Visual elements in an information presentation are often spatially and semantically grouped hierarchically for effective message delivery. Studying the hierarchical grouping information can help researchers and designers better explore layout structures and understand design demographics. However, recovering hierarchical grouping is challenging due to a large number of possibilities for compositing visual elements into a single-page design. This paper introduces an automatic approach that takes the layout of visual elements as input and returns the hierarchical grouping as output. To understand information presentations, we first contribute a dataset of 23,072 information presentations with diverse layouts to the community. Next, we propose our technique with a Transformer-based model to predict relatedness between visual elements and a bottom-up algorithm to produce the hierarchical grouping. Finally, we evaluate our technique through a technical experiment and a user study with thirty designers. Results show that the proposed technique is promising.
翻译:信息演示中的视觉元素往往在空间和语义上按等级分组,以便有效地传递信息。研究等级分组信息可以帮助研究人员和设计者更好地探索布局结构并理解设计人口结构。然而,由于将视觉元素合成成单页设计的可能性很大,正在恢复的等级分组具有挑战性。本文引入了一种自动方法,将视觉元素的布局作为输入,并将等级分组返回为输出。为了理解信息演示,我们首先为社区提供了23 072个具有不同布局的信息演示数据集。接下来,我们提出我们用基于变换器的模型来预测视觉元素与生成等级组合的自下而上算法之间的关联性的技术。最后,我们通过技术实验和与30名设计师的用户研究来评估我们的技术。结果显示,拟议的技术很有希望。