FaceAI Connect: A Professional Web Application Integrating Real-Time Face Detection and State-Aware AI Chatbot

Author

Tanishka Rajesh Kamble,Prajwal Jadhav

Abstract

 In recent years, integrating Artificial Intelligence (AI) into web applications has revolutionized user experience. This paper presents "FaceAI Connect," a professional and responsive web application that combines real-time face detection, facial expression recognition, and an intelligent chatbot system. Using Face-API.js built on top of TensorFlow.js, the system processes webcam feeds directly in the browser to ensure data privacy and reduce server load. The chatbot interacts with users dynamically, adapting its responses based on the detected emotional state of the user. 

The dashboard also features an interactive analytics section powered by Chart.js to visualize user emotions and interactions over time. Our experimental results demonstrate that the proposed architecture achieves high accuracy in expression recognition and provides seamless real-time performance on standard web browsers. This system has broad applications in e-learning, mental health monitoring, and customer service portals.

Keywords

Face Detection, Artificial Intelligence, Chatbot, Emotion Recognition, Face-API.js, WebRTC, Machine Learning.

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References

[1] A. K. Jain, S. Li, "Handbook of Face Recognition", Springer, 2011.
[2] V. Mühler, "Face-api.js: JavaScript API for face recognition in the browser with tensorflow.js", GitHub Repository, 2018.
[3] Y. Zhang, M. Chen, "Client-Side Emotion Recognition for Interactive Chatbots," IEEE Transactions on Affective Computing, vol. 12, no. 4, pp. 45-56, 2021.
[4] Chart.js Contributors, "Simple, clean and engaging HTML5 based JavaScript charts," Chart.js Documentation, 2023.

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