HRsR: Hierarchical Rotation System Reconstruction

2026-06-05

AI Summary

Surface reconstruction from point clouds often struggles to balance geometric fidelity with topological control while suffering from poor computational scalability. This work proposes a hierarchical reconstruction framework that first simplifies the input point cloud via edge collapse on a k-nearest neighbor graph, then efficiently reconstructs a mesh on this simplified structure while enforcing topological consistency through an intersection-handling mechanism. Finally, geometric details are recovered using a quality-driven vertex splitting strategy. Compared to the original RsR method, the proposed approach achieves comparable reconstruction quality while delivering up to a 6× speedup and reducing memory consumption by more than 8×, thereby significantly enhancing both efficiency and scalability.

Abstract

Surface reconstruction from point clouds remains challenging when both geometric fidelity and topology control are required. Rotation System Reconstruction (RsR) reconstructs triangle meshes from point clouds while explicitly controlling topology through the Euler characteristic, but its sequential edge insertion limits scalability. We present Hierarchical Rotation System Reconstruction (HRsR), which accelerates RsR through a hierarchical pipeline of edge collapses and vertex splits. HRsR first simplifies the input using a $k$-nearest neighbor graph, performs reconstruction on the reduced structure, and then restores geometric detail while preserving topology. To maintain geometric consistency, we incorporate intersection handling and quality-driven vertex split selection. Experiments demonstrate up to a $6\times$ speedup and more than $8\times$ reduction in memory usage over RsR, while achieving comparable reconstruction results.

Problem

• surface reconstruction
• point clouds
• topology control
• geometric fidelity
• scalability

Innovation

• Hierarchical Reconstruction
• Rotation System
• Topology Control
• Point Cloud
• Mesh Simplification