Cartoons are an important part of our entertainment culture. Though drawing a cartoon is not for everyone, creating it using an arrangement of basic geometric primitives that approximates that character is a fairly frequent technique in art. The key motivation behind this technique is that human bodies - as well as cartoon figures - can be split down into various basic geometric primitives. Numerous tutorials are available that demonstrate how to draw figures using an appropriate arrangement of fundamental shapes, thus assisting us in creating cartoon characters. This technique is very beneficial for children in terms of teaching them how to draw cartoons. In this paper, we develop a tool - shape2toon - that aims to automate this approach by utilizing a generative adversarial network which combines geometric primitives (i.e. circles) and generate a cartoon figure (i.e. Mickey Mouse) depending on the given approximation. For this purpose, we created a dataset of geometrically represented cartoon characters. We apply an image-to-image translation technique on our dataset and report the results in this paper. The experimental results show that our system can generate cartoon characters from input layout of geometric shapes. In addition, we demonstrate a web-based tool as a practical implication of our work.
翻译:漫画是我们娱乐文化的一个重要部分。 虽然绘画漫画不是每个人的娱乐文化。 虽然绘画漫画不是对每个人都有好处, 但是它使用基本几何原始的组合来创建它, 并使用一种基本几何原始, 其特征是艺术中相当常见的技巧。 这个技术的关键动机是: 人体和漫画数字可以分为各种基本的几何原始。 许多教义可以展示如何使用基本形状的适当安排来绘制图表, 从而帮助我们创建卡通人物。 这个技术在教孩子们如何绘制漫画方面非常有用。 在本文中, 我们开发了一种工具 - 形状2to -, 其目的是通过使用一个基因对抗网络来将这个方法自动化。 这个网络将几何原始( 即圆) 组合起来, 并产生一个根据给定的近似的卡通数字( 米奇鼠) 。 为此, 我们创建了一个以几何为代表的漫画字符数据集。 我们在我们的数据集中应用了一种图像和图像翻译技术, 并报告本文中的结果。 实验结果显示我们的系统能够从实际形状的输入布局中生成卡通字符字符。 此外, 我们展示了一个网络工具。