Facial Emotion Detection Using Convolutional Neural Networks

The most important aspect to understand human behavior is face reading. The expression speaks better than words. The expressions of face reflect human perspective and its mental state. The aim of this paper is to sight faces from image, extract facial expressions and classify them into different emotions like sad, happy, anger, and neutral. This paper discusses a technique named facial emotion recognition using convolutional neural networks (FERC). There are two parts in convolution neural networks (CNN) first removal of background from image and second facial feature extraction (EV). This application is used in medical treatment, teaching field, police investigation, human robot interface.