ML Anthology

Geometry and Learning Co-Supported Normal Estimation for Unstructured Point Cloud

Haoran Zhou, Honghua Chen, Yidan Feng, Qiong Wang, Jing Qin, Haoran Xie, Fu Lee Wang, Mingqiang Wei, Jun Wang
CVPR 2020
doi:10.1109/CVPR42600.2020.01325 /cvpr/2020/zhou2020cvpr-geometry/

Abstract

In this paper, we propose a normal estimation method for unstructured point cloud. We observe that geometric estimators commonly focus more on feature preservation but are hard to tune parameters and sensitive to noise, while learning-based approaches pursue an overall normal estimation accuracy but cannot well handle challenging regions such as surface edges. This paper presents a novel normal estimation method, under the co-support of geometric estimator and deep learning. To lowering the learning difficulty, we first propose to compute a suboptimal initial normal at each point by searching for a best fitting patch. Based on the computed normal field, we design a normal-based height map network (NH-Net) to fine-tune the suboptimal normals. Qualitative and quantitative evaluations demonstrate the clear improvements of our results over both traditional methods and learning-based methods, in terms of estimation accuracy and feature recovery.

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Cite

Text

Zhou et al. "Geometry and Learning Co-Supported Normal Estimation for Unstructured Point Cloud." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020. doi:10.1109/CVPR42600.2020.01325

Markdown

[Zhou et al. "Geometry and Learning Co-Supported Normal Estimation for Unstructured Point Cloud." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020.](https://mlanthology.org/cvpr/2020/zhou2020cvpr-geometry/) doi:10.1109/CVPR42600.2020.01325

BibTeX

@inproceedings{zhou2020cvpr-geometry,
  title     = {{Geometry and Learning Co-Supported Normal Estimation for Unstructured Point Cloud}},
  author    = {Zhou, Haoran and Chen, Honghua and Feng, Yidan and Wang, Qiong and Qin, Jing and Xie, Haoran and Wang, Fu Lee and Wei, Mingqiang and Wang, Jun},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2020},
  doi       = {10.1109/CVPR42600.2020.01325},
  url       = {https://mlanthology.org/cvpr/2020/zhou2020cvpr-geometry/}
}