ColorEmo: Color Hunt with Affective Words

Abstract

Color is a main channel to express emotions of an image. Selecting a good color scheme with color harmony and proper emotional expression is very important in many fields, such as design. There are many color palette tools to help users search, create, edit, save, and share color themes, but few tools are from the perspective of emotional expression and explicitly address the emotional effects of colors. In this paper, a color hunt system with affective words called ColorEmo is developed. Multiple types of input, including affective words, affective categories in image-scale space, and main colors, are allowed for users with accurate emotional description. Based on the dataset with 428,924 color themes, the system provides rich candidates. The system is designed for user research experiments. The user-friendly interactions are offered for easy color modifications. The affective matching and color harmony are evaluated in real time while changing colors. This system can be used in many scenarios of designs and applications.

Flexible neural color compatibility model for efficient color extraction from image

“…Color palette is a valuable tool in various research areas related to color Wang et al, 11 Kim and Choi, 12 Yang et al, 13 and Shi et al 14 Color palette extraction involves the identification and extraction of a set of colors from an image or a dataset of images. A common approach for palette extraction is to use the k‐means algorithm, which clusters the existing colors in an image Chang et al, 15 Zhang et al, 16 Phan et al 17 In this method, the user typically sets the hyperparameter k , representing the number of clusters.…”