Airflow Canvas


EOI: 10.11242/viva-tech.01.06.014

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Citation

Ujjval Solanki, Sohel Qureshi, Rajkamal Verma, Prof. Krutika Vartak, "Airflow Canvas", VIVA-IJRI Volume 1, Issue 6, Article 1, pp. 1-5, 2023. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

Airflow Canvas – Digital Art with Hand Gesture is an application that introduces real-time drawing functionalities through the detection of a green object within the camera's live feed. Leveraging the robust foundation of OpenCV, this application excels in tracking the movements of the green object in the surrounding air, translating these movements into dynamic drawing actions directly on the screen. The application uses Convolutional Neural Network (CNN) model, finely tuned to accurately recognize and classify the shapes generated by the user during the drawing process. This intelligent integration of computer vision techniques and advanced deep learning algorithms empowers users with an unparalleled, intuitive, and interactive drawing experience. In Airflow Canvas – Digital Art with Hand Gesture essence, represents an exceptional tool for fostering creative exploration and expression.

Keywords

– Convolutional Neural Network (CNN) model, Open CV, TensorFlow.

References

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