Structure-Aware Surface Reconstruction via Primitive Assembly

被引:0
|
作者
Jiang, Jingen [1 ,2 ,3 ,4 ]
Zhao, Mingyang [1 ,5 ]
Xin, Shiqing [4 ]
Yang, Yanchao [6 ]
Wang, Hanxiao [1 ,3 ]
Jia, Xiaohong [2 ,3 ]
Yan, Dong-Ming [1 ,3 ]
机构
[1] CASIA, MAIS & NLPR, Beijing, Peoples R China
[2] Chinese Acad Sci, KLMM, AMSS, Beijing, Peoples R China
[3] UCAS, Beijing, Peoples R China
[4] Shandong Univ, Jinan, Peoples R China
[5] BAAI, Beijing, Peoples R China
[6] Univ Hong Kong, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
SHAPE; SEGMENTATION; SET;
D O I
10.1109/ICCV51070.2023.01303
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We propose a novel and efficient method for reconstructing manifold surfaces from point clouds. Unlike previous approaches that use dense implicit reconstructions or piecewise approximations and overlook inherent structures like quadrics in CAD models, our method faithfully preserves these quadric structures by assembling primitives. To achieve high-quality primitive extraction, we use a variational shape approximation, followed by a mesh arrangement for space partitioning and candidate primitive patches generation. We then introduce an effective pruning mechanism to classify candidate primitive patches as active or inactive, and further prune inactive patches to reduce the search space and speed up surface extraction significantly. Finally, the optimal active patches are computed by a binary linear programming and assembled as manifold and watertight surfaces. We perform extensive experiments on a wide range of CAD objects to validate its effectiveness.
引用
收藏
页码:14125 / 14134
页数:10
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