Open AccessA COMPUTATIONAL MODEL FOR VISUAL METAPHORS - Interpreting Creative Visual Advertisements
Author(s) -
Angela Schwering,
Kai-Uwe Küehnberger,
Ulf Krumnack,
Helmar Gust,
Tonio Wandmacher,
Bipin Indurkhya,
Amitash Ojha
Publication year - 2009
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5220/0001660303390344
Subject(s) - analogy , computer science , creativity , perception , context (archaeology) , similarity (geometry) , heuristic , task (project management) , domain (mathematical analysis) , human–computer interaction , cognitive science , computational creativity , artificial intelligence , image (mathematics) , psychology , linguistics , mathematics , engineering , paleontology , philosophy , mathematical analysis , biology , social psychology , neuroscience , systems engineering
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.
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