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Squishicalization: Exploring Elastic Volume Physicalization
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AI
DOI：10.1109/TVCG.2024.3516481.png)
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Abstract
En 中文
We introduce <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Squishicalization</i>, 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 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Squishicalization</i>, 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 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Squishicalization</i>.
Keywords:
Data physicalization
digital fabrication
volume data
tactile information encoding
Journal
IF:
6.5
Papers:
294
Citations:
2.2W
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