Point Cloud Alignment
Point Cloud Alignment is a computational method that establishes spatial correspondence between two or more point clouds by estimating the optimal geometric transformation that minimizes the distance between overlapping regions, distinguishing it from other point cloud processing tasks through its focus on relative pose estimation and registration.
405
Publications
24.9K
Citations
1.3K
Authors
409
Institutions
Publications per year
2017–2026
251
Parents
405
Aligning point cloud views using persistent feature histograms
Radu Bogdan Rusu, Nico Blodow, Zoltán-Csaba Márton et al. · 2008 · 1K citations
PointNetLK: Robust & Efficient Point Cloud Registration Using PointNet
Yasuhiro Aoki, Hunter Goforth, Rangaprasad Arun Srivatsan et al. · 2019 · 856 citations
The Trimmed Iterative Closest Point algorithm
Dmitry Chetverikov, D. Svirko, Dmitry Stepanov et al. · 2003 · 622 citations
1–5 of 405
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409
Wuhan University
Wuhan, China
15 h-index
64 publications
2.3K citations
Tsinghua University
Beijing, China
13 h-index
24 publications
1.8K citations

Chinese Academy of Sciences
Beijing, China
11 h-index
23 publications
876 citations
University of Technology Sydney
Sydney, Australia
10 h-index
23 publications
1.9K citations
Technical University of Munich
Munich, Germany
10 h-index
25 publications
5.7K citations

Xi'an Jiaotong University
Xi'an, China
8 h-index
39 publications
1.2K citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
8 h-index
16 publications
668 citations
ETH Zurich
Zurich, Switzerland
8 h-index
16 publications
1.4K citations
1–8 of 409
21 publications · 1.6K citations
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Repository · 18 publications · 781 citations
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14 publications · 319 citations
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13 publications · 508 citations
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TPAMI · 10 publications · 653 citations
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