Abstract
We propose a novel method that automatically analyzes stroke-related artistic styles of paintings. A set of adaptive interfaces are also developed to connect the style analysis with existing painterly rendering systems, so that the specific artistic style of a template painting can be effectively transferred to the input photo with minimal effort. Different from conventional texture-synthesis based rendering techniques that focus mainly on texture features, this work extracts, analyzes and simulates high-level style features expressed by artists’ brush stroke techniques. Through experiments, user studies and comparisons with ground truth, we demonstrate that the proposed style-orientated painting framework can significantly reduce tedious parameter adjustment, and it allows amateur users to efficiently create desired artistic styles simply by specifying a template painting.
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This work is supported by Fok Ying-Tong Education Foundation of China under Grant No. 131065 and the International Joint Project from the Royal Society of UK under Grant No. JP100987.
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Zang, Y., Huang, H. & Li, CF. Stroke Style Analysis for Painterly Rendering. J. Comput. Sci. Technol. 28, 762–775 (2013). https://doi.org/10.1007/s11390-013-1375-8
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DOI: https://doi.org/10.1007/s11390-013-1375-8