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Learning to Recognize the Art Style of Paintings Using Multi-cues

机译:学习使用多线索识别绘画的艺术风格

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Visual characteristics of paintings display high-level semantic concept: art style to the viewers. Classification of art style depends mainly on human knowledge and experience, which remains a big challenge for computer vision. In this paper, based on careful studies on art literature, we propose a simple but effective method to automatically identify the art style between the Chinese wash painting and the foreign art painting. The efficiency of our method lies on that three cues: color contrast, blank-leaving and uniformity of illumination are utilized to recognize the art style of one image. Experiments results show that, our method outperforms state-of-the-art approaches, yielding higher precision while requiring less computation time. Using the cues presented in this paper, our method can successfully identify whether one painting belongs to Chinese or foreign art style.
机译:绘画的视觉特征表现出高级的语义概念:艺术风格给观赏者。艺术风格的分类主要取决于人类的知识和经验,这仍然是计算机视觉的一大挑战。本文在对艺术文献进行认真研究的基础上,提出了一种简单有效的方法来自动识别中国水墨画与外国水墨画之间的艺术风格。我们的方法的效率在于三个线索:色彩对比度,空白留白和照明均匀性被用来识别一张图像的艺术风格。实验结果表明,我们的方法优于最新方法,具有更高的精度,同时需要更少的计算时间。利用本文提供的线索,我们的方法可以成功地识别一幅画是属于中国风格还是外国风格。

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