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Stream/Area:
-
Subject:
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Paper ID:
10.55041/IJSREM44540
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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.
– Our project “GestureFlow: Advanced Hand Gesture Control System” leverages real-time computer vision and deep learning techniques to create a robust, touchless control interface using hand gestures. The system utilizes MediaPipe Hands for efficient hand landmark detection and processes dynamic hand movements and finger configurations to identify a wide range of intuitive gestures such as swipes, pinches, and specific finger patterns. These gestures are mapped to actions like mouse control, clicks, volume adjustment, media playback, screenshot capture, window management, and many more. The system includes smoothed cursor tracking, velocity-based gesture recognition, and responsive command execution to ensure real-time performance. It also offers dynamic visual feedback and adaptive handling of gesture timing to improve precision and usability. Overall, the project presents an accessible, multi-functional human-computer interaction framework aimed at enhancing hands-free control and reducing reliance on traditional input devices in everyday computing environments.
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Publication Date
4/14/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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