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Industrial Applications of Affective Engineering pp 111–122Cite as

Modeling Emotional Evaluation of Traditional Vietnamese Aodai Clothes Based on Computer Vision and Machine Learning

Abstract

The more that human society develops, the greater the human need for well-mannered and elegant clothes, especially traditional costumes. Selecting fine clothes for a specific occasion is always an interesting individual question. Based on computer vision and machine learning, this research proposes a Kansei (emotional) evaluation for Aodai, which is traditional and well-known Vietnamese clothes for women. Features of an Aodai image are described by color coherence vectors. Self-organizing maps (SOMs) and multilayer neural networks (NNs) are used to learn the relationships between the image features and the Kansei words. Once learned, the system can recommend which Aodai is suitable for a woman through her desired feelings. She can use this recommendation when purchasing an Aodai at online stores or selecting one from her own collection for an outing. Topics for future research include investigating other image representation methods, such as combinations of color buckets in different parts of the Aodai, using more detailed descriptions in decorative patterns, and integrating conspicuity factors such as color harmony, discriminability and visibility.

Keywords

  • Kansei
  • Vietnamese Aodai
  • Fashion design
  • Traditional costume
  • Color coherence vector

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Acknowledgments

The authors would like to thank Mr. Dang Tuan Linh at Ritsumeikan University and other people for their valuable help on the Aodai evaluation survey.

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Authors and Affiliations

  1. The University of Electro-Communications, Tokyo, Japan

    Thang Cao

  2. VNU University of Science, Hanoi, Vietnam

    Hung T. Nguyen

  3. Hanoi Water Resources University, Hanoi, Vietnam

    Hien M. Nguyen

  4. Kochi University of Technology, Kochi, Japan

    Yukinobu Hoshino

Authors
  1. Thang Cao
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  2. Hung T. Nguyen
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  3. Hien M. Nguyen
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  4. Yukinobu Hoshino
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Corresponding author

Correspondence to Thang Cao .

Editor information

Editors and Affiliations

  1. Graduate School of Information, Production and Systems (IPS), Waseda University, Kitakyushu, Fukuoka, Japan

    Junzo Watada

  2. Kogakuin University, Tokyo, Tokyo, Japan

    Hisao Shiizuka

  3. Department of Industrial Design, KAIST, Yusung-gu, Daejon-shi, Korea, Republic of (South Korea)

    Kun-Pyo Lee

  4. Department of Kansei Engineering Faculty of Textile Science and Technolog, Shinshu University, Matsumoto, Nagano, Japan

    Tsuyoshi Otani

  5. Centre for Intelligent Systems Research, Deakin University Geelong Waurn Ponds Campus, Waurn Ponds, West Australia, Australia

    Chee-Peng Lim

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Cao, T., Nguyen, H.T., Nguyen, H.M., Hoshino, Y. (2014). Modeling Emotional Evaluation of Traditional Vietnamese Aodai Clothes Based on Computer Vision and Machine Learning. In: Watada, J., Shiizuka, H., Lee, KP., Otani, T., Lim, CP. (eds) Industrial Applications of Affective Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-04798-0_9

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  • DOI: https://doi.org/10.1007/978-3-319-04798-0_9

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