Squishicalization: Exploring Elastic Volume Physicalization

Information

• Publication Type: Journal Paper (without talk)
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: December 2024
• DOI: 10.1109/TVCG.2024.3516481
• ISSN: 1941-0506
• Journal: IEEE Transactions on Visualization and Computer Graphics
• Open Access: yes
• Pages: 14
• Publisher: IEEE COMPUTER SOC
• Pages: 1 – 14
• Keywords: Elasticity, Three Dimensional Printing, Pipelines, Fabrication, Microstructures, Rendering Computer Graphics, Encoding, Printing, Data Physicalization, Data Visualization, Digital Fabrication

Abstract

We introduce Squishicalization , a pipeline for generating physicalizations of volumetric data that encode scalar information through their physical characteristics—specifically, by varying their “squishiness” or local elasticity. Data physicalization research is increasingly exploring multisensory information encoding, with a particular focus on enhancing direct interactivity. With Squishicalization , we leverage the tactile dimension of physicalization as a means of direct interactivity. Inspired by conventional volume rendering, we adapt the concept of transfer functions to encode scalar values from volumetric data into local elasticity levels. In this way, volumetric scalar data are transformed into sculptures, where the elasticity represents physical properties such as the material's density distribution within the volume. In our pipeline, scalar values guide the weighted sampling of the scalar field. The sampled data is then processed through Voronoi tessellation to create a sponge-like structure, which can be printed with consumer-grade 3D printers and readily available filament. To validate our pipeline, we conduct a computational and mechanical evaluation, as well as a two-stage perceptual study of the capabilities of our generated squishicalizations. To further investigate potential application scenarios, we interview experts across several domains. Finally, we summarize actionable insights and future avenues for the application of our All supplemental materials are available at https://osf.io/35gnv/?view_only=605e5085061f40439a98545f0c447cf3 .

Additional Files and Images

Weblinks

• Entry in reposiTUm (TU Wien Publication Database)
• DOI: 10.1109/TVCG.2024.3516481

BibTeX

@article{pahr-2024-squishicalization,
  title =      "Squishicalization: Exploring Elastic Volume Physicalization",
  author =     "Daniel Pahr and Michal Piovar\v{c}i and Hsiang-Yun Wu and
               Renata Raidou",
  year =       "2024",
  abstract =   "We introduce Squishicalization , a pipeline for generating
               physicalizations of volumetric data that encode scalar
               information through their physical
               characteristics—specifically, by varying their
               “squishiness” or local elasticity. Data physicalization
               research is increasingly exploring multisensory information
               encoding, with a particular focus on enhancing direct
               interactivity. With Squishicalization , we leverage the
               tactile dimension of physicalization as a means of direct
               interactivity. Inspired by conventional volume rendering, we
               adapt the concept of transfer functions to encode scalar
               values from volumetric data into local elasticity levels. In
               this way, volumetric scalar data are transformed into
               sculptures, where the elasticity represents physical
               properties such as the material's density distribution
               within the volume. In our pipeline, scalar values guide the
               weighted sampling of the scalar field. The sampled data is
               then processed through Voronoi tessellation to create a
               sponge-like structure, which can be printed with
               consumer-grade 3D printers and readily available filament.
               To validate our pipeline, we conduct a computational and
               mechanical evaluation, as well as a two-stage perceptual
               study of the capabilities of our generated
               squishicalizations. To further investigate potential
               application scenarios, we interview experts across several
               domains. Finally, we summarize actionable insights and
               future avenues for the application of our All supplemental
               materials are available at
               https://osf.io/35gnv/?view_only=605e5085061f40439a98545f0c447cf3
               .",
  month =      dec,
  doi =        "10.1109/TVCG.2024.3516481",
  issn =       "1941-0506",
  journal =    "IEEE Transactions on Visualization and Computer Graphics",
  pages =      "14",
  publisher =  "IEEE COMPUTER SOC",
  pages =      "1--14",
  keywords =   "Elasticity, Three Dimensional Printing, Pipelines,
               Fabrication, Microstructures, Rendering Computer Graphics,
               Encoding, Printing, Data Physicalization, Data
               Visualization, Digital Fabrication",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2024/pahr-2024-squishicalization/",
}