Interactive design of periodic yarn-level cloth patterns

J Leaf, R Wu, E Schweickart, DL James… - ACM Transactions on …, 2018 - dl.acm.org
ACM Transactions on Graphics (TOG), 2018dl.acm.org
We describe an interactive design tool for authoring, simulating, and adjusting yarn-level
patterns for knitted and woven cloth. To achieve interactive performance for notoriously slow
yarn-level simulations, we propose two acceleration schemes:(a) yarn-level periodic
boundary conditions that enable the restricted simulation of only small periodic patches,
thereby exploiting the spatial repetition of many cloth patterns in cardinal directions, and (b)
a highly parallel GPU solver for efficient yarn-level simulation of the small patch. Our system …
We describe an interactive design tool for authoring, simulating, and adjusting yarn-level patterns for knitted and woven cloth. To achieve interactive performance for notoriously slow yarn-level simulations, we propose two acceleration schemes: (a) yarn-level periodic boundary conditions that enable the restricted simulation of only small periodic patches, thereby exploiting the spatial repetition of many cloth patterns in cardinal directions, and (b) a highly parallel GPU solver for efficient yarn-level simulation of the small patch. Our system supports interactive pattern editing and simulation, and runtime modification of parameters. To adjust the amount of material used (yarn take-up) we support "on the fly" modification of (a) local yarn rest-length adjustments for pattern specific edits, e.g., to tighten slip stitches, and (b) global yarn length by way of a novel yarn-radius similarity transformation. We demonstrate the tool's ability to support interactive modeling, by novice users, of a wide variety of yarn-level knit and woven patterns. Finally, to validate our approach, we compare dozens of generated patterns against reference images of actual woven or knitted cloth samples, and we release this corpus of digital patterns and simulated models as a public dataset to support future comparisons.
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