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  Image content is more important than1Bouma’s Law for scene metamers

Wallis, T., Funke, C., Ecker, A., Gatys, L., Wichmann, F., & Bethge, M. (2019). Image content is more important than1Bouma’s Law for scene metamers. eLife, 8, 1-43. doi:10.7554/eLife.42512.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0005-678F-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-6790-4
Genre: Journal Article

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https://elifesciences.org/articles/42512 (Publisher version)
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 Creators:
Wallis, TSA, Author
Funke, CM, Author
Ecker, AS, Author              
Gatys, LA, Author
Wichmann, FA, Author              
Bethge, M1, 2, Author              
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              

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 Abstract: We subjectively perceive our visual field with high fidelity, yet peripheral distortions can go unnoticed and peripheral objects can be difficult to identify (crowding). Prior work showed that humans could not discriminate images synthesised to match the responses of a mid-level ventral visual stream model when information was averaged in receptive fields with a scaling of about half their retinal eccentricity. This result implicated ventral visual area V2, approximated ‘Bouma’s Law’ of crowding, and has subsequently been interpreted as a link between crowding zones, receptive field scaling, and our perceptual experience. However, this experiment never assessed natural images. We find that humans can easily discriminate real and model-generated images at V2 scaling, requiring scales at least as small as V1 receptive fields to generate metamers. We speculate that explaining why scenes look as they do may require incorporating segmentation and global organisational constraints in addition to local pooling.

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 Dates: 2019-04
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.7554/eLife.42512
eDoc: e42512
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Title: eLife
Source Genre: Journal
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Publ. Info: Cambridge : eLife Sciences Publications
Pages: - Volume / Issue: 8 Sequence Number: - Start / End Page: 1 - 43 Identifier: ISSN: 2050-084X
CoNE: https://pure.mpg.de/cone/journals/resource/2050-084X