Beyond Bouma's window: How to explain global aspects of crowding?

PLoS Computational Biology
Adrien DoerigM H Herzog

Abstract

In crowding, perception of an object deteriorates in the presence of nearby elements. Although crowding is a ubiquitous phenomenon, since elements are rarely seen in isolation, to date there exists no consensus on how to model it. Previous experiments showed that the global configuration of the entire stimulus must be taken into account. These findings rule out simple pooling or substitution models and favor models sensitive to global spatial aspects. In order to investigate how to incorporate global aspects into models, we tested a large number of models with a database of forty stimuli tailored for the global aspects of crowding. Our results show that incorporating grouping like components strongly improves model performance.

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Citations

Jul 22, 2020·PLoS Computational Biology·Adrien DoerigMichael H Herzog
Jul 28, 2019·Journal of Vision·Ruth RosenholtzShaiyan Keshvari
Jul 25, 2020·PLoS Computational Biology·Noor SeijdelH Steven Scholte
Dec 30, 2020·Journal of Vision·Endel Põder
Jan 5, 2021·Journal of Vision·Daniel Herrera-EspositoLeonel Gomez-Sena
Jan 8, 2021·Journal of Vision·Antonio Rodriguez, Richard Granger
Jul 4, 2021·Vision Research·Daniel Herrera-EspositoRuben Coen-Cagli
Jul 17, 2021·NeuroImage·Maya A JastrzębowskaMichael H Herzog
Jul 7, 2021·PLoS Computational Biology·Alban BornetErik Van der Burg
Jul 30, 2021·Nature Communications·Corey M Ziemba, Eero P Simoncelli
Sep 14, 2021·Journal of Vision·Oh-Hyeon ChoungMichael H Herzog
Oct 29, 2021·Journal of Vision·Robert J LeeJasna Martinovic

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Software Mentioned

Tensorflow
Alexnet
LAMINART

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