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Understanding Customer Reviews using Facial Expression Recognition System

The 21st century marks the beginning of Industry4.0 with data as primary driving force. The abundant availability of high-resolution videos, images of numerous industry processes, human activities coupled with sophisticated data driven technologies stands a base for evolution of latest technologies like image processing, industrial process automation. Here, the aim is to adapt the image processing technology to understand human behaviors based on the facial expressions drawn from various persons and apply that to evaluate customer review in retail market. The objective is to build a deep learning facial expression recognition classification model using OpenCV, Convolutional Neural Networks (CNN) libraries backed by TensorFlow framework and the trained model is deployed to a web interface using Flask API and generate customer review sheet. Attempts are made to analyze and classify data into 3 customer reviews as Satisfied, Not Satisfied and Neutral. These classification algorithms are deployed to find the real-time facial expression on videos and images to find the probability that an image belong to specific class data and generate customer review sheet.