Hierarchical Spatial Decomposition
Hierarchical Spatial Decomposition is a hierarchical data organization method that partitions three-dimensional space into successively finer levels of spatial resolution through recursive subdivision, enabling efficient representation and selective refinement of volumetric data.
131
Publications
8.6K
Citations
361
Authors
179
Institutions
Publications per year
2017–2026
17
131
Real-time compression of point cloud streams
Julius Kammerl, Nico Blodow, Radu Bogdan Rusu et al. · 2012 · 338 citations
1–5 of 131
361
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University of Illinois Urbana-Champaign, United States
3 publications · 47 citations
3
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3
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3
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2
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1–5 of 361
179
Princeton University
Princeton, United States
6 h-index
12 publications
2K citations
University of Maryland, College Park
College Park, United States
6 h-index
10 publications
302 citations
University of Illinois Urbana-Champaign
Urbana, United States
5 h-index
13 publications
293 citations

Tel Aviv University
Tel Aviv, Israel
4 h-index
5 publications
297 citations
Stanford University
Stanford, United States
4 h-index
7 publications
292 citations

University of Toronto
Toronto, Canada
4 h-index
7 publications
380 citations

Weizmann Institute of Science
Rehovot, Israel
3 h-index
12 publications
1.2K citations
Massachusetts Institute of Technology
Cambridge, United States
3 h-index
4 publications
144 citations
1–8 of 179
3 publications · 99 citations
3
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3 publications · 45 citations
3
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3 publications · 425 citations
3
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3 publications · 180 citations
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2 publications · 163 citations
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