Efficient structure-aware selection techniques for 3D point cloud visualizations with 2DOF input

Lingyun Yu*, Konstantinos Efstathiou, Petra Isenberg, Tobias Isenberg

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

63 Citations (Scopus)

Abstract

Data selection is a fundamental task in visualization because it serves as a pre-requisite to many follow-up interactions. Efficient spatial selection in 3D point cloud datasets consisting of thousands or millions of particles can be particularly challenging. We present two new techniques, TeddySelection and CloudLasso, that support the selection of subsets in large particle 3D datasets in an interactive and visually intuitive manner. Specifically, we describe how to spatially select a subset of a 3D particle cloud by simply encircling the target particles on screen using either the mouse or direct-touch input. Based on the drawn lasso, our techniques automatically determine a bounding selection surface around the encircled particles based on their density. This kind of selection technique can be applied to particle datasets in several application domains. TeddySelection and CloudLasso reduce, and in some cases even eliminate, the need for complex multi-step selection processes involving Boolean operations. This was confirmed in a formal, controlled user study in which we compared the more flexible CloudLasso technique to the standard cylinder-based selection technique. This study showed that the former is consistently more efficient than the latter-in several cases the CloudLasso selection time was half that of the corresponding cylinder-based selection.

Original languageEnglish
Article number6327229
Pages (from-to)2245-2254
Number of pages10
JournalIEEE Transactions on Visualization and Computer Graphics
Volume18
Issue number12
DOIs
Publication statusPublished - 2012
Externally publishedYes

Keywords

  • 3D interaction
  • direct-touch interaction
  • spatial selection

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