Abstract
Abstract: Emotion is a subjective phenomenon, utilizing knowledge and science behind tagged data and extracting the components that comprise it has been a difficult challenge. With the advancement of deep learning in computer vision, emotion identification has become a popular research topic. This Project presents feature extraction of facial expressions using a neural network combination for the recognition of various facial emotions (sad, happy, neutral, angry, surprised, fear). Convolution Neural Network has been used to achieve a accuracy of 75%, which have excellent recognition of image features. Haar-Cascade has been used to find the region that contains the face, so the model has to only work with the region which has face.
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