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Home / Archives / Volume-6 / Issue-1 / Article-4

Volume - 6 | Issue - 1 | march 2024

Virtual Painting through Hand Gestures: A Machine Learning Approach Open Access
R. Shanthi  , S. Abdul Azeez, N. Deepak Kumar  232
Pages: 39-49
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Cite this article
Shanthi, R., S. Abdul Azeez, and N. Deepak Kumar. "Virtual Painting through Hand Gestures: A Machine Learning Approach." Journal of Ubiquitous Computing and Communication Technologies 6, no. 1 (2024): 39-49
Published
30 April, 2024
Abstract

The hand gesture paint application represents an innovative venture in the realm of computer vision, harnessing the capabilities of the MediaPipe library and OpenCV to develop a sophisticated painting tool driven by hand gestures. By leveraging these powerful frameworks, the application enables users to express their creativity through intuitive gestures captured by a webcam. At its core, the work seeks to redefine the conventional painting experience by providing users with a seamless interface controlled entirely by hand movements. Through the integration of the MediaPipe library and OpenCV, users can effortlessly draw, erase, and switch between various drawing tools, all with the fluidity of natural hand gestures. By eliminating the need for traditional input devices, the hand gesture paint application offers a novel approach to digital art creation, empowering users to engage directly with their canvas in a more intuitive and immersive manner. Through this innovative blend of technology and creativity, the application opens up new avenues for artistic expression, inviting users to explore the boundless possibilities of digital painting through the simple movement of their hands.

Keywords

Virtual painting Hand gesture recognition Gesture-based interaction Computer vision Machine Learning Human-computer interaction

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