Facial Expression Recognition using Machine Learning

Abstract

This is a research based project named “FACIAL EXPRESSION RECOGNOTIONUSING MACHINE LEARNING.” Nowadays, Machine Learning(ML) has played a vital role in modern technology. For facial detection, recognition, and detection of facial expressions, artificial intelligence (AI)-based computer technology is employed. Machinelearning has a branch called "Deep Learning"(DL). For tracking and classifying the human face, several approaches are necessary. Deep learning algorithms have been outperforming traditional methods in computer vision tests. Facial detection and recognition applications are used in various fields to ensure security, identification, andverification. Facial emotion recognition helps identify a person’s feelings fromfacial expressions. In this paper, we will work on detecting human faces, recognizing faces accurately, and classifying facial expressions.To detect and identify facial expressions accurately, we used deep learning algorithms. We divided our work into three segments: the first segment, where we are going to capture a face in real-time and to detect the faceaccurately, for that purpose we are using the Haar-Cascade detection algorithm; nowinthe second segment, where it processes the first part’s input based on face feature as well as the database we used (CNN). The final segment is where it authenticates the face sothat it can classify the expression of the face into such categories as happy, sad, disgust, surprise, angry, and neutral.The proposed work’s objective is to simplify face detection, recognition, and emotion recognition.In short, we planned to ensure the performance of the automatic face expression detection and recognition systems is dignified with accuracy.