Interactive design of periodic yarn-level cloth patterns

Interactive design of periodic yarn-level cloth patterns
复制标题

DOI:
10.1145/3272127.3275105
复制
发表时间:
2018-12
期刊:
ACM Transactions on Graphics (TOG)
影响因子:
--
通讯作者:
Jonathan Leaf;Rundong Wu;Eston Schweickart;Doug L. James;Steve Marschner
Jonathan Leaf;Rundong Wu;Eston Schweickart;Doug L. James;Steve Marschner
中科院分区:
其他
文献类型:
--
作者:
Jonathan Leaf;Rundong Wu;Eston Schweickart;Doug L. James;Steve Marschner

文献摘要

被引文献

相似文献

我们描述了一种用于编织和编织布的纱线级图案的交互式设计工具。为了实现臭名昭著的缓慢纱线级模拟的交互性能,我们提出了两个加速度方案:(a)纱线级的周期性边界条件,可以仅对小量周期贴片进行限制模拟,从而利用许多布模式在红衣主教方向上的空间重复,(b)高度平行的GPU求解器,用于对小斑块的有效纱线级模拟。我们的系统支持交互式模式编辑和仿真,以及参数的运行时修改。为了调整所使用的材料量(纱线摄取),我们支持(a)(a)(a)针对图案特定编辑的局部纱线静止调整,例如,拧紧滑动针迹,以及(b)全球纱线长度通过新颖的纱线 - 拉迪乌斯相似性转换。我们演示了该工具的能力,可以通过新手用户,各种纱线编织和编织模式来支持交互式建模的能力。最后,为了验证我们的方法,我们将数十种生成的模式与实际编织或针织布样品的参考图像进行了比较,并将这种数字模式和模拟模型的语料库作为公共数据集进行了比较,以支持将来的比较。
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.