Graph-based generative representation learning of semantically and behaviorally augmented floorplans
Graph-based generative representation learning of semantically and behaviorally augmented floorplans
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DOI：
10.1007/s00371-021-02155-w
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发表时间：
2020-12
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通讯作者：
Vahid Azizi;Muhammad Usman;H. Zhou;P. Faloutsos;M. Kapadia
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文献类型：
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作者：
Vahid Azizi;Muhammad Usman;H. Zhou;P. Faloutsos;M. Kapadia
平面图通常用来表示建筑物的布局。研究人员致力于促进设计过程的计算技术，例如自动分析和优化，通常使用简单的平面图表示，忽略空间的语义，不考虑与使用相关的分析。我们提出了一种平面图嵌入技术，该技术使用属性图来建模平面图的几何信息、设计语义和行为特征作为节点和边缘属性。提出并训练了一种长短期记忆（LSTM）变分自编码器（VAE）架构，用于将属性图作为向量嵌入到连续空间中。进行用户研究，以评估从给定输入（例如，设计布局）的嵌入空间中检索的类似平面图的耦合。定性、定量和用户研究评估表明，我们的嵌入框架为平面图产生了有意义和准确的矢量表示。此外，我们提出的模型是生成的。我们研究并展示了它在生成新平面图方面的有效性。我们还发布了我们构建的数据集。我们将每个平面图的设计语义属性和模拟生成的人类行为特征包含在数据集中，以供社区进一步研究。
Floorplans are commonly used to represent the layout of buildings. Research works toward computational techniques that facilitate the design process, such as automated analysis and optimization, often using simple floorplan representations that ignore the space’s semantics and do not consider usage-related analytics. We present a floorplan embedding technique that uses an attributed graph to model the floorplans’ geometric information, design semantics, and behavioral features as the node and edge attributes. A long short-term memory (LSTM) variational autoencoder (VAE) architecture is proposed and trained to embed attributed graphs as vectors in a continuous space. A user study is conducted to evaluate the coupling of similar floorplans retrieved from the embedding space for a given input (e.g., design layout). The qualitative, quantitative, and user study evaluations show that our embedding framework produces meaningful and accurate vector representations for floorplans. Besides, our proposed model is generative. We studied and showcased its effectiveness for generating new floorplans. We also release the dataset that we have constructed. We include the design semantic attributes and simulation-generated human behavioral features for each floorplan in the dataset for further study in the community.