Non-Watertight Polygonal Surface Reconstruction From Building Point Cloud via Connection and Data Fit

Polygonal planes are used to simplify the modeling of the building point cloud, which is widely applied for city planning, 3-D cadastral management, and model rendering. Much of the current research mainly focuses on watertight polygon model reconstruction from the 3-D model data with few missing values, which is highly hypothetical and restricted in application. Therefore, this letter proposes a non-watertight PolyFit (NW-PolyFit) algorithm based on the fit degree of connection and data fitting to reconstruct a non-watertight polygon model from the data with missing values. First, to refine the planar structure in buildings, the refined supporting planes are generated from the detected point cloud primitives. Second, to retain the sharp features, the
$\delta $
expansion planes are generated from their corresponding supporting planes. We get the relationship between primitives by intersecting those
$\delta $
expansion planes. Finally, to eliminate the influence of missing data, a fit-and-remove strategy is proposed to filter the generated candidate’s faces, which achieves non-watertight modeling. Experiments show that the NW-PolyFit achieved similar modeling effects for completed data compared with the state-of-the-art methods. The NW-PolyFit achieves non-watertight modeling from the point cloud data with massive missing values while other methods do not.