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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM42815
Volume:
9 |
3 |
Mar 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
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.
KEYWORDS
Publication Date
3/22/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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