Georgia Tech students explore color recognition in artworks through an innovative fusion of APIs and machine learning. The research utilizes the Art Institute of Chicago's API for metadata acquisition, combined with a color clustering algorithm, allowing for a detailed statistical analysis of color usage in
This team from Georgia Tech discuss the process of data cleaning and analysis in the context of studying color patterns in artworks. They used a dataset from the Art Institute of Chicago, consisting of 122,435 artworks, for this purpose. The data was cleaned to extract
This article explores the use of clustering algorithms and art museum APIs to extract dominant color palettes from artworks, with a focus on the collection of the Art Institute of Chicago. The authors demonstrate how to programmatically access image and metadata, extract color statistics, and