Point Cloud Mapping
Point Cloud Mapping is a methodological framework that establishes correspondences between raw 3D point cloud data and semantic or spatial representations by aligning unstructured geometric observations into structured, interpretable models for downstream analysis and visualization.
186
Publications
10.8K
Citations
707
Authors
246
Institutions
Publications per year
2017–2026
137
Parents
186
Towards 3D Point cloud based object maps for household environments
Radu Bogdan Rusu, Zoltán-Csaba Márton, Nico Blodow et al. · Robotics and Autonomous Systems · 2008 · 1.1K citations
Model globally, match locally: Efficient and robust 3D object recognition
Bertram Drost, Markus Ulrich, Nassir Navab et al. · 2010 · 982 citations
Kintinuous: Spatially Extended KinectFusion
Thomas J. Whelan, Michael Kaess, Maurice Fallon et al. · DSpace@MIT (Massachusetts Institute of Technology) · 2012 · 544 citations · Full text
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246
Wuhan University
Wuhan, China
7 h-index
21 publications
432 citations
Technical University of Munich
Munich, Germany
6 h-index
22 publications
8.8K citations
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
Wuhan, China
5 h-index
13 publications
269 citations
The University of Tokyo
Tokyo, Japan
5 h-index
10 publications
175 citations

Centre National de la Recherche Scientifique
Paris, France
4 h-index
14 publications
353 citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
4 h-index
11 publications
884 citations
Georgia Institute of Technology
Atlanta, United States
4 h-index
11 publications
433 citations
University of Southern California
Los Angeles, United States
4 h-index
10 publications
589 citations
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11 publications · 453 citations
11
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10 publications · 195 citations
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9 publications · 265 citations
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8 publications · 263 citations
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6 publications · 541 citations
7
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