Point Cloud Change Detection
Point Cloud Change Detection is a computational method that identifies spatial and geometric differences between two or more point cloud datasets of the same scene captured at different times, distinguishing itself from other change detection approaches by operating directly on unstructured 3D point representations to reveal temporal alterations in the underlying environment.
109
Publications
5.8K
Citations
353
Authors
181
Institutions
Publications per year
2017–2026
61
Parents
109
M. R. James, Stuart Robson, Mark W. Smith · Earth Surface Processes and Landforms · 2017 · 490 citations · Full text
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Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
4 publications · 168 citations
4
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1–5 of 353
181

University of Twente
Enschede, The Netherlands
7 h-index
25 publications
755 citations

Centre National de la Recherche Scientifique
Paris, France
6 h-index
12 publications
4K citations
Wuhan University
Wuhan, China
5 h-index
17 publications
632 citations
Arizona State University
Tempe, United States
4 h-index
7 publications
423 citations
Technical University of Munich
Munich, Germany
4 h-index
15 publications
561 citations
Heidelberg University
Heidelberg, Germany
4 h-index
14 publications
574 citations
The Ohio State University
Columbus, United States
3 h-index
10 publications
397 citations
University College London
London, United Kingdom
3 h-index
7 publications
553 citations
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15 publications · 665 citations
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10 publications · 158 citations
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7 publications · 357 citations
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6 publications · 427 citations
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6 publications · 165 citations
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