An Efficient Method for Automatic Emotion Detection from Facial Expression

The human face plays an important role for automatic recognition of emotion in the �eld of identi�cation of human emotion and the interaction between human and computer for some real application like driver state surveillance, personalized learning, health monitoring, automatic music player, etc. In this article we have tried to design an automated framework for emotion detection using facial expression. Facial expression recognition system require to overcome the human face having multiple variability such as colour, orientation, expression, posture, texture and so on. Facial Expression Recognition is challenging problem up till now because of many reasons, moreover, it consists of three sub challenging tasks face detection, facial feature extraction and expression classi�cation. PCA (Principal Component Analysis) analysis is used to detect the face from the captured image. Extended local binary pattern is used for feature extraction of the face. Emotion detection is done by calculating the Euclidian distance between the feature points. Emotions are classified into seven major categories viz. joy, sorrow, surprise, disgust, fear, anger, neutral.