WaveMouse

WaveMouse

Krishnali Patil1, Esha Ambekar2, Diksha Monde3, Priya Sahu4, Prof.Geeta Arwindekar5

1,2,3,4Students, Department of Information Technology Engineering, Datta Meghe College of Engineering, Airoli, Navi Mumbai, Maharashtra, India.

5Assistant Professor, Department of Information Technology Engineering, Datta Meghe College of Engineering, Airoli, Navi Mumbai, Maharashtra, India.

ABSTRACT
The proposed system introduces a touch-free method for cursor control, replacing traditional physical mice with a camera-based approach. By leveraging MediaPipe and OpenCV alongside machine learning and deep learning techniques, it accurately recognizes hand gestures for actions like navigation, clicking, and scrolling. Unlike wired, wireless, or Bluetooth mice, this system removes the dependency on external hardware or power-based dongles. It employs CNN models for precise gesture recognition and processing. Python and OpenCV serve as the core technologies, with the camera acting as the input device and providing real-time feedback for user adjustments. Gesture recognition advancements open new possibilities and challenges for virtual interaction. Reducing physical contact, especially in the post- COVID-19 era, enhances accessibility and hygiene. Additionally, the system integrates a chatbot to assist users with navigation, troubleshooting, and understanding gesture controls, improving usability. This innovation can drive further research and practical applications in virtual environments. Hand gestures can replace traditional mouse functions like clicking and dragging. The system offers a seamless, hardware-free computing experience.

KEYWORD
convolutional neural network, machine learning, OpenCV