Abstract:

Gesture Mate is a computer vision application that allows users to interact with devices using hand gestures, providing a more natural and intuitive user interface. It is a system that uses OpenCV and Media Pipe to detect hand gestures and convert them into computer commands. The system allows users to interact with computers using hand gestures, which can be especially useful in situations where traditional input devices are not available or not feasible to use. The system uses OpenCV to detect and track the user's hand in realtime, and Media Pipe to classify the hand gestures based on the detected hand landmarks. The system makes use of video tracking, which is used in continuously detecting the gestures. Based on the position of the fingertips, the system recognizes hand gestures and performs actions such as selecting colors for virtual painting, moving the mouse pointer for virtual mouse control, and adjusting the volume for volume control. Gesture Mate does not use any machine learning modules and relies solely on algorithms for hand detection and tracking to recognize the hand gestures. The application provides a real-time experience for users and can be used for various applications that require gesture recognition. The paper also includes experimental results that demonstrate the accuracy and effectiveness of the system. The experiments show that the system is able to accurately detect and recognize hand gestures in real-time, with high precision. Overall, the Gesture Mate system provides a novel and effective way for users to interact with computers using hand gestures. The system has the potential to be used in a variety of applications, such as gaming, and accessibility.

Description:

OpenCV, Media Pipe, hand detection, tracking.