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Photo rendering with swarms: From figurative to abstract pherogenic imaging

机译:成群的照片渲染:从具象性到抽象的信息生成成像

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This paper describes the use of ant colony models for photographic rendering, that is, for the depiction or interpretation of photographic images. A description of a previously proposed ant-based edge detection method called pherographia is given in order to contextualize this paper's proposal. Then, the application of the KANTS algorithm to photo-rendering is introduced. KANTS is ant-based clustering algorithm described by a set of equations that model the local behavior of simple units (ants). These units represent data samples. When moving on a heterogeneous 2-dimensional lattice of vectors, global behavior emerges from the local interaction between the ants, which self-organize into clusters. In this paper, a data set consists of the RGB values of a digital (or digitalized) photograph. Two different approaches for the initialization of the environment are tested, each one resulting in radically different output images: when the environment is initialized with the RGB values of the same image that is used to generate the data set, the final result is very similar to the original photo; a random initialization of the environment leads to an abstract interpretation of the photo. The results are contextualized within previous swarm artworks by the authors.
机译:本文介绍了将蚁群模型用于摄影渲染,即用于摄影图像的描绘或解释。为了介绍本文的建议,对先前提出的基于蚂蚁的边缘检测方法pherographia进行了描述。然后,介绍了KANTS算法在光渲染中的应用。 KANTS是基于蚂蚁的聚类算法,由一组方程式描述,这些方程式对简单单元(蚂蚁)的局部行为进行建模。这些单位代表数据样本。当在矢量的异构二维晶格上移动时,全局行为会从蚂蚁之间的局部相互作用中显现出来,这些蚂蚁会自组织成簇。在本文中,数据集由数码(或数字化)照片的RGB值组成。测试了两种不同的初始化环境的方法,每种方法都产生了完全不同的输出图像:当使用用于生成数据集的同一图像的RGB值初始化环境时,最终结果与原始照片;环境的随机初始化导致对照片的抽象解释。作者将这些结果与先前的大量作品相结合。

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