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Adrien Doerig, Aaron Clarke, Greg Francis, Michael Herzog; Towards a Unifying Model of Crowding: Model Olympics. Journal of Vision 2017;17(10):399. doi: https://doi.org/10.1167/17.10.399.
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© ARVO (1962-2015); The Authors (2016-present)
In crowding, perception of an object deteriorates in the presence of nearby elements. Obviously, crowding is a ubiquitous phenomenon since elements are rarely seen in isolation. Up to date, there exists no consensus on how to model crowding. In previous experiments, it was shown that the global configuration of the entire stimulus needs to be taken into account. These findings rule out simple pooling or substitution models and favor models sensitive to global spatial aspects. In order to further investigate how to incorporate these aspects into models, we tested a large number of models, using a database of about one hundred stimuli. As expected, all local models fail. Further, capturing basic regularities in the stimulus does not suffice to account for global aspects, as illustrated by the failures of Fourier analysis and textural models. Our results highlight the importance of grouping to explain crowding. Specifically, we show that a two-stage model improves performance strongly. In this model, first, elements are segregated into groups and, second, only elements in the same group interfere with each other. The model must integrate information across large parts of the visual field.
Meeting abstract presented at VSS 2017
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