Emotion Detection Using Deep Learning Approach

When we search for the word ‘sad’ on an online search engine, we can find different types of images like broken hearts, rainy days, sad emoticons, & people sitting with their heads down. These pictures are distinct. Yet they express the same emotion ‘sadness’. Different researchers have concentrated on emotion detection from images using facial expressions, but only a few researches are found on emotion detection from both face & non-face images. We create a dataset by collecting data from various social media. We propose a method for emotion classification from images where we adopt the deep learning concept along with a few preprocessing steps including data augmentation & filtering. Our approach classifies images into five different emotional categories. Our approach shows promising experimental results in emotion classification. The accuracy of our proposed approach is 85 percent.