PwP: Permutating with Probability for Efficient Group Selection in VR
Group selection in virtual reality is an important means of multi-object selection, which allows users to quickly group multiple objects and can significantly improve the operation efficiency of multiple types of objects. In this paper, we propose a group selection method based on multiple rounds of probability permutation, in which the efficiency of group selection is substantially improved by making the object layout of the next round easier to be batch-selected through interactive selection, object grouping probability computation, and position rearrangement in each round of the selection process. We conducted ablation experiments to determine the algorithm coefficients and validate the effectiveness of the algorithm. In addition, an empirical user study was conducted to evaluate the ability of our method to significantly improve the efficiency of the group selection task in an immersive virtual reality environment. The reduced operations also indirectly reduce the user task load and improve usability.
Authors
- Xuehuai Shi
- Han-Dong Chen
- Lili Wang (ORCID: https://orcid.org/0000-0003-4867-4357)
- Wei Lin (ORCID: https://orcid.org/0000-0003-2851-820X)
- Jian Wu (ORCID: https://orcid.org/0000-0001-6094-9056)
- Weicheng Zhang
Institutions
- Nanjing University of Posts and Telecommunications (CN)
- Beihang University (CN)
Publication Details
- Journal
- IEEE Transactions on Visualization and Computer Graphics
- Published
- 2025-03-11
- DOI
- https://doi.org/10.1109/tvcg.2025.3549560
- Primary Topic
- Visual Attention and Saliency Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00