Drawing on screen using P5.js and ml5.js
This paper presents a novel approach to creating an interactive drawing application using hand pose detection. The system leverages ML5.js (a machine learning library) and P5.js (a creative coding library) to detect hand gestures in real-time and translate them into drawing actions on a canvas. By tracking the distance between the thumb and other fingers of the user's hand, the system enables the creation of a virtual paintbrush with different colors. Additionally, the system allows users to erase the canvas by joining all fingers of the right hand. The brush size can be dynamically adjusted based on the distance between the forefinger and thumb of the left hand. This project demonstrates the potential of combining machine learning and creative coding for intuitive human-computer interaction.
Authors
- Aryan lakhanpal
- Aryan Pandey
Institutions
- Institute of Management Technology (IN)
Publication Details
- Journal
- International Journal For Multidisciplinary Research
- Published
- 2025-04-20
- DOI
- https://doi.org/10.36948/ijfmr.2025.v07i02.40882
- Primary Topic
- Computational Physics and Python Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00