# A Graph-Based Representation Method for Fashion Color
## 1 Introduction  
Fashion trends are notoriously volatile and change quickly with time. One major channel to determine fashion trends are fashion shows [1], where the latest fashion designs are debuted. In this event, fashion designers showcase their upcoming lines of clothing through models. According to previous research, color, cut, head decorations, and pattern are four major elements to investigate in fashion styles [2]. The color of the fashion apparel plays a pivotal role in fashion trend prediction.  
However, in most of the existing fashion color research, such as fashion color trend prediction [3; 4; 5] or fashion color compatibility study [6; 7], each of the colors in a piece of fashion apparel is extracted and quantified as an isolated element, as shown in Figure 1. Even if there are multiple colors in the same apparel item, each color is still being measured and quantified independently in the collection and representation of the color data.  
Figure 1: Conventional method of color data collection, analysis, and representation [8].  
Although there are some fixed composition principles for color collocation, they are still not enough to reflect human perception of the colors from a given piece of fashion apparel. Human perception of color is a comprehensive process including not only the attributes of each color itself, but also the collocation relationship between colors [9]. However, there is no work that studies the proper relationship of the colors in fashion apparel with the comprehensive extractable information.  
To capture the relationship between the colors in fashion apparel, there is a need for the proper representation of the color data from a single fashion apparel item as well as extraction of comprehensive information about it. The popularity of the knowledge graph has demonstrated the effectiveness of representing real world entities, i.e., objects, events, situations, and concepts, with comprehensive representation of the relationships between them [10; 11; 12; 13].  
For the reasons above, we aim to develop an advanced color representation of a given fashion apparel item that provides more information about the color data, including not only the attributes of individual color elements, but also their collocation, matching, and geographical information. Given a piece of fashion apparel, four consecutive problems are studied with our method: (1) the number of colors; (2) the ratios of each color; (3) the relationships between each of the colors; and (4) the representation of the colors for better perception.  
This paper studies advanced color representation for fashion apparel with the expectation of understanding whether we can better grasp and recognize the design information of the colors by establishing a more comprehensive color representation from a given fashion apparel item. These results are of great significance for fashion color research. In addition, they also provide a new method for computer-aided quantitative analysis for the recognition and style matching of colors in fashion apparel. In modern color trend prediction and analysis with big amounts of data input, especially when using the most popular machine learning methods, machines are still trying to mimic human cognitive processes for analysis and prediction; however, human cognition of color has not been fully understood and studied. Therefore, the study in this work also aims to add the power to the exploration of color cognitive study.  
The rest of the paper is organized as follows. Section 2 introduces the background and our motivations. Section 3 presents our proposed graph-based color representation method. We evaluate our proposed methods with different case studies in Section 4. Section 5 concludes the paper.