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FoCo system: a tool to bridge the domain gap between fashion and artificial intelligence

FoCo system: a tool to bridge the domain gap between fashion and artificial intelligence The deficiency of the mapping between fashion color (FoCo) value and linguistic color expression causes the difficulty of machine-based fashion understanding tasks that are heavily associated with color matching. The purpose of this paper is to propose the FoCo system and construct it with four steps, in order to bridge this gap.Design/methodology/approachThe color distribution in HSB color space is analyzed to estimate the rough number of color categories. Similar color values are grouped to obtain the initial HSB value range for each color category. The intra-category color differences are calculated to determine their final HSB value ranges and Pantone color is used for fine-tuning.FindingsWith practical applications in mind, the FoCo system is designed as a hierarchical structure with three layers.Originality/valueThe FoCo system is designed as a hierarchical structure with three layers: color units for color matching-related tasks, color categories for style analysis tasks and color tones for color recognition tasks. Extensive experiments demonstrate the effectiveness of the FoCo system. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Clothing Science and Technology Emerald Publishing

FoCo system: a tool to bridge the domain gap between fashion and artificial intelligence

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0955-6222
DOI
10.1108/ijcst-10-2018-0130
Publisher site
See Article on Publisher Site

Abstract

The deficiency of the mapping between fashion color (FoCo) value and linguistic color expression causes the difficulty of machine-based fashion understanding tasks that are heavily associated with color matching. The purpose of this paper is to propose the FoCo system and construct it with four steps, in order to bridge this gap.Design/methodology/approachThe color distribution in HSB color space is analyzed to estimate the rough number of color categories. Similar color values are grouped to obtain the initial HSB value range for each color category. The intra-category color differences are calculated to determine their final HSB value ranges and Pantone color is used for fine-tuning.FindingsWith practical applications in mind, the FoCo system is designed as a hierarchical structure with three layers.Originality/valueThe FoCo system is designed as a hierarchical structure with three layers: color units for color matching-related tasks, color categories for style analysis tasks and color tones for color recognition tasks. Extensive experiments demonstrate the effectiveness of the FoCo system.

Journal

International Journal of Clothing Science and TechnologyEmerald Publishing

Published: Sep 2, 2019

Keywords: Fashion; Artificial intelligence; Color cognition; Color matching; Style analysis

References