A Computational Model for Visual Metaphors. Interpreting Creative Visual Advertisements
نویسندگان
چکیده
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 viewers 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 common technique to create new, interesting and unconventional interpretations. In this paper, we analyzed the role of perceptual similarity in various advertisements and propose an extension to the “Heuristic-Driven Theory Projection”, an existing computational framework for analogy-making, that can be used to automatically compute interpretations for creative visual metaphors in advertisements.
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