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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM38050

Hand Gesture Recognition for Interactive On-Screen Drawing with Real-Time Subtitling for Teaching

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM38050

Volume:

8 |

10 |

Oct 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM38050

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

KL

Kiran Likhar

SL

Shivani Lahurkar

RS

Ravi Shahu

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Abstract

This research presents the development of an innovative educational tool leveraging hand gesture recognition for interactive on-screen drawing with real-time subtitling. Built on OpenCV and Python, the platform enables educators to draw and manipulate digital content through intuitive hand gestures, enhancing classroom engagement. Additionally, real-time subtitle generation offers accessibility for hearing-impaired students by converting drawn content into text notes. This system addresses key challenges in traditional digital drawing tools, such as limited interaction methods and accessibility, aiming to deliver a more inclusive learning environment. Preliminary results indicate high recognition accuracy, smooth interaction, and potential for broader educational applications. Future improvements will involve expanding the gesture set and refining accuracy for complex gestures.

KEYWORDS

Hand Gesture Recognition Interactive Learning Real-Time Subtitling Educational Technology OpenCV

Cite This Article

Kiran Likhar, Shivani Lahurkar, Ravi Shahu, "Hand Gesture Recognition for Interactive On-Screen Drawing with Real-Time Subtitling for Teaching," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 10, Oct 2024. https://doi.org/10.55041/IJSREM38050

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Publication Date

10/19/2024

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Review Rounds: 2

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