Reconstruction and Preservation of Feature Curves in 3D Point Cloud Processing

Given a 3D point cloud, we propose a method for suitably resampling the cloud while reconstructing and preserving the feature curves to which some points are identified to belong. The first phase of our strategy enriches the cloud by approximating the curvilinear profiles outlined by the feature points with piece-wise polynomial parametric space curves through the use of the Hough transform. The second phase describes how the removal of a point or its insertion can be performed without affecting the approximated profiles and preserving the enriched structure of the cloud. The combination of the two steps provides multiple possibilities for processing a point cloud by varying its size or improving its density homogeneity without affecting the retrieved feature curves. The various capabilities of our approach are investigated to produce simplification, refinement, and resampling techniques whose effectiveness is evaluated through experiments and comparisons.

Automated summary

This paper proposes a method for suitably resampling a 3D point cloud while preserving the feature curves to which some points belong. The method enriches the cloud by approximating curvilinear profiles and allows for point removal or insertion without affecting the approximated profiles. The effectiveness of the method is evaluated through experiments and comparisons.