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

Authors

353

  1. US
    Uwe Stilla

    Technical University of Munich, Germany

    5 publications · 194 citations

    5

    h-index

  2. GV
    George Vosselman

    University of Twente, Netherlands

    4 publications · 149 citations

    4

    h-index

  3. BH
    Bernhard Höfle

    Heidelberg University, Germany

    4 publications · 168 citations

    4

    h-index

  4. SO
    Sander Oude Elberink

    University of Twente, Netherlands

    4 publications · 104 citations

    4

    h-index

  5. KA
    Katharina Anders

    Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany

    4 publications · 168 citations

    4

    h-index

1–5 of 353