Suggestive painterly style image generation system to satisfy user preferences

S. Kodama, Tokiichiro Takahashi
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Abstract

In non-photorealistic rendering (NPR), an evaluated value of the rendered image is not absolute. It is different for each user. Therefore, in NPR, it is important to render an image that satisfies user preferences. Many methods of painterly style image generation have been proposed/developed. However, these methods focus on image generation that imitates painting material or a painterly style. Therefore, to the best of our knowledge, the study of how to generate a painterly style image that satisfies user preferences dose not yet exist. When gazing at an image, the user is more effective at quickly identifying regions that the user dislikes than in finding preferred regions. To address this point, we propose a mechanism of painterly style rendering that satisfies user preferences.
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暗示性画风图像生成系统,满足用户偏好
在非真实感渲染(NPR)中,所渲染图像的评估值不是绝对的。对于每个用户来说都是不同的。因此,在NPR中,呈现满足用户偏好的图像非常重要。许多绘画风格的图像生成方法已经提出/发展。然而,这些方法侧重于模仿绘画材料或绘画风格的图像生成。因此,据我们所知,如何生成满足用户偏好的绘画风格图像的研究尚不存在。当用户盯着一张图片看时,比起寻找自己喜欢的区域,用户更能快速识别出自己不喜欢的区域。为了解决这一点,我们提出了一种满足用户偏好的绘画风格渲染机制。
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