PuzzleNet: Boundary-Aware Feature Matching for Non-Overlapping 3D Point Clouds Assembly

We address the 3D shape assembly of multiple geometric pieces without overlaps, a scenario often encountered in 3D shape design, field archeology, and robotics. Existing methods depend on strong assumptions on the number of shape pieces and coherent geometry or semantics of shape pieces. Despite rai...

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Bibliographic Details
Published in:	Journal of computer science and technology Vol. 38; no. 3; pp. 492 - 509
Main Authors:	Liu, Hao-Yu, Guo, Jian-Wei, Jiang, Hai-Yong, Liu, Yan-Chao, Zhang, Xiao-Peng, Yan, Dong-Ming
Format:	Journal Article
Language:	English
Published:	Singapore Springer Nature Singapore 01.06.2023 Springer Springer Nature B.V
Subjects:	Algorithms Archaeology Artificial Intelligence Assembly Automation Computer Science Data Structures and Information Theory Datasets Information Systems Applications (incl.Internet) Iterative methods Manufacturing engineering Neural networks Regular Paper Robotics Semantics Software Engineering Theory of Computation Three dimensional models point cloud shape assembly 3D registration boundary feature geometric learning
ISSN:	1000-9000, 1860-4749
Online Access:	Get full text
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