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

机译:FoCo系统:弥合时尚与人工智能之间的领域鸿沟的工具

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Purpose 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/approach The 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. Findings With practical applications in mind, the FoCo system is designed as a hierarchical structure with three layers. Originality/value The 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.
机译:目的时尚色彩(FoCo)值与语言色彩表达之间的映射不足,导致与色彩匹配紧密相关的基于机器的时尚理解任务的困难。本文的目的是提出FoCo系统,并分四个步骤构建它,以弥合这一差距。设计/方法/方法分析HSB颜色空间中的颜色分布,以估计大致的颜色类别。将相似的颜色值进行分组以获得每种颜色类别的初始HSB值范围。计算类别内的色差以确定其最终的HSB值范围,并使用Pantone颜色进行微调。结果考虑到实际应用,FoCo系统被设计为具有三层的分层结构。原创性/价值FoCo系统被设计为具有三层的层次结构:用于颜色匹配相关任务的颜色单位,用于样式分析任务的颜色类别以及用于颜色识别任务的色调。大量实验证明了FoCo系统的有效性。

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