GESTURE RECOGNITION BASED VIRTUAL KEYBOARD AND MOUSE SYSTEM

Abstract

Human–Computer Interaction (HCI) has significantly evolved with the development of computer vision and machine learning technologies. Traditional input devices such as keyboards and mice require physical contact, which may limit accessibility and create hygiene concerns in shared environments. Gesture recognition technology provides a touchless interaction method by allowing users to control computers using hand movements captured through cameras. This paper proposes a Gesture Recognition Based Virtual Keyboard and Mouse system that enables users to perform computer operations using hand and facial gestures without relying on physical hardware devices. The system utilizes computer vision techniques to detect hand movements, eye gestures, and facial landmarks from real-time video captured through a webcam. These gestures are interpreted using image processing algorithms and mapped to corresponding mouse and keyboard actions such as cursor movement, clicking, scrolling, and typing. The system is implemented using Python with libraries such as OpenCV, Dlib, and PyAutoGUI. Experimental results demonstrate that the proposed system provides an efficient and user-friendly method of controlling computers with improved accessibility and reduced dependency on physical input devices. This approach has potential applications in assistive technologies, smart classrooms, virtual reality environments, and interactive display systems.