Graph-based representations of point clouds

This paper introduces a skeletal representation, called Point Cloud Graph, that generalizes the definition of the Reeb graph to arbitrary point clouds sampled from m-dimensional manifolds embedded in the d-dimensional space. The proposed algorithm is easy to implement and the graph representation yields to an effective abstraction of the data. Finally, we present experimental results on point-sampled surfaces and volumetric data that show the robustness of the Point Cloud Graph to non-uniform point distributions and its usefulness for shape comparison.

► Extension of the Reeb graph to point clouds representing m-manifolds embedded in Rd. ► general framework wrt the quality of data such as noise, occlusions, multiple components. ► suitability of the descriptor for shape comparison of point clouds. ► improvement of the computational cost with respect to the previous work.