Gesture Recognition System for Human-Computer Interaction using Computer Vision

Abstract

In order to improve human-computer interaction (HCI), this paper presents the Gesture Recognition System (GRS), which makes use of computer vision techniques. With hand gestures recorded by a webcam, users can operate computer functions with this system. The goal of the paper is to use the Python MediaPipe library to create a gesture recognition algorithm that is both accurate and efficient. Hand tracking, landmark detection, and gesture classification are all part of the methodology. Real-time experiments are used to assess the system's performance, and optimization strategies are investigated to improve speed and accuracy. The outcomes show how well the suggested system works to facilitate natural and intuitive computer interaction, opening up possibilities for a wide range of applications.