R.I.P.
๐ป
Ghosted
Sculptable Mesh Structures for Room-Scale Form-Finding
July 09, 2026 ยท Grace Period ยท ๐ UIST 2025: Proceedings of the 38th Annual ACM Symposium on User Interface Software and Technology
Authors
Jesse T. Gonzalez, Yanzhen Zhang, Dian Zhu, Alice Yu, Sapna Tayal, Nazm Furniturewala, Ziying Qi, Somin Ella Moon, Leyi Han, Alexandra Ion, Scott E. Hudson
arXiv ID
2607.08736
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
UIST 2025: Proceedings of the 38th Annual ACM Symposium on User Interface Software and Technology
Abstract
It can be hard to design a physical structure entirely within the confines of a computer monitor. To better capture the interplay between real-world objects and a designer's work-in-progress, practitioners will often go through a sequence of low-fidelity prototypes (paper, clay, foam) before arriving at a form that satisfies both functional and aesthetic concerns. While necessary, this model-making process can be quite time-consuming, particularly at larger scales, and the resulting geometry can be difficult to translate into a CAD environment, where it will be further refined. This paper introduces a user-adjustable, room-scale, "shape-aware" mesh structure for low-fidelity prototyping. A user physically manipulates the mesh by lengthening and shortening the edges, altering the overall curvature and sculpting coarse forms. The edges are equipped with resistive length sensors, and transmit their configuration to a central computer. The structure can later be reproduced in software, connecting this prototyping stage to the larger computational design pipeline.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Human-Computer Interaction
R.I.P.
๐ป
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
๐ป
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
๐ป
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
๐ป
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
๐ป
Ghosted