AHEAD: Adaptive Hierarchical Edge Detection for Real-Time Artistic Stylization

Adaptive Hierarchical Edge Detection: Enhancing Real-Time Artistic Stylization in Computer Graphics | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Adaptive Hierarchical Edge Detection: Enhancing Real-Time Artistic Stylization in Computer Graphics Lino Roshaan M.K. This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8849147/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract Non-Photorealistic Rendering (NPR) has gained prominence in gaming, offering stylized, artistic expressions over hyperrealism. This paper introduces a unified, real-time post-processing shader architecture that leverages adaptive sensitivity and a three-layer hierarchy to overcome limitations in traditional edge detection algorithms. By employing a Max-pooling fusion technique, our method preserves edge integrity and recovers details in low-light areas, facilitating shorter asset development times. Experimental results demonstrate a significant reduction in manual tuning efforts, achieving high-fidelity artistic stylization with minimal performance overhead across diverse game engines. The complete source code and usage guidelines necessary to reproduce these results are publicly accessible at https://github.com/Chronos-Asteri/AHEAD-AdaptiveEdgeDetection (DOI: https://doi.org/10.5281/zenodo.18765546 ). Non-Photorealistic Rendering Edge Detection Real-time Shaders Max-pooling Fusion Game Development Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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