  Computational aesthetics is an emerging field of research which has attracted
different research groups in the last few years. In this field, one of the main
approaches to evaluate the aesthetic quality of paintings and photographs is a
feature-based approach. Among the different features proposed to reach this
goal, color plays an import role. In this paper, we introduce a novel dataset
that consists of paintings of Western provenance from 36 well-known painters
from the 15th to the 20th century. As a first step and to assess this dataset,
using a classifier, we investigate the correlation between the subjective
scores and two widely used features that are related to color perception and in
different aesthetic quality assessment approaches. Results show a
classification rate of up to 73% between the color features and the subjective
scores.
