Efficient registration of multi-view point sets by K-means clustering

DOI10.1016/J.INS.2019.03.024zbMath1451.68293arXiv1710.05193OpenAlexW2766534319WikidataQ128224126 ScholiaQ128224126MaRDI QIDQ2215151

Zutao Jiang, Georgios Evangelidis, Changqing Zhang, Zhongyu Li, Jihua Zhu, Shanmin Pang

Publication date: 10 December 2020

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1710.05193

zbMATH Keywords

iterative closest pointpoint setsK-means clusteringmulti-view registration

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Machine vision and scene understanding (68T45)

Related Items (2)

Low-rank local tangent space embedding for subspace clustering ⋮ Simultaneous learning coefficient matrix and affinity graph for multiple kernel clustering

Uses Software

• Go-ICP
• BundleFusion
• PRMLT

Cites Work

• Unnamed Item
• Accurate integration of multi-view range images using \(k\)-means clustering
• On Averaging Multiview Relations for 3D Scan Registration
• Fast Descriptors and Correspondence Propagation for Robust Global Point Cloud Registration

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