WindPoly: Polygonal Mesh Reconstruction via Winding Numbers

July 27, 2024 Β· Declared Dead Β· πŸ› European Conference on Computer Vision

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors Xin He, Chenlei Lv, Pengdi Huang, Hui Huang arXiv ID 2407.19208 Category cs.GR: Graphics Citations 3 Venue European Conference on Computer Vision Last Checked 6 months ago
Abstract
Polygonal mesh reconstruction of a raw point cloud is a valuable topic in the field of computer graphics and 3D vision. Especially to 3D architectural models, polygonal mesh provides concise expressions for fundamental geometric structures while effectively reducing data volume. However, there are some limitations of traditional reconstruction methods: normal vector dependency, noisy points and defective parts sensitivity, and internal geometric structure lost, which reduce the practicality in real scene. In this paper, we propose a robust and efficient polygonal mesh reconstruction method to address the issues in architectural point cloud reconstruction task. It is an iterative adaptation process to detect planar shapes from scattered points. The initial structural polygonal mesh can be established in the constructed convex polyhedral space without assistance of normal vectors. Then, we develop an efficient polygon-based winding number strategy to orient polygonal mesh with global consistency. The significant advantage of our method is to provide a structural reconstruction for architectural point clouds and avoid point-based normal vector analysis. It effectively improves the robustness to noisy points and defective parts. More geometric details can be preserved in the reconstructed polygonal mesh. Experimental results show that our method can reconstruct concise, oriented and faithfully polygonal mesh that are better than results of state-of-the-art methods. More results and details can be found on https://vcc.tech/research/2024/WindPoly
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Graphics

R.I.P. πŸ‘» Ghosted

Everybody Dance Now

Caroline Chan, Shiry Ginosar, ... (+2 more)

cs.GR πŸ› ICCV πŸ“š 820 cites 8 years ago
R.I.P. πŸ‘» Ghosted

Animating Human Athletics

Jessica K. Hodgins, Wayne L. Wooten, ... (+2 more)

cs.GR πŸ› SIGGRAPH πŸ“š 765 cites 3 years ago

Died the same way β€” πŸ‘» Ghosted