Automatically modeling piecewise planar furniture shapes from unorganized point cloud
文献类型：会议论文
| 作者 | Zhao, Junhao; Zong, Chen; Cao, Luming; Chen, Shuangmin; Liu, Guozhu; Xu, Jian; Xin, Shiqing |
| 出版日期 | 2020 |
| 会议日期 | JUN 02-04, 2020 |
| 关键词 | SURFACE RECONSTRUCTION SEGMENTATION OBJECTS MAPS |
| 卷号 | 90 |
| DOI | 10.1016/j.cag.2020.05.019 |
| 英文摘要 | Piecewise planar 3D objects are very common in digital furniture manufacturing. In this paper, we propose a novel method for automatic reconstruction of 3D objects with planar facets from unorganized point clouds. We formulate this problem into a point clustering problem where the key difficulty lies in consolidating co-planar points into a cluster. In order to achieve this purpose, the first step is to triangulate the input point cloud into a mesh (may have over connectivity) that is a super-set of the underlying manifold mesh surface. Then the hundreds of thousands of normal vectors of triangles, after being mapped onto a Gauss sphere, are capable of reporting reliable facing directions of the faces of the final 3D model. After grouping the points based on co-planarity, we fit each cluster with a planar facet and then assemble them into a piecewise planarization representation of the whole model. We further introduce an additional regularization term to meet the orthogonality requirement on a particular occasion, and then transform this problem into a purely convex optimization problem. Our method is efficient and requires just a few parameters. Extensive experimental results show that it is able to handle point clouds with various levels of noise and yield a desirable piecewise planar 3D model with a clean and compact representation. (C) 2020 Elsevier Ltd. All rights reserved. |
| 学科主题 | Computer Science |
| ISSN号 | 0097-8493 |
| 源URL | [http://ir.nimte.ac.cn/handle/174433/23294]  |
| 专题 | 会议专题 会议专题_会议论文 |
| 推荐引用方式 GB/T 7714 | Zhao, Junhao,Zong, Chen,Cao, Luming,et al. Automatically modeling piecewise planar furniture shapes from unorganized point cloud[C]. 见:. JUN 02-04, 2020. |
入库方式： OAI收割
来源：宁波材料技术与工程研究所
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