English

Consistent Point Orientation for Manifold Surfaces via Boundary Integration

Computer Vision and Pattern Recognition 2024-07-04 v1 Graphics

Abstract

This paper introduces a new approach for generating globally consistent normals for point clouds sampled from manifold surfaces. Given that the generalized winding number (GWN) field generated by a point cloud with globally consistent normals is a solution to a PDE with jump boundary conditions and possesses harmonic properties, and the Dirichlet energy of the GWN field can be defined as an integral over the boundary surface, we formulate a boundary energy derived from the Dirichlet energy of the GWN. Taking as input a point cloud with randomly oriented normals, we optimize this energy to restore the global harmonicity of the GWN field, thereby recovering the globally consistent normals. Experiments show that our method outperforms state-of-the-art approaches, exhibiting enhanced robustness to noise, outliers, complex topologies, and thin structures. Our code can be found at \url{https://github.com/liuweizhou319/BIM}.

Cite

@article{arxiv.2407.03165,
  title  = {Consistent Point Orientation for Manifold Surfaces via Boundary Integration},
  author = {Weizhou Liu and Xingce Wang and Haichuan Zhao and Xingfei Xue and Zhongke Wu and Xuequan Lu and Ying He},
  journal= {arXiv preprint arXiv:2407.03165},
  year   = {2024}
}

Comments

accepted in siggraph2024

R2 v1 2026-06-28T17:28:01.554Z