Adaptive pointcloud segmentation for assisted interactions

Harald Steinlechner, Bernhard Rainer, Michael Schwarzler, Georg Haaser, Attila Szabo, Stefan Maierhofer, Michael Wimmer

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)
6 Downloads (Pure)


In this work, we propose an interaction-driven approach streamlined to support and improve a wide range of real-time 2D interaction metaphors for arbitrarily large pointclouds based on detected primitive shapes. Rather than performing shape detection as a costly pre-processing step on the entire point cloud at once, a user-controlled interaction determines the region that is to be segmented next. By keeping the size of the region and the number of points small, the algorithm produces meaningful results and therefore feedback on the local geometry within a fraction of a second. We can apply these finding for improved picking and selection metaphors in large point clouds, and propose further novel shape-assisted.

Original languageEnglish
Title of host publicationProceedings - I3D 2019
Subtitle of host publicationACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery (ACM)
Number of pages9
ISBN (Electronic)9781450363105
Publication statusPublished - 21 May 2019
Event2019 ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, I3D 2019 - Montreal, Canada
Duration: 21 May 201923 May 2019


Conference2019 ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, I3D 2019


  • Interactive Editing
  • Pointcloud Segmentation
  • Shape Detection

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