Adaptive pointcloud segmentation for assisted interactions
Harald Steinlechner (VRVis Research Center)
Bernhard Rainer (AIT Austrian Institute of Technology)
M. Schwarzler (TU Delft - Computer Graphics and Visualisation)
Georg Haaser (VRVis Research Center)
Attila Szabo (VRVis Research Center)
Stefan Maierhofer (VRVis Research Center)
Michael Wimmer (Technische Universität Wien)
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Abstract
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.