FeatureLego : Volume Exploration Using Exhaustive Clustering of Super-Voxels
We present a volume exploration framework, FeatureLego, that uses a novel voxel clustering approach for efficient selection of semantic features. We partition the input volume into a set of compact super-voxels that represent the finest selection granularity. We then perform an exhaustive clustering...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - 25(2019), 9 vom: 18. Sept., Seite 2725-2737
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| 1. Verfasser: |
Jadhav, Shreeraj
(VerfasserIn) |
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| Weitere Verfasser: |
Nadeem, Saad,
Kaufman, Arie |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2019
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics
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| Schlagworte: | Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S. |
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