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

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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 

Notes

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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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.The University of Electro-CommunicationsTokyoJapan
  2. 2.VNU University of ScienceHanoiVietnam
  3. 3.Hanoi Water Resources UniversityHanoiVietnam
  4. 4.Kochi University of TechnologyKochiJapan

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