A simple provable algorithm for curve reconstruction
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
A simple algorithm for homeomorphic surface reconstruction
Proceedings of the sixteenth annual symposium on Computational geometry
Feature sensitive surface extraction from volume data
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Shape dimension and approximation from samples
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Proceedings of the conference on Visualization '01
IEEE Transactions on Visualization and Computer Graphics
Robust moving least-squares fitting with sharp features
ACM SIGGRAPH 2005 Papers
Voronoi-based variational reconstruction of unoriented point sets
SGP '07 Proceedings of the fifth Eurographics symposium on Geometry processing
Data-dependent MLS for faithful surface approximation
SGP '07 Proceedings of the fifth Eurographics symposium on Geometry processing
Sharp Feature Detection in Point Clouds
SMI '10 Proceedings of the 2010 Shape Modeling International Conference
ℓ1-Sparse reconstruction of sharp point set surfaces
ACM Transactions on Graphics (TOG)
Non-manifold surface reconstruction from high-dimensional point cloud data
Computational Geometry: Theory and Applications
Feature-Preserving Reconstruction of Singular Surfaces
Computer Graphics Forum
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The detection and reconstruction of feature curves in surfaces from a point cloud data is a challenging problem because most of the known theories for smooth surfaces break down at these places. The features such as boundaries, sharp ridges and corners, and curves where multiple surface patches intersect creating non-manifold points are often considered important geometries for further processing. As a result, they need to be preserved in a reconstruction of the sampled surface from its point sample. The problem becomes harder in the presence of noise. We propose a robust Voronoi-based pipeline that engages several substeps consisting of approaches proposed originally for smooth case. We modify or enhance them to handle features in singular surfaces. The experimental results provide the evidence that the method is effective.