to build a successful model with the help of CNN (Convolutional Neural Network), and in this model, we use the FER 2013 facial expression dataset with the help of which we get the validation accuracy of 72%. In this project, we combine two major projects that are facial emotion recognition and gender classification and we are able to detect the gender and emotion in live time even if the face is partially visible.