A computational model for visual metaphors: Interpreting creative visual advertisements

Abstract

Coming up with new and creative advertisements is a sophisticated task for humans, because creativity requires breaking conventional associations to create new juxtaposition of familiar objects. Using objects in an uncommon context attracts the viewer's attention and is an effective way to communicate a message in advertisements. Perceptual similarity seems to be a major source for creativity in the domain of visual metaphors, e.g. replacing objects by perceptually similar, but conceptually different objects is a technique to create new and unconventional interpretations. In this paper, we analyze the role of perceptual similarity in advertisements and propose an extension of Heuristic-Driven Theory Projection, a computational theory for analogy making that can be used to automatically compute interpretations of visual metaphors.