Accessibility And Control the System Using Hand Gestures

The work demonstrates a touchless Human-Computer Interaction (HCI) solution that allows computer users to interface with their PC via natural, intuitive hand movements.Utilizing machine learning and computer vision technology, the system employs a webcam and the mediaPipe framework for real-time identification and tracking of hand landmarks.By smart gesture recognition and mapping, users can carry out system actions like mouse movement, clicking, scrolling, volume and brightness adjustment, screenshot capture, double click and all without ever having to physically touch an input device.It was implemented in Python and incorporates a number of libraries such as OpenCV, mediapipe and other. I.INTRODUCTIONThe COVID-19 pandemic has increased the awareness of the necessity for touchless interfaces in public and personal computing.This project presents a virtual cursor system controlled by hand movements alone, recorded by a regular webcam.These interfaces enable users to control and interact with digital systems using hand and body gestures, offering a touchless and often more immersive experience.It illustrates an inexpensive, accessible contactless system control solution, particularly applicable in hygienic or assistive interface scenarios.The system incorporates gesture debouncing, hold duration checking for sensitive actions, cursor smoothing, and adaptive sensitivity scaling according to frame area.This technology is often used for enhancing accessibility for individuals with disabilities or for creating hands-free interfaces for various devices, including computers, smart TVs, and other interactive environments IARJSET