Abstract During an emergency inside large buildings such as hospitals and shopping malls, the availability of up-to-date information is critical. One common source of information is the 2D layout of buildings and emergency exits. For most buildings, this information is represented as tangled floor plans, which in most cases are outdated. One solution to update the data of buildings after each renovation is to recreate 3D models of buildings in a quick and automatic approach. These 3D models provide proactively crucial building information in a digital format for first responders to be used in emergency cases. Thanks to advances in remote sensing, laser scanners can be used to generate an accurate spatial representation of buildings quickly. However, such devices provide point clouds, which are unstructured data. In this paper, we introduce a complete workflow that allows to generate 3D models from point clouds of buildings and extract fine-grained indoor navigation networks from those models, to support advanced path planning for disaster management and navigation of different types of agents. The process extracts structural elements of buildings such as walls, slabs, ceiling and openings, and reconstruct their volumetric shapes. Additionally, the furnishing elements in the input point clouds are identified and reconstructed as the obstacles. Stairs are also reconstructed to allow multistory navigation path planning. Our algorithm is fully 3D and can handle vertical and slanted structures. We test it on several real datasets, compared it to the state-of-the-art approaches and provide a process to check the consistency of the reconstruction, which allows in return to further improve its result.

中文翻译：

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从点云进行室内 3D 重建，以优化复杂建筑中的路由，以支持灾难管理

摘要 在医院和购物中心等大型建筑物内发生紧急情况时，获取最新信息至关重要。一种常见的信息来源是建筑物和紧急出口的二维布局。对于大多数建筑物，此信息表示为错综复杂的平面图，在大多数情况下已过时。在每次翻新后更新建筑物数据的一种解决方案是以快速和自动的方法重新创建建筑物的 3D 模型。这些 3D 模型以数字格式主动提供重要的建筑信息，供急救人员在紧急情况下使用。由于遥感技术的进步，激光扫描仪可用于快速生成建筑物的准确空间表示。但是，此类设备提供点云，即非结构化数据。在本文中，我们引入了一个完整的工作流程，允许从建筑物的点云生成 3D 模型并从这些模型中提取细粒度的室内导航网络，以支持不同类型代理的灾害管理和导航的高级路径规划。该过程提取建筑物的结构元素，如墙壁、楼板、天花板和开口，并重建它们的体积形状。此外，输入点云中的装饰元素被识别并重建为障碍物。楼梯也被重建以允许多层导航路径规划。我们的算法是完全 3D 的，可以处理垂直和倾斜的结构。我们在几个真实的数据集上对其进行了测试，将其与最先进的方法进行了比较，并提供了一个过程来检查重建的一致性，