Undated · Developer
Volume Gesture Control
ML Project
- Discipline
- Machine learningCoding
- For
- Study
- Stack
- PythonMediaPipeOpenCVComputer VisionNumPyPyAudio
- Links
- GitHub
Problem
Physical volume controls are inconvenient when working from a distance or during presentations.
What I built
Developed a hands-free volume control system using computer vision and gesture recognition.
Built a gesture-controlled volume system with 95% accuracy and real-time tracking at up to 60 FPS
What went into it
- Conceptualised and developed a gesture-controlled volume control system using computer vision with real-time hand tracking via the MediaPipe library, achieving a 95% accuracy rate.
- Mapped the distance between thumb and index finger to system volume adjustments, providing intuitive touchless audio control.
- Implemented visual feedback through OpenCV overlays, resulting in lossless hand tracking at up to 60 FPS for smooth real-time interaction.
- Developed robust hand detection modules using Python, integrating OpenCV, MediaPipe, PyAudio, and NumPy for a complete gesture recognition pipeline.