A Novel Slicing-Based Regularization Method for Raw Point Clouds in Visible IoT

Three-dimensional scanning technology is becoming increasingly popular in the Internet of Things and cyber-physical social systems. Existing reconstruction algorithms and shape extraction algorithms usually require regularized points and clear topological relationships between them. In this paper, a novel slicing-based method is proposed to regularize raw point clouds, in which we first slice the raw point to get cross section points, and then generate regular point clouds under the topology control of cross section shapes, and finally produce regular point clouds at multiple levels of detail. The proposed method is effective specifically for huge raw point clouds and the experiment results show that the proposed method can produce regularized point clouds for surface meshing, shapes analysis, shapes extraction, and so on.