Machine Learning Enhanced User Interfaces for Designing Advanced Knitwear

Martijn ten Bhömer, Hai Ning Liang, Difeng Yu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The relationship between visual appearance and structure and technical properties of a knitted fabric is subtle and complex. This is an area that has been traditionally problematic within the knitting sector, understanding between technologists and designers is hindered which limits the possibility of dialogues from which design innovation can emerge. Recently there has been interest from the Human-Computer Interaction (HCI) community to narrow the gap between product design and knitwear. The goal of this article is to show the potential of predictive software design tools for fashion designers who are developing personalized advanced functionalities in textile products. The main research question explored in this article is: “How can designers benefit from intelligent design software for the manufacturing of personalized advanced functionalities in textile products?”. In particular we explored how to design interactions and interfaces that use intelligent predictive algorithms through the analysis of a case study, in which several predictive algorithms were compared in the practice of textile designers.

Original languageEnglish
Title of host publicationHCI International 2019 - Posters - 21st International Conference, HCII 2019, Proceedings
EditorsConstantine Stephanidis
PublisherSpringer Verlag
Pages212-219
Number of pages8
ISBN (Print)9783030235277
DOIs
Publication statusPublished - 2019
Event21st International Conference on Human-Computer Interaction, HCI International 2019 - Orlando, United States
Duration: 26 Jul 201931 Jul 2019

Publication series

NameCommunications in Computer and Information Science
Volume1033
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference21st International Conference on Human-Computer Interaction, HCI International 2019
Country/TerritoryUnited States
CityOrlando
Period26/07/1931/07/19

Keywords

  • Knitwear
  • Machine learning
  • User Interface

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

Fingerprint

Dive into the research topics of 'Machine Learning Enhanced User Interfaces for Designing Advanced Knitwear'. Together they form a unique fingerprint.

Cite this