A business needs to work on the right problems to be able to grow. These problems can only be provided by the people who are using the product or service made by the business. Accurate customer feedback is what allows a business to set its priorities straight. Thus, in this paper, we have attempted to make a simple and easy-to-use tool from already existing resources that will provide real-time customer reviews to business owners which will help them in improving their service. The result of the model execution includes the performance of various concepts that are face detection, face recognition, emotion detection, storage in the database and calculations to find the positive (happy and surprise), negative emotion (sad, fear, angry, and disgust) and neutral (neither positive nor negative). For understanding the functioning of the model, OpenCV and CNN fundamentals have been explained in detail in the paper. This paper concludes by discussing the future scopes of the tool created. In the past, CCTV cameras were used for security only, but now these can be used to get customers’ real-time reviews also which will be very beneficial to them to improve their services. This will allow them to grow and compete in the future, where survival is going to depend on how well a business uses AI in its day-to-day operations.

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Automated Customer Feedback Generation Using Facial Expression Through OpenCV

  • Ayushi,
  • Deepak Arora

摘要

A business needs to work on the right problems to be able to grow. These problems can only be provided by the people who are using the product or service made by the business. Accurate customer feedback is what allows a business to set its priorities straight. Thus, in this paper, we have attempted to make a simple and easy-to-use tool from already existing resources that will provide real-time customer reviews to business owners which will help them in improving their service. The result of the model execution includes the performance of various concepts that are face detection, face recognition, emotion detection, storage in the database and calculations to find the positive (happy and surprise), negative emotion (sad, fear, angry, and disgust) and neutral (neither positive nor negative). For understanding the functioning of the model, OpenCV and CNN fundamentals have been explained in detail in the paper. This paper concludes by discussing the future scopes of the tool created. In the past, CCTV cameras were used for security only, but now these can be used to get customers’ real-time reviews also which will be very beneficial to them to improve their services. This will allow them to grow and compete in the future, where survival is going to depend on how well a business uses AI in its day-to-day operations.