Computational approaches are beginning to be used to design dynamic visual identities fuelled by data and generative processes. In this work, we explore these computational approaches in order to generate a visual identity that creates bespoke letterings and images. We achieve this developing a generative design system that automatically assembles black and white visual modules. This system generates designs performing two main methods: (i) Assisted generation; and (ii) Automatic generation. Assisted generation method produces outputs wherein the placement of modules is determined by a configuration file previous defined. On the other hand, the Automatic generation method produces outputs wherein the modules are assembled to depict an input image. This system speeds up the process of design and deployment of one visual identity design as well as it generates outputs visual coherent among them. In this paper, we compressively describe this system and its achievements.
翻译:计算方法开始用于设计由数据和基因化过程所推动的动态视觉身份。 在这项工作中,我们探索这些计算方法,以便产生一种可视特征,产生专用字母和图像。我们实现这个开发一个可自动组合黑白视觉模块的基因化设计系统。这个系统产生设计,采用两种主要方法:(一) 辅助生成;和(二) 自动生成。辅助生成方法产生输出,使模块的位置由先前定义的配置文件决定。另一方面,自动生成方法产生输出,将模块组合成一个输入图像。这个系统加速了一个视觉身份设计的设计和应用过程,并产生了它们之间视觉一致性的产出。在这个文件中,我们压缩地描述这个系统及其成就。