Facial Expression Recognition Using Convolutional Network

Abstract

Abstract: This paper focuses on Emotion Recognition using facial expressions. It aims to detect facial expressions accurately and efficiently. Convolutional Neural Network has developed to help in recognizing emotions through facial expressions and classify them into seven basic categories which are: happy, sad, neutral, surprise, fear, disgust, and angry. So, Convolutional Neural Network is implemented to extract relevant features of the input images and classify them into seven labels. For evaluating the proposed model, Facial Emotion Recognition 2013 dataset is usedso that the model achieves the best accuracy rate. Facial expression recognition has been an activearea of research over the past few decades, and it is still challenging due to the high intra-class variation.