FabObscura: Computational Design and Fabrication for Interactive Barrier-Grid Animations
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3746059.3747629.pdf
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1.97 MB
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Checksum (MD5)
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Author(s)
Sethapakdi, Ticha
Perroni-Scharf, Maxine
Li, Mingming
Li, Jiaji
Solomon, Justin
Satyanarayan, Arvind
Mueller, Stefanie
Date Issued
September 27, 2025
Publisher
ACM|The 38th Annual ACM Symposium on User Interface Software and Technology
Citation
Ticha Sethapakdi, Maxine Perroni-Scharf, Mingming Li, Jiaji Li, Justin Solomon, Arvind Satyanarayan, and Stefanie Mueller. 2025. FabObscura: Computational Design and Fabrication for Interactive Barrier-Grid Animations. In Proceedings of the 38th Annual ACM Symposium on User Interface Software and Technology (UIST '25). Association for Computing Machinery, New York, NY, USA, Article 109, 1–16.
Version
Final published version
Abstract
We present FabObscura: a system for creating interactive barrier-grid animations, a classic technique that uses occlusion patterns to create the illusion of motion. Whereas traditional barrier-grid animations are constrained to simple linear occlusion patterns, FabObscura introduces a parameterization that represents patterns as mathematical functions. Our parameterization offers two key advantages over existing barrier-grid animation design methods: first, it has a high expressive ceiling by enabling the systematic design of novel patterns; second, it is versatile enough to represent all established forms of barrier-grid animations.
Using this parameterization, our computational design tool enables an end-to-end workflow for authoring, visualizing, and fabricating these animations without domain expertise. Our applications demonstrate how FabObscura can be used to create animations that respond to a range of user interactions, such as translations, rotations, and changes in viewpoint. By formalizing barrier-grid animation as a computational design material, FabObscura extends its expressiveness as an interactive medium.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1145/3746059.3747629
