Web Real-Time Communication Using Gesture

Gesture recognition has emerged as a promising technology for enhancing human-computer interaction in various domains. In this paper, we propose a novel approach to gesture recognition using WebRTC (Web Real-Time Communication), a powerful web technology that enables real-time communication between web browsers. Our approach leverages the capabilities of WebRTC to capture live video streams from webcams and process them in real-time for gesture recognition. We present a detailed methodology for integrating WebRTC with a custom deep learning techniques. We evaluate the performance of our system using a diverse set of hand gestures and demonstrate its effectiveness in real-world scenarios. Our experimental results show an average recognition accuracy of 90%, outperforming existing methods in terms of both accuracy and computational efficiency. Potential applications of our approach in interactive web applications, gaming, and augmented reality systems. This work contributes the research on gesture recognition and demonstrates the feasibility of using WebRTC for real-time gesture recognition applications.