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首页> 外文期刊>Multimedia Tools and Applications >Automatic portrait oil painter: joint domain stylization for portrait images
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Automatic portrait oil painter: joint domain stylization for portrait images

机译：自动人像油画家：人像图像的联合域样式

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摘要

Everyone has the dream of being in the center of famous art paintings, admired by numerous future generations. However, the dream came true at a huge cost of the painter's commission in old days. In our paper, another practical choice is provided for everyone to achieve that dream - an automatic portrait oil painter transferring some artistic styles from one single reference painting. To address this issue, we propose a joint-domain image stylization approach, particularly for portrait oil paintings. From the view of artistic appreciation, we analyze an amount of oil painting art works and summarize three critical factors to depict the figure, i.e. color, structure and texture. Based on this point, we separate and represent an artistic work into these three domains. Then, considering their intrinsic properties and following an art creation route, we propose the corresponding approaches to jointly model and transfer the features in these domains. First, a swatch-based color adjustment is proposed to recolor the tone of the input image based on semantic regions corresponding to the references. Second, the main structures of the input image is maintained by sparse reconstruction. Third, a coarse-to-fine texture synthesis is used to enhance the detail oil painting patterns. Extensive experimental results demonstrate that the proposed method achieves desirable results compared with state-of-the-art methods in not only transferring the styles from references but also keeping consistent contents with the given portrait.
机译：每个人都梦想着成为著名艺术绘画的中心，并受到众多后代的钦佩。然而，梦想成真是在过去画家的委托下付出的巨大代价。在我们的论文中，为每个人提供了另一个可行的选择来实现这一梦想-自动肖像画家从一幅参考画中转移了一些艺术风格。为了解决这个问题，我们提出了一种联合域图像样式化方法，特别是对于肖像油画。从艺术欣赏的角度出发，我们分析了大量油画艺术品，并总结了三个关键因素来描绘人物形象，即色彩，结构和质地。基于这一点，我们将艺术作品分为这三个领域并将其表示出来。然后，考虑到它们的内在属性并遵循艺术创作路线，我们提出了相应的方法来共同建模和传递这些领域中的特征。首先，提出了一种基于色板的颜色调整，以根据与参考相对应的语义区域为输入图像的色调重新着色。其次，输入图像的主要结构是通过稀疏重建来维护的。第三，使用粗糙到精细的纹理合成来增强细节油画图案。大量的实验结果表明，与现有方法相比，该方法不仅可以从参考文献中转移样式，而且还可以与给定肖像保持一致的内容，因此可以达到理想的效果。

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