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Geometrical transformations in object categorization


Graf,  M
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Graf, M. (2002). Geometrical transformations in object categorization. Poster presented at Second Annual Meeting of the Vision Sciences Society (VSS 2002), Sarasota, FL, USA.

A previous speeded categorization experiment demonstrated that basic level categorization performance deteriorates with increasing amount of topological (warping) transformation between two successively presented category members (Graf, VSS 2001). If topological transformations are involved in basic level categorization, then performance in related tasks should also be influenced by the amount of shape deformation. In particular, the typicality (or representativeness) of category members should be determined by the transformational distance to the category representation. Also, shape similarity should decrease with increasing transformational distance between the objects. These predictions were investigated for 2D outline shapes of objects from 25 common and familiar object categories. In the typicality task, subjects had to rate the typicality of different category members that were produced with a warping algorithm — i.e. had to judge how well the objects fit with their idea of the category. In the similarity task, the amount of topological transformation between two objects from the same basic level category was manipulated, and subjects had to rate the similarity of the objects. The results confirmed the predictions: First, typicality ratings varied in a systematic way with topological shape transformation: A graded category structure was found, and typicality decreased with increasing distance to the most typical exemplar. Second, perceived similarity decreased in a highly significant way with increasing amount of topological transformation. These findings indicate that basic level categorization performance and perceived shape similarity depend on the amount of topological transformation. The results can be accounted for by an alignment model of categorization and similarity which involves deforming transformations. The suggested model can be regarded as an image-based extension to the structural alignment account of similarity (e.g. Markman Gentner, 1993).