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Fashion Design Aid System with Application of Interactive Genetic Algorithms

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Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10198))

Abstract

These days, consumers can make their choice from a wide variety of clothes provided in the market; however, some prefer to have their clothes custom-made. Since most of these consumers are not professional designers, they contact a designer to help them with the process. This approach, however, is not efficient in terms of time and cost and it does not reflect the consumer’s personal taste as much as desired. This study proposes a design system using Interactive Genetic Algorithm (IGA) to overcome these problems. IGA differs from traditional Genetic Algorithm (GA) by leaving the fitness function to the personal preference of the user. The proposed system uses user’s taste as a fitness value to create a large number of design options, and it is based on an encoding scheme either describing a dress as a whole or as a two-part piece of clothing. The system is designed in the Rhinoceros 3D software, using python, which provides good speed and interface options. The assessment experiments with several subjects indicated that the proposed system is effective.

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Acknowledgements

I would like to express my deep gratitude to Professor Upe Flueckiger and Dr. Nelson Rushton for their patient guidance and enthusiastic encouragement during the development of this research work.

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Authors and Affiliations

  1. College of Architecture, Texas Tech University, Lubbock, Texas, USA

    Nazanin Alsadat Tabatabaei Anaraki

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  1. Nazanin Alsadat Tabatabaei Anaraki
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Correspondence to Nazanin Alsadat Tabatabaei Anaraki .

Editor information

Editors and Affiliations

  1. University of Coimbra , Coimbra, Portugal

    João Correia

  2. RMIT University , Melbourne, Victoria, Australia

    Vic Ciesielski

  3. University of Malta , Msida, Malta

    Antonios Liapis

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Tabatabaei Anaraki, N.A. (2017). Fashion Design Aid System with Application of Interactive Genetic Algorithms. In: Correia, J., Ciesielski, V., Liapis, A. (eds) Computational Intelligence in Music, Sound, Art and Design. EvoMUSART 2017. Lecture Notes in Computer Science(), vol 10198. Springer, Cham. https://doi.org/10.1007/978-3-319-55750-2_20

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  • DOI: https://doi.org/10.1007/978-3-319-55750-2_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55749-6

  • Online ISBN: 978-3-319-55750-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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