Research on Geometry Kernel for Large-Scale Point-Clouds Captured by Laser Scanners

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Recent mid-range laser scanners can capture large-scale point-clouds of manufacturing facilities and industrial plants. This research project aims to develop a new geometry kernel that can handle very large point-clouds. To achieve this goal, we defined a new framework that can unify point-clouds and their 2D images. This framework allows us to very efficiently process large-scale point-clouds. Then we developed algorithms for various point processing methods, and incorporated them into our geometry kernel. In addition, we evaluated algorithms and the kernel using point-clouds of facilities, such as power plants and automobile assembly factories.