標題: Generating Pointillism Paintings Based on Seurat's Color Composition
作者: Wu, Yi-Chian
Tsai, Yu-Ting
Lin, Wen-Chieh
Li, Wen-Hsin
資訊工程學系
Department of Computer Science
公開日期: 1-Jun-2013
摘要: This paper presents a novel example-based stippling technique that employs a simple and intuitive concept to convert a color image into a pointillism painting. Our method relies on analyzing and imitating the color distributions of Seurat's paintings to obtain a statistical color model. Then, this model can be easily combined with the modified multi-class blue noise sampling to stylize an input image with characteristics of color composition in Seurat's paintings. The blue noise property of the output image also ensures that the color points are randomly located but remain spatially uniform. In our experiments, the multivariate goodness-of-fit tests were adopted to quantitatively analyze the results of the proposed and previous methods, further confirming that the color composition of our results are more similar to Seurat's painting style than that of previous approaches. Additionally, we also conducted a user study participated by artists to qualitatively evaluate the synthesized images of the proposed method.
URI: http://dx.doi.org/10.1111/cgf.12161
http://hdl.handle.net/11536/22313
ISSN: 0167-7055
DOI: 10.1111/cgf.12161
期刊: COMPUTER GRAPHICS FORUM
Volume: 32
Issue: 4
起始頁: 153
結束頁: 162
Appears in Collections:Articles


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