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.

Global Illumination is affected by the slightest change in a 3D scene, requiring a complete reevaluation of the distributed light. In cases where real-time algorithms are not applicable due to high demands on the achievable accuracy, this recomputation from scratch results in artifacts like flickering or noise, disturbing the visual appearance and negatively affecting interactive lighting design workflows. We propose a novel system tackling this problem by providing incremental updates of a baked global illumination solution after scene modifications, and a re-convergence after a few seconds. Using specifically targeted incremental data structures and prioritization strategies in a many-light global illumination algorithm, we compute a differential update from one illumination state to another. We further demonstrate the use of a novel error balancing strategy making it possible to prioritize the illumination updates.