SpaceCast
Also known as CAST
In a 3D particle cloud on a 2D screen, the user draws a lasso; of the dense clusters inside it, the one whose outline best matches the lasso is selected, preferring nearer clusters.
How it works
The particles are turned into a smooth density field. Inside the frustum of the lasso, regions above a density threshold are split into separate clusters, each is projected to the screen, and the one with the largest overlap with the lasso is chosen; a cluster in front wins if its overlap is at least 80% of the best. A slider then adjusts the density threshold. Works for partly occluded clusters as long as the user traces the target's border. Compared on a pen tablet (20 participants) with cylinder selection and CloudLasso: the CAST techniques took 16 to 23 s against 43 s for CloudLasso and 88 s for cylinders, with the same accuracy.
Papers
- Lingyun Yu, Konstantinos Efstathiou, Petra Isenberg, Tobias Isenberg (2016). CAST: Effective and Efficient User Interaction for Context-Aware Selection in 3D Particle Clouds. IEEE Transactions on Visualization and Computer Graphics 22(1), 886-895 doi:10.1109/TVCG.2015.2467202
- Lonni Besançon, Mickael Sereno, Mehdi Ammi, Lingyun Yu, Tobias Isenberg (2019). Hybrid Touch/Tangible Spatial 3D Data Selection. Computer Graphics Forum 38(3), 553-567 doi:10.1111/cgf.13710