Consistent Point Orientation for Manifold Surfaces via Boundary Integration

July 03, 2024 ยท Declared Dead ยท ๐Ÿ› International Conference on Computer Graphics and Interactive Techniques

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Authors Weizhou Liu, Xingce Wang, Haichuan Zhao, Xingfei Xue, Zhongke Wu, Xuequan Lu, Ying He arXiv ID 2407.03165 Category cs.CV: Computer Vision Cross-listed cs.GR Citations 12 Venue International Conference on Computer Graphics and Interactive Techniques Repository https://github.com/liuweizhou319/BIM} Last Checked 1 month ago
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}.
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