MeTACAST: Target- and Context-Aware Spatial Selection in VR

Abstract

MeTACAST presents target- and context-aware spatial selection techniques for point cloud visualization in VR. The techniques support selection intents such as dense regions, filament-like structures, and clusters while allowing post-selection threshold adjustment. They are designed to reduce the limits of occlusion, non-uniform density, and complex 3D shapes during immersive data selection.

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BibTeX

@article{zhao2024metacast,
  author = {Zhao, Lixiang and Isenberg, Tobias and Xie, Fuqi and Liang, Hai-Ning and Yu, Lingyun},
  title = {MeTACAST: Target- and Context-Aware Spatial Selection in VR},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  volume = {30},
  number = {1},
  pages = {480--494},
  year = {2024},
  doi = {10.1109/TVCG.2023.3326517}
}