Willich, Julius von ; Günther, Sebastian ; Matviienko, Andrii ; Schmitz, Martin ; Müller, Florian ; Mühlhäuser, Max (2023)
DensingQueen: Exploration Methods for Spatial Dense Dynamic Data.
11th ACM Symposium on Spatial User Interaction. Sydney, Australia (13.-15.10.2023)
doi: 10.1145/3607822.3614535
Conference or Workshop Item, Bibliographie
Abstract
Research has proposed various interaction techniques to manage the occlusion of 3D data in Virtual Reality (VR), e.g., via gradual refinement. However, tracking dynamically moving data in a dense 3D environment poses the challenge of ever-changing occlusion, especially if motion carries relevant information, which is lost in still images. In this paper, we evaluated two interaction modalities for Spatial Dense Dynamic Data (SDDD), adapted from existing interaction methods for static and spatial data. We evaluated these modalities for exploring SDDD in VR, in an experiment with 18 participants. Furthermore, we investigated the influence of our interaction modalities on different levels of data density on the users’ performance in a no-knowledge task and a prior-knowledge task. Our results indicated significantly degraded performance for higher levels of density. Further, we found that our flashlight-inspired modality successfully improved tracking in SDDD, while a cutting plane-inspired approach was more suitable for highlighting static volumes of interest, particularly in such high-density environments.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2023 |
| Creators: | Willich, Julius von ; Günther, Sebastian ; Matviienko, Andrii ; Schmitz, Martin ; Müller, Florian ; Mühlhäuser, Max |
| Type of entry: | Bibliographie |
| Title: | DensingQueen: Exploration Methods for Spatial Dense Dynamic Data |
| Language: | English |
| Date: | 13 October 2023 |
| Publisher: | ACM |
| Book Title: | SUI '23: Proceedings of the 2023 ACM Symposium on Spatial User Interaction |
| Event Title: | 11th ACM Symposium on Spatial User Interaction |
| Event Location: | Sydney, Australia |
| Event Dates: | 13.-15.10.2023 |
| DOI: | 10.1145/3607822.3614535 |
| URL / URN: | https://dl.acm.org/doi/abs/10.1145/3607822.3614535 |
| Abstract: | Research has proposed various interaction techniques to manage the occlusion of 3D data in Virtual Reality (VR), e.g., via gradual refinement. However, tracking dynamically moving data in a dense 3D environment poses the challenge of ever-changing occlusion, especially if motion carries relevant information, which is lost in still images. In this paper, we evaluated two interaction modalities for Spatial Dense Dynamic Data (SDDD), adapted from existing interaction methods for static and spatial data. We evaluated these modalities for exploring SDDD in VR, in an experiment with 18 participants. Furthermore, we investigated the influence of our interaction modalities on different levels of data density on the users’ performance in a no-knowledge task and a prior-knowledge task. Our results indicated significantly degraded performance for higher levels of density. Further, we found that our flashlight-inspired modality successfully improved tracking in SDDD, while a cutting plane-inspired approach was more suitable for highlighting static volumes of interest, particularly in such high-density environments. |
| Uncontrolled Keywords: | Spatial Data, Data Interaction, Virtual Reality, Dense Data, Data exploration, Dynamic Data |
| Additional Information: | Art.No.: 22 |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Telecooperation LOEWE LOEWE > LOEWE-Zentren LOEWE > LOEWE-Zentren > emergenCITY |
| Date Deposited: | 01 Nov 2023 13:19 |
| Last Modified: | 22 Nov 2023 10:47 |
| PPN: | 513393064 |
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