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Article Dans Une Revue Applied Artificial Intelligence Année : 2001

A Model of Abstraction in Visual Perception

Lorenza Saitta
  • Fonction : Auteur

Résumé

In artificial intelligence, abstraction has been mainly studied as a mapping between languages in relation to problem-solving, with the aim of reducing the complexity of the task. However, abstraction has a much larger scope in reasoning; we are investigating, in this article, how abstraction can be used in concept representation. To this aim, we propose a novel, perception-based model of abstraction, which originates from the observation that conceptualization of a domain, even though involving entities belonging to several epistemological levels, is nevertheless primarily based on perception. This view has been recently advocated by Goldstone and Barsalou in cognitive science. A model of representation/abstraction is then proposed and its application to a real-world problem of robot visual perception and categorization is presented.
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Dates et versions

hal-01184259 , version 1 (13-08-2015)

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Lorenza Saitta, Jean-Daniel Zucker. A Model of Abstraction in Visual Perception. Applied Artificial Intelligence, 2001, 15 (8), pp.761-776. ⟨10.1080/088395101317018591⟩. ⟨hal-01184259⟩
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