A Review on Interactive Air Canvas Application
Dr.Chethan BK Department of Computer Science and Engineering (Artificial Intelligence
and Machine Learning) Vidyavardhaka College of Engineering
Mysuru, India chethanbk@vvce.ac.in
Sharvari R
Department of Computer Science and Engineering (Artificial Intelligence and Machine Learning)
Vidyavardhaka College of Engineering Mysuru, India sharvarir105@gmail.com
Rahul SB
Department of Computer Science and Engineering (Artificial Intelligence and Machine Learning)
Vidyavardhaka College of Engineering
Mysuru, India gowdasb13@gmail.com
Vaishnavi S
Department of Computer Science and Engineering (Artificial Intelligence and Machine Learning)
Vidyavardhaka College of Engineering Mysuru, India 2802vaishnavi@gmail.com
Reshma R
Department of Computer Science and Engineering (Artificial Intelligence and Machine Learning)
Vidyavardhaka College of Engineering Mysuru, India reshmareshu045@gmail.com
Abstract— In today's dynamic landscape of human- computer interaction, there's a growing demand for interfaces that seamlessly merge the digital and physical realms. Traditional input methods like keyboards and mice, though reliable, fall short in meeting the expectations of users seeking more intuitive engagement with technology. The Air Canvas project, leveraging OpenCV and MediaPipe, addresses this need by creating an interactive drawing platform that monitors real- time hand movements. Users can paint in mid-air, translating hand gestures into vibrant strokes on a digital canvas. This work highlights the potential of computer vision and gesture recognition to bridge the gap between technology and art, offering immersive and creative applications. Writing, a fundamental form of communication, is explored through a motion-to-text converter for smart wearables. By tracking finger movements using computer vision, this system generates text for purposes like texting and emails, presenting a valuable communication tool, especially for the deaf community.
Keywords— OpenCV, MediaPipe, Interfaces, Real-time hand movements, Gesture Recognition.
