VirtuBoard Project
Developed a virtual drawing application using OpenCV and MediaPipe to create an interactive "air canvas" that allows users to draw and interact with a virtual board through hand gestures detected by a webcam.
Key Features:
- Real-Time Hand Gesture Detection: Leveraged MediaPipe to accurately detect and track hand landmarks in real-time, allowing users to draw on a virtual canvas with their finger movements.
- Dynamic Pen Control: Implemented keyboard shortcuts to dynamically change pen colors (red, green, blue, white) and clear the canvas, enhancing user interaction and control.
- Seamless Canvas Integration: Blended the virtual drawing canvas with the live webcam feed, ensuring a smooth and immersive drawing experience.
- Interactive User Interface: Designed an intuitive interface with real-time feedback, making it easy for users to interact with the virtual board.
Technologies Used: Python, OpenCV, MediaPipe, NumPy
Responsibilities:
- Conceptualized and developed the application, integrating real-time video processing and hand tracking.
- Implemented gesture recognition to interpret finger movements as drawing commands.
- Created an efficient blending mechanism to overlay the virtual canvas onto the live video feed.
- Developed and tested keyboard controls for dynamic pen color changes and canvas clearing.
- Ensured smooth and responsive performance for an engaging user experience
