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The light detection and ranging (LiDAR) technology plays an important role in obtaining the three-dimensional information. A large number of point cloud data of the objects can be obtained through the LiDAR technology. The Iterative Closest Point (ICP) algorithm was widely used for registering the point cloud data, which typically only scan an object from one direction at a time. However, massive...
Building digitalization is an important component of digital city development. Terrestrial laser scanning (TLS) technology provides a high-precision and high-density data source to guarantee building digitalization and reconstruction. However, when these large scattered points cloud are used to build a 3D digital model, the points of building boundaries extraction is an essential issue. In this paper,...
The efficiency and accuracy loss are the key issues for the point cloud simplification. In this paper, a feature preserving algorithm is proposed for point cloud simplification based on hierarchical clustering with the surface feature description. The surface variation is presented as the main criterion for the efficient hierarchical clustering method to simplify the mass and dense point cloud fast,...
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