Consistent Point Orientation for Manifold Surfaces via Boundary Integration
Fuente:
arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
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| _version_ | 1866909241033359360 |
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| author | Liu, Weizhou Wang, Xingce Zhao, Haichuan Xue, Xingfei Wu, Zhongke Lu, Xuequan He, Ying |
| author_facet | Liu, Weizhou Wang, Xingce Zhao, Haichuan Xue, Xingfei Wu, Zhongke Lu, Xuequan He, Ying |
| contents | 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}. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_03165 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Consistent Point Orientation for Manifold Surfaces via Boundary Integration Liu, Weizhou Wang, Xingce Zhao, Haichuan Xue, Xingfei Wu, Zhongke Lu, Xuequan He, Ying Computer Vision and Pattern Recognition Graphics 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}. |
| title | Consistent Point Orientation for Manifold Surfaces via Boundary Integration |
| topic | Computer Vision and Pattern Recognition Graphics |
| url | https://arxiv.org/abs/2407.03165 |