KnitPicking Textures: Programming and Modifying Complex Knitted Textures for Machine and Hand Knitting - Robotics Institute Carnegie Mellon University

KnitPicking Textures: Programming and Modifying Complex Knitted Textures for Machine and Hand Knitting

Megan Hofmann, Lea Albaugh, Ticha Sethapakadi, Jessica Hodgins, Scott E. Hudson, James McCann, and Jennifer Mankoff
Conference Paper, Proceedings of 32nd Annual ACM Symposium on User Interface Software and Technology (UIST '19), pp. 5 - 16, October, 2019

Abstract

Knitting creates complex, soft fabrics with unique texture properties that can be used to create interactive objects. However, little work addresses the challenges of designing and using knitted textures computationally. We present KnitPick: a pipeline for interpreting hand-knitting texture patterns into KnitGraphs which can be output to machine and hand-knitting instructions. Using KnitPick, we contribute a measured and photographed data set of 472 knitted textures. Based on findings from this data set, we contribute two algorithms for manipulating KnitGraphs. KnitCarving shapes a graph while respecting a texture, and KnitPatching combines graphs with disparate textures while maintaining a consistent shape. KnitPick is the first system to bridge the gap between hand-and machine-knitting when creating complex knitted textures.

BibTeX

@conference{Hofmann-2019-121964,
author = {Megan Hofmann and Lea Albaugh and Ticha Sethapakadi and Jessica Hodgins and Scott E. Hudson and James McCann and Jennifer Mankoff},
title = {KnitPicking Textures: Programming and Modifying Complex Knitted Textures for Machine and Hand Knitting},
booktitle = {Proceedings of 32nd Annual ACM Symposium on User Interface Software and Technology (UIST '19)},
year = {2019},
month = {October},
pages = {5 - 16},
}