Literature DB >> 19853450

Crowding in peripheral vision: why bigger is better.

Dennis M Levi1, Thom Carney.   

Abstract

We enjoy the illusion that visual resolution is high across the entire field of vision. However, this illusion can be easily dispelled by trying to identify objects in a cluttered environment out of the corner of your eye. This reflects, in part, the well-known decline in visual resolution in peripheral vision; however, the main bottleneck for reading or object recognition in peripheral vision is crowding. Objects that can be easily identified in isolation seem indistinct and jumbled in clutter. Crowding is thought to reflect inappropriate integration of the target and flankers in peripheral vision [1, 2]. Here, we uncover and explain a paradox in peripheral crowding: under certain conditions, increasing the size or number of flanking rings results in a paradoxical decrease in the magnitude of crowding-i.e., the bigger or more numerous the flanks, the smaller the crowding. These surprising results are predicted by a model in which crowding is determined by the centroids of approximately 4-8 independent features within approximately 0.5x the target eccentricity. These features are then integrated into a texture beyond the stage of feature analysis. We speculate that this process may contribute to the illusion of high resolution across the field of vision.

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Year:  2009        PMID: 19853450      PMCID: PMC3045113          DOI: 10.1016/j.cub.2009.09.056

Source DB:  PubMed          Journal:  Curr Biol        ISSN: 0960-9822            Impact factor:   10.834


  33 in total

1.  The two-dimensional shape of spatial interaction zones in the parafovea.

Authors:  A Toet; D M Levi
Journal:  Vision Res       Date:  1992-07       Impact factor: 1.886

2.  Capacity limit of visual short-term memory in human posterior parietal cortex.

Authors:  J Jay Todd; René Marois
Journal:  Nature       Date:  2004-04-15       Impact factor: 49.962

3.  Crowding is unlike ordinary masking: distinguishing feature integration from detection.

Authors:  Denis G Pelli; Melanie Palomares; Najib J Majaj
Journal:  J Vis       Date:  2004-12-30       Impact factor: 2.240

4.  Holistic crowding: selective interference between configural representations of faces in crowded scenes.

Authors:  Elizabeth G Louie; David W Bressler; David Whitney
Journal:  J Vis       Date:  2007-11-26       Impact factor: 2.240

5.  Crowding with conjunctions of simple features.

Authors:  Endel Põder; Johan Wagemans
Journal:  J Vis       Date:  2007-11-20       Impact factor: 2.240

6.  Grouping of contextual elements that affect vernier thresholds.

Authors:  Maka Malania; Michael H Herzog; Gerald Westheimer
Journal:  J Vis       Date:  2007-01-29       Impact factor: 2.240

7.  The roles of cortical image separation and size in active visual search performance.

Authors:  Brad C Motter; Diglio A Simoni
Journal:  J Vis       Date:  2007-02-08       Impact factor: 2.240

8.  Lateral interactions in peripherally viewed texture arrays.

Authors:  F Wilkinson; H R Wilson; D Ellemberg
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  1997-09       Impact factor: 2.129

Review 9.  The uncrowded window of object recognition.

Authors:  Denis G Pelli; Katharine A Tillman
Journal:  Nat Neurosci       Date:  2008-10       Impact factor: 24.884

Review 10.  Crowding--an essential bottleneck for object recognition: a mini-review.

Authors:  Dennis M Levi
Journal:  Vision Res       Date:  2008-01-28       Impact factor: 1.886

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  46 in total

1.  The mechanism of word crowding.

Authors:  Deyue Yu; Melanie M U Akau; Susana T L Chung
Journal:  Vision Res       Date:  2011-11-07       Impact factor: 1.886

2.  Visual crowding is correlated with awareness.

Authors:  Thomas S A Wallis; Peter J Bex
Journal:  Curr Biol       Date:  2011-02-08       Impact factor: 10.834

3.  Vision: seeing through the gaps in the crowd.

Authors:  David Whitney
Journal:  Curr Biol       Date:  2009-12-15       Impact factor: 10.834

4.  Crowding is tuned for perceived (not physical) location.

Authors:  Steven C Dakin; John A Greenwood; Thomas A Carlson; Peter J Bex
Journal:  J Vis       Date:  2011-08-08       Impact factor: 2.240

5.  Crowding, grouping, and object recognition: A matter of appearance.

Authors:  Michael H Herzog; Bilge Sayim; Vitaly Chicherov; Mauro Manassi
Journal:  J Vis       Date:  2015       Impact factor: 2.240

6.  Crowding by a repeating pattern.

Authors:  Sarah Rosen; Denis G Pelli
Journal:  J Vis       Date:  2015       Impact factor: 2.240

7.  Cube search, revisited.

Authors:  Xuetao Zhang; Jie Huang; Serap Yigit-Elliott; Ruth Rosenholtz
Journal:  J Vis       Date:  2015-03-16       Impact factor: 2.240

8.  The dependence of crowding on flanker complexity and target-flanker similarity.

Authors:  Jean-Baptiste Bernard; Susana T L Chung
Journal:  J Vis       Date:  2011-07-05       Impact factor: 2.240

9.  Image correlates of crowding in natural scenes.

Authors:  Thomas S A Wallis; Peter J Bex
Journal:  J Vis       Date:  2012-07-13       Impact factor: 2.240

10.  Contour interaction in foveal vision: a response to Siderov, Waugh, and Bedell (2013).

Authors:  Daniel R Coates; Dennis M Levi
Journal:  Vision Res       Date:  2013-11-08       Impact factor: 1.886

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