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Towards Rigorous Study of Artistic Style: A New Psychophysical Paradigm

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Gerhard,  Holly
Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Bethge,  M
Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Gerhard, H., & Bethge, M. (2014). Towards Rigorous Study of Artistic Style: A New Psychophysical Paradigm. Art & Perception, 2(1-2), 23-44. doi:10.1163/22134913-00002010.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0027-8069-6
Abstract
What makes one artistrsquo;s style so different from anotherrsquo;s? How do we perceive these differences? Studying the perception of artistic style has proven difficult. Observers typically view several artworks and must group them or rate similarities between pairs. Responses are often driven by semantic variables, such as scene type or the presence/absence of particular subject matter, which leaves little room for studying how viewers distinguish a Degas ballerina from a Toulouse-Lautrec ballerina, for example. In the current paper, we introduce a new psychophysical paradigm for studying artistic style that focuses on visual qualities and avoids semantic categorization issues by presenting only very local views of a piece, thereby precluding object recognition. The task recasts stylistic judgment in a psychophysical texture discrimination framework, where visual judgments can be rigorously measured for trained and untrained observers alike. Stimuli were a dataset of drawings by Pieter Bruegel the Elder and his imitators studied by the computer science community, which showed that statistical analyses of the drawingsrsquo; local content can distinguish an authentic Bruegel from an imitation. Our non-expert observers also successfully discriminated the authentic and inauthentic drawings and furthermore discriminated stylistic variations within the categories, demonstrating the new paradigmrsquo;s feasibility for studying artistic style perception. At the same time, however, we discovered several issues in the Bruegel dataset that bear on conclusions drawn by the computer vision studies of artistic style.