Uncorking the bottleneck of crowding: a fresh look at object recognition

Herzog, Michael H.; Manassi, Mauro

doi:10.1016/j.cobeha.2014.10.006

Cited by 67 publications

(63 citation statements)

References 43 publications

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“…flankers and targets substantially differ in complexity (Zhang, Zhang, Xue, Liu, & Yu, 2009). Herzog and Manassi (2015) in a recent overview of these studies have offered a strong argument against the conventional, exclusively bottom-up account of crowding.…”

Section: Introductionmentioning

confidence: 96%

Side flankers produce less crowding, but only for letters

Vejnović

Zdravković

2015

Cognition

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Section: Introductionmentioning

confidence: 96%

Side flankers produce less crowding, but only for letters

Vejnović

Zdravković

2015

Cognition

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“…Indeed, even the term crowding refers to the result of some visual process and not a mechanism. The underlying cause of crowding has previously been explained by various computational models1123404142474849 and higher-level mechanistic hypotheses2450. Population code models, in which all visual features probabilistically contribute to perceptual reports, can produce a wide variety of data51, including so-called averaging and substitution errors41.…”

mentioning

confidence: 99%

Visual crowding is a combination of an increase of positional uncertainty, source confusion, and featural averaging

Harrison

Bex

2017

Sci Rep

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Although we perceive a richly detailed visual world, our ability to identify individual objects is severely limited in clutter, particularly in peripheral vision. Models of such “crowding” have generally been driven by the phenomenological misidentifications of crowded targets: using stimuli that do not easily combine to form a unique symbol (e.g. letters or objects), observers typically confuse the source of objects and report either the target or a distractor, but when continuous features are used (e.g. orientated gratings or line positions) observers report a feature somewhere between the target and distractor. To reconcile these accounts, we develop a hybrid method of adjustment that allows detailed analysis of these multiple error categories. Observers reported the orientation of a target, under several distractor conditions, by adjusting an identical foveal target. We apply new modelling to quantify whether perceptual reports show evidence of positional uncertainty, source confusion, and featural averaging on a trial-by-trial basis. Our results show that observers make a large proportion of source-confusion errors. However, our study also reveals the distribution of perceptual reports that underlie performance in this crowding task more generally: aggregate errors cannot be neatly labelled because they are heterogeneous and their structure depends on target-distractor distance.

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“…Our results are however inconsistent with higher-level theories of crowding. Gestalt approaches (21) argue that crowding occurs when the target is 'grouped' with the flankers, e.g. by forming a pattern with the flankers (44), and that it is reduced when the flankers form patterns that exclude the target (45).…”

Section: Discussionmentioning

confidence: 99%

“…Given the distributed processing of these features across the visual system (17,18), can one process produce this multitude of effects? Most models implicitly assume that crowding is a single mechanism that affects all features in a combined manner, particularly for higherorder approaches where crowding derives from attention (19,20) or grouping (21). If crowding were instead to operate independently for distinct visual features, these effects could involve an array of neural substrates with varied mechanisms.…”

Section: Introductionmentioning

confidence: 99%

Dissociable effects of visual crowding on the perception of colour and motion

Greenwood

Parsons

2019

Preprint

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Our ability to recognise objects in peripheral vision is fundamentally limited by crowding, the deleterious effect of clutter that disrupts the recognition of features ranging from orientation and colour to motion and depth. Prior research is equivocal on whether this reflects a singular process that disrupts all features simultaneously or multiple processes that affect each independently. We examined crowding for motion and colour, two features that allow a strong test of feature independence. 'Cowhide' stimuli were presented 15 degrees in peripheral vision, either in isolation or surrounded by flankers to give crowding. Observers reported either the target hue (blue/purple) or its direction (clockwise/counterclockwise from upwards). We first established that both features show systematic crowded errors (predominantly biased towards the flanker identities) and selectivity for target-flanker similarity (with reduced crowding for dissimilar target/flanker elements). The multiplicity of crowding was then tested with observers identifying both features: a singular object-selective mechanism predicts that when crowding is weak for one feature and strong for the other that crowding should be all-or-none for both. In contrast, when crowding was weak for colour and strong for motion, errors were reduced for colour but remained for motion, and vice versa with weak motion and strong colour crowding. This double dissociation follows the predictions of independent crowding processes, suggesting that crowding can disrupt vision in a feature-specific manner. The ability to recognise one aspect of a cluttered scene, like colour, thus offers no guarantees for the correct recognition of other aspects, like motion. Significance statementThe fundamental limitation on our peripheral vision is crowding, the disruptive effect of image clutter on object recognition. Crowding is widely assumed to be a singular process, affecting all of the features (e.g. orientation, motion, and colour) within an object simultaneously. In contrast, we find a double dissociation for these disruptions: observers can make errors in judging the colour of a crowded object whilst correctly judging its movement direction, and vice versa. This dissociation is well described by a population-coding model that independently pools the motion and colour of target and flanker elements. We suggest that crowding may be a generic set of processes distributed throughout the visual system that independently simplify the representation of our visual field.

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Uncorking the bottleneck of crowding: a fresh look at object recognition

Cited by 67 publications

References 43 publications

Side flankers produce less crowding, but only for letters

Side flankers produce less crowding, but only for letters

Visual crowding is a combination of an increase of positional uncertainty, source confusion, and featural averaging

Dissociable effects of visual crowding on the perception of colour and motion

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