Perceptual and Computational Categories in Art

Abstract

The categorization of art (paintings, literature) into distinct styles such as expressionism, or surrealism has had a profound influence on how art is presented, marketed, analyzed, and historicized. Here, we present results from several perceptual experiments with the goal of determining whether such categories also have a perceptual foundation. Following experimental methods from perceptual psychology on category formation, naive, non-expert participants were asked to sort printouts of artworks from different art periods into categories. Converting these data into similarity data and running a multi-dimensional scaling (MDS) analysis, we found distinct perceptual categories which did in some cases correspond to canonical art periods. Initial results from a comparison with several computational algorithms for image analysis and scene categorization are also reported.