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Efficient Retrieval of 3D Building Models Using Embeddings of Attributed Subgraphs

机译:使用属性子图的嵌入高效检索3D建筑模型

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We present a novel method for retrieval and classification of 3D building models that is tailored to the specific requirements of architects. In contrast to common approaches our algorithm relies on the interior spatial arrangement of rooms instead of exterior geometric shape. We first represent; the internal topological building structure by a Room Connectivity Graph (RCG). To enable fast and efficient retrieval and classification with RCGs, we transform the structured graph representation into a vector-based one by introducing a new concept of subgraph embeddings. We provide comprehensive experiments showing that the introduced subgraph embeddings yield superior performance compared to state-of-the-art graph retrieval approaches.
机译:我们提出了一种新颖的3D建筑模型检索和分类方法,该方法适合建筑师的特定要求。与常见方法相反,我们的算法依赖于房间的内部空间布置,而不是外部几何形状。我们首先代表;通过房间连通图(RCG)来了解内部拓扑建筑结构。为了使用RCG进行快速有效的检索和分类,我们通过引入子图嵌入的新概念,将结构化图表示转换为基于矢量的图表示。我们提供的综合实验表明,与最新的图形检索方法相比,引入的子图嵌入产生了更高的性能。

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