The growing demand for building information modeling (BIM) data and ubiquitous applications make it increasingly necessary to establish a reliable way to share the models on lightweight devices. Building scenes have strong occlusion features and the building exterior plays an important role in digital devices with limited computational resources. This allows the possibility to reduce the resource consumption while roaming in outdoor scenes by culling away the interior building data. This article addresses the task of automatic annotation of BIM building exterior via voxel index analysis. We showcase the research of using industry foundation classes (IFC) and other mainstream formats as our input data and proposed an automatic algorithm for annotating the building exterior. Afterward, a practical and accurate voxel index analysis procedure is designed for frequently flawed models. The annotation can be added directly into the original data file under the same IFC standard, avoiding the complex procedure and information loss in semantics mapping between different standards. The final examinations show the robustness of our algorithm and the capability of handling large BIM building models.

中文翻译：

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ExteriorTag：通过体素指数分析自动对BIM建筑外观进行语义标注

对建筑信息模型 (BIM) 数据和无处不在的应用程序不断增长的需求使得建立一种在轻量级设备上共享模型的可靠方式变得越来越必要。建筑场景具有很强的遮挡特征，建筑外观在计算资源有限的数字设备中起着重要作用。这允许通过剔除室内建筑数据来减少在室外场景中漫游时的资源消耗。本文解决了通过体素指数分析自动标注 BIM 建筑外观的任务。我们展示了使用行业基础类（IFC）和其他主流格式作为我们的输入数据的研究，并提出了一种用于注释建筑物外观的自动算法。之后，为经常有缺陷的模型设计了实用且准确的体素指数分析程序。在同一IFC标准下，标注可以直接添加到原始数据文件中，避免了不同标准之间语义映射的复杂程序和信息丢失。期末考试显示了我们算法的稳健性和处理大型 BIM 建筑模型的能力。