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Proceedings of the 2023 Eighth International Conference on Research in Intelligent Computing in Engineering

Annals of Computer Science and Information Systems, Volume 38

Immersive Virtual Painting: Pushing Boundaries in Real-Time Computer Vision using OpenCV with C++

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DOI: http://dx.doi.org/10.15439/2023R58

Citation: Proceedings of the 2023 Eighth International Conference on Research in Intelligent Computing in Engineering, Pradeep Kumar, Manuel Cardona, Vijender Kumar Solanki, Tran Duc Tan, Abdul Wahid (eds). ACSIS, Vol. 38, pages 41–50 ()

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Abstract. This paper presents an innovative approach for immersive virtual painting using real-time computer vision techniques. A meticulously crafted color detection algorithm implemented in C++ and OpenCV achieves up to 97.4\% accuracy in identifying specified hues from live video feeds. The detected colors are seamlessly translated into vibrant brush strokes rendered on a digital canvas in real-time. The algorithms exhibit remarkable speed, analyzing each frame within 15ms, enabling ultra-low latency painting interactions. Optimization strategies involving parallel processing and code optimizations provide further performance gains. Comparative analysis reveals 3-4x faster execution using C++ over Python for color detection. The platform delivers an intuitive, natural, and uninterrupted painting experience, as validated through user studies. By automating color detection and digital rendering, this research transforms virtual painting from a passive activity to an immersive form of human-computer co-creativity. The fusion of computer vision, rendering algorithms, and optimization techniques establishes new frontiers in interactive digital art platforms and reshapes human-computer collaboration. Highlights: This research achieves exceptional accuracy in real-time color detection, with up to 97.4\% precision in identifying specified hues across thousands of video frames. The integrated system enables seamless user interaction for natural virtual painting expressions, eliminating disruptive color selection interruptions. Comparative analysis reveals significant 3-4x performance gains by implementing the algorithms in C++ instead of Python, underscoring the efficiency benefits of C++ for real-time computer vision applications. User studies validate the immersive experience delivered by the platform, with users highlighting the responsiveness, precision, and intuitive interaction unmatched by traditional virtual painting tools. The proposed techniques establish a new paradigm in real-time computer vision, pushing the boundaries of virtual creativity platforms and reshaping human-computer collaboration in the arts.

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