Application of interactive genetic algorithm to fashion design

Hee Su Kim, Sung-Bae Cho

Research output: Contribution to journalArticle

215 Citations (Scopus)

Abstract

In general, computer-aided design support systems have got an approach of traditional artificial intelligence, which statistically analyzes data such as the behavior of designer, to extract formal design behavior. This approach, however, can neither deal with continuous change of fashion nor reflect personal taste well, as it just depends on large amount of collected data. To overcome this sort of problem interactive genetic algorithm (IGA) has been recently proposed, as a new trend of evolutionary computation. IGA uses human's response as fitness value when the fitness function cannot be explicitly defined. This enables IGA to be applied to artistic domains, and we propose a fashion design aid system using it. Unlike the previous works that attempt to model the dress design by several spline curves, the proposed system is based on a new encoding scheme that practically describes a dress with three parts: body and neck, sleeve, and skirt. By incorporating the domain-specific knowledge into the genotype, we could develop a more realistic design aid system for women's dress. We have implemented the system with OpenGL and VRML to enhance the system interface. The experiments with several human subjects show that the IGA approach to dress design aid system is promising.

Original languageEnglish
Pages (from-to)635-644
Number of pages10
JournalEngineering Applications of Artificial Intelligence
Volume13
Issue number6
DOIs
Publication statusPublished - 2000 Jan 1

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Design aids
Genetic algorithms
Evolutionary algorithms
Splines
Artificial intelligence
Computer aided design
Experiments

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Cite this

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Application of interactive genetic algorithm to fashion design. / Kim, Hee Su; Cho, Sung-Bae.

In: Engineering Applications of Artificial Intelligence, Vol. 13, No. 6, 01.01.2000, p. 635-644.

Research output: Contribution to journalArticle

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