Color Aesthetics: Fuzzy based User-driven Method for Harmony and
  Preference Prediction
Pakizar Shamoi Atsushi Inoue Hiroharu Kawanaka
Color is the most important intrinsic sensory feature that has a powerful
impact on product sales. Color is even responsible for raising the aesthetic
senses in our brains. Account for individual differences is crucial in color
aesthetics. It requires user-driven mechanisms for various e-commerce
applications. We propose a method for quantitative evaluation of all types of
perceptual responses to color(s): distinct color preference, color harmony, and
color combination preference. Preference for color schemes can be predicted by
combining preferences for the basic colors and ratings of color harmony.
Harmonious pallets are extracted from big data set using comparison algorithms
based on fuzzy similarity and grouping. The proposed model results in useful
predictions of harmony and preference of multicolored images. For example, in
the context of apparel coordination, it allows predicting a preference for a
look based on clothing colors. Our approach differs from standard aesthetic
models, since in accounts for a personal variation. In addition, it can process
not only lower-order color pairs, but also groups of several colors.