Enhancing User Experience in Air Canvas Through Robust Hand Gesture Recognition Using Computer Vision
Desiya Nanban, Y. Ajitha, Jennifer Selvan, Twajamahoro Jean Pierre, S. Belina V. J. Sara, R. Ragesha · FMDB transactions on sustainable computer letters. · 2024
The Air Canvas Hand Recognition Project aims to revolutionize the way we interact with digital interfaces by leveraging hand gesture recognition to create an intuitive, contactless drawing application. This project combines computer vision, machine learning, and real-time image processing to detect and interpret hand movements, allowing users to draw, write, and manipulate virtual objects in the air. The primary objective is to develop a user-friendly system that can accurately track hand gestures and convert them into digital input without the need for traditional input devices. Live video is captured using a normal webcam and processed using OpenCV, a sophisticated open-source computer vision library. This project uses Media pipe to implement OpenCV for the air canvas. The Air canvas will let users sketch, write, and present without a keyboard, mouse, or digital presentation equipment. It tracks your hand movements to write, draw, and text. It basically accesses the camera, which shows your hand motions live so the spectator can see what you're doing. Computer vision and real-time processing in the Air Canvas Hand Recognition Project enable more natural and intuitive human-computer interactions.