AI VIRTUAL MOUSE USING COMPUTER VISION TEAM –8 (International Journal of Food and Nutritional Sciences, 2024)
This project presents a hand gesture recognition and control system that utilizes computer vision and machine learning techniques to interpret human hand gestures and perform corresponding actions on a computer. The system employs the MediaPipe framework to detect and track hand landmarks in real-time video feeds, and a custom-built gesture recognition algorithm to classify hand gestures into predefined categories.The project consists of three main modules Hand Recognition Controller, and Gesture Controller. Hand Recognition is responsible for detecting and tracking hand landmarks, classifying hand gestures, and providing gesture information to the Controller module. The Controller module executes actions based on the recognized gestures, while the Gesture Controller module serves as the entry point of the system, capturing video feeds, processing hand landmarks, and passing the information to the Hand Recognition and Controller modules.Overall, this project demonstrates a comprehensive hand gesture recognition and control system.