Point Cloud Skeletons via Laplacian Based Contraction

By Junjie Cao, Andrea Tagliasacchi, Matt Olson, Hao Zhang, Zhixun Su. Shape Modeling International Conference, 2010

342 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

3D Skeletons: A State‐of‐the‐Art Report (2016, methodology): “While centeredness and smoothness of the produced ACS is suboptimal as compared to other ACS methods discussed in this section, this approach is widely used in post-processing to convert contracted geometry into curve networks [WL08,ATC ∗ 08, CTO ∗ 10, TAOZ12].”
P2P-NET: Bidirectional Point Displacement Net for Shape Transform (methodology): “By taking the surface samples as input, meso-skeletons of the shapes are obtained us-ing a contraction-based approach [Cao et al. 2010].”
1 An End-to-End Framework for Evaluating Surface Reconstruction (2011, methodology): “Our benchmark should also prove to be useful for recent methods which resample point clouds with large missing data [Tagliasacchi et al. 2009; Cao et al. 2010; Shalom et al. 2010].”
State of research in automatic as-built modelling (2015, background): “Another distinctive feature commonly used in pipe modelling is the geometric skeleton [12,29,131].”