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Augmented Reality (AR) systems like Google’s Quick, Draw! and Microsoft’s
Azure Spatial Anchors have advanced in using computer vision and
AI for interactive applications. However, these platforms face challenges in
recognizing user drawings accurately due to variations in sketch styles, lighting
conditions, and inconsistent rendering. Additionally, they often have
steep learning curves, which impact user experience and accessibility. The
main challenges of current systems include variability in user sketches, poor
performance under different lighting, and non-intuitive interfaces, leading to
frustrations like delayed responses and inaccurate recognition. These issues
make existing systems less effective, especially when dealing with complex
drawings in real-time. A comprehensive system is proposed that combines
deep learning-based feature extraction, AR frame detection, AR rendering,
game physics, and real-time processing. It also integrates mobile AR control
synchronization and AI-powered hand gesture recognition. This platform enables
users to play games like Sudoku, block games, and snake games from
hand-drawn images, providing a seamless, real-time experience by combining
computer vision, deep learning, and AR.
Keywords:
Augmented Reality (AR),Hand-Drawn Image Recognition,Real-Time Interaction,Gesture Recognition,AR Game Framework,User Experience in AR
Cite Article:
"An AI-Powered AR Game Platform for Hand-Drawn Sketch Recognition", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.b289-b320, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504138.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator