• Ashwin Singh
• Rajinder Singh
• Sahil Tambe
• Shivam Upadhyay
• Umesh Mohite

The continuous advancement in technology necessitates the modernization of various sectors. With the evolution of sophisticated devices, it is now possible to virtually control systems through human gestures. When working with painting applications, individuals often encounter challenges in expressing their imagination through traditional methods. The Air Canvas Project addresses this issue by focusing on the development of a motion-to-text converter. This project specifically concentrates on the advancement of a hand tracking system, which serves as a virtual pen for creating drawings and shapes, as well as functioning as an eraser. The implementation utilizes the Open Computer Vision Library (OpenCV) and Mediapipe for efficient hand tracking. In contrast to existing projects that may involve complex processes and time-consuming methodologies for hand-drawn creations, our project leverages new technologies and simplified approaches. The system employs a camera to track hand movements, enabling users to draw or add text effortlessly by waving their hands.

Air Writing, Mediapipe, OpenCV, Hand Tracking, Gesture-Based Interaction, Computer Vision, Human- Computer Interaction, Machine Learning

"SMART WHITE BOARD", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.h251-h259, March-2024, Available :http://www.jetir.org/papers/JETIR2403733.pdf

"SMART WHITE BOARD", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. pph251-h259, March-2024, Available at : http://www.jetir.org/papers/JETIR2403733.pdf