Robust Normal Estimation and Orientation for Unstructured Point Clouds

大量的点云处理算法，如几何基元的提取，曲面重建，基于点的渲染等的性能都显著地依赖于点云法向估计的质量。高质量的法向估计应给不易受到孤立点，噪声，点云采样分布等的影响。此外，由于存在大量的百万级别的点云数据，提高法向估计算法的速度也是一个重要的研究问题。我们的贡献如下，相关文章截至2019.11累计被引：81次。

p 首次利用子空间结构的稳定性，得到鲁棒的高质量保特征法向估计算法。

p 提出首个点云法向估计的基准和首个定向估计的基准，使得相关算法可以在统一的数据集上展开大规模的定量比较。

p 整合传统鲁棒优化模型于端到端深度网络中，提出截至2019最高质量的法向估计算法。

发表文章情况：

1.       Jie Zhang, Junjie Cao*, Xiuping Liu, Jun Wang, Jian Liu, Xiquan Shi. Point cloud normal estimation via low-rank subspace clustering. Computers & Graphics (SMI 2013), 2013, 37(6): 697-706. (SCI, IF: 1.029) (Cited by 39). (CCF C) (中科院4区)

2.       Xiuping Liu, Jie Zhang, Junjie Cao*, Bo Li, Ligang Liu. Quality Point Cloud Normal Estimation by Guided Least Squares Representation. Computers & Graphics (Special Issue of SMI 2015), 2015, 51, 106-116. (SCI, IF: 1.03) (Cited by 15).  (CFC C).

3.       Junjie Cao, He Chen, Jie Zhang*, Yujiao Li, Xiuping Liu, Changqing Zou. Normal Estimation via Shifted Neighborhood for point cloud. Journal of Computational and Applied Mathematics, 2018, 329, 57-67. (SCI, IF: 1.328) (Cited by 6).  (JCR 2, 数学Top)

4.       Jie~Zhang, Junjie Cao (co-first authors), Xiuping Liu*, He Chen, Bo Li, Ligang Liu. Multi-Normal Estimation via Pair Consistency Voting. IEEE Transactions on Visualization and Computer Graphics, 2019, 25(4), 1693-1706. (CCF A, JCR2, Top) (Cited by 2)

1.       Junjie Cao*, Ying He, Zhiyang Li, Xiuping Liu, Zhixun Su. Orienting Raw Point Sets by Global Contraction and Visibility Voting. Computers & Graphics (SMI 2011), 2011, 35(3): 733-740. (SCI, IF: 0.720) (Cited by 10) (CCF C) (中科院工程技术大类4区；计算机科学小类3区)

2.       Jian Liu, Junjie Cao*, Xiuping Liu, Jun Wang, Xiaochao Wang, Xiquan Shi. Mendable consistent orientation of point clouds. Computer-Aided Design, 2014, 55: 26-36. (SCI, IF: 1.264) (Cited by 9) (CCF B) (中科院工程技术大类3区；计算机科学小类2区)