As one of the most successful multimedia tools for digital media and creative industry, computer-aided drawing system assists users to convert the input real photos into painterly style images. Nowadays, it is widely developed as cloud brush engine service in many creative software tools and applications of artistic rendering such as Prisma, Photoshop Cloud, and Meitu, because the machine learning server has more powerful than the stand-alone version. In this paper, we propose a web collaborative Stroke-based Learning and Rendering (WebSBLR) system. Different from the existing methods that are mainly focused on the artistic filters, we concentrate on the stroke realistic rendering engine for browser on client using WebGL and HTML5. Moreover, we implement the learning-based stroke drawing path generation module on the server. By this way, we enable to achieve the computer-supported cooperative work (CSCW), especially for multi-screen synchronous interaction. The experiments demonstrated our method are efficient to web-based multi-screen painting simulation.It can successfully learn artists’ styles and render pictures with consistent and smooth brush strokes.
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We firstly thank anonymous reviewers for their helpful comments. This work was supported in part by the National Natural Science Foundation of China under Project 61602088, Project 61572108, Project 61632007, and Project 61502339, the National Thousand-Young-Talents Program of China, the Fundamental Research Funds for the Central Universities under Project ZYGX2014Z007, Project ZYGX2015J055 and Project ZYGX2016J212.
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Xie, N., Zhao, T., Yang, Y. et al. Web-based SBLR method of multimedia tools for computer-aided drawing. Multimed Tools Appl 78, 799–816 (2019). https://doi.org/10.1007/s11042-018-5949-x
- Multimedia tools
- Artistic stylization