Design and Evaluation of a Deep Learning Algorithm for Emotion Recognition
R. Raja Subramanian, Chunduri Sandya Niharika, Dondapati Usha Rani, P. Geetha Pavani, Ketepalli Poojita Lakshmi Syamala
Abstract
Facial emotion recognition is one of the most interesting research areas where many researchers are actively participating over the past few decades. This paper attempts to discuss about the application of emotion recognition where seven different emotions such as happy, sad, neutral, angry, surprise, fear and disgust are obtained. Humans can produce thousands of emotions in different situations which have different meanings, intensities and complexities. By using convolutional neural network (CNN) algorithm, an accuracy of about 89%has been achieved. It is the simplest way of all. For better results deep learning and neutral networks have been used. Our proposed deep learning model helps us in focusing important features in humans face to detect emotion using multiple datasets such as FER-2013 and image dataset.