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Floorplan generation from 3D point clouds: A space partitioning approach

机译:从3D点云产生的地板:空间分区方法

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International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)We propose a novel approach to automatically reconstruct the floorplan of indoor environments from raw sensor data. In contrast to existing methods that generate floorplans under the form of a planar graph by detecting corner points and connecting them, our framework employs a strategy that decomposes the space into a polygonal partition and selects edges that belong to wall structures by energy minimization. By relying on a efficient space-partitioning data structure instead of a traditional and delicate corner detection task, our framework offers a high robustness to imperfect data. We demonstrate the potential of our algorithm on both RGBD and LIDAR points scanned from simple to complex scenes. Experimental results indicate that our method is competitive with respect to existing methods in terms of geometric accuracy and output simplicity.
机译:国际摄影测量和遥感学会,Inc。(ISPRS)我们提出了一种新颖的方法,可以从原始传感器数据自动重建室内环境的平面图。 相反,通过检测角点并将它们连接到平面图形式的现有方法,我们的框架采用了一种将空间分解成多边形分区的策略,并通过能量最小化选择属于壁结构的边缘。 通过依赖高效的空间分区数据结构而不是传统和精致的角检测任务,我们的框架提供了高稳健性来不完美的数据。 我们展示了我们在扫描从简单到复杂场景的RGBD和LIDAR点上的算法的潜力。 实验结果表明,在几何准确度和输出简单方面,我们的方法对现有方法具有竞争力。

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