Customer Satisfaction Recognition using Facial Features

Abstract: Facial Emotion, Age and Gender are important factors in Human Computer Interaction. According to different surveys, non-verbal components convey two thirds of human communication. Among non-verbal components, facial features are one of the main information channels. Hence, we are proposing a CNN Model to recognize the facial Emotions, Age and Gender to recognize Customer Satisfaction. The technology used is Convolutional Neural Networks from Machine Learning. The dataset consisting of pixel sets of images of people with different Emotions, Age and Gender is used to train the model. The proposed model is a real time model used to detect the face using live video stream and determine the Emotion, Age and Gender and hence in turn determine if the customer is satisfied or not. The main advantage of the proposed system is that it uses real time live video stream through webcam. The key concept of this system is to use Machine Learning algorithm to determine Emotion, Age and Gender of Customer. Key Words: Customer Satisfaction Recognition, Convolutional Neural Network, OpenCV, Emotion, Age ,Gender, Machine learning.