Object-level visual information gets through the bottleneck of crowding

Abstract

Natural visual scenes are cluttered. In such scenes, many objects in the periphery can be crowded, blocked from identification, simply because of the dense array of clutter. Outside of the fovea, crowding constitutes the fundamental limitation on object recognition and is thought to arise from the limited resolution of the neural mechanisms that select and bind visual features into coherent objects. Thus it is widely believed that in the visual processing stream, a crowded object is reduced to a collection of dismantled features with no surviving holistic properties. Here, we show that this is not so: an entire face can survive crowding and contribute its holistic attributes to the perceived average of the set, despite being blocked from recognition. Our results show that crowding does not dismantle high-level object representations to their component features.

Face features and face configurations both contribute to visual crowding

“…For example, Banno and Saiki (2012) revealed a deleterious impact of nearby flankers on calculation of average circle size, suggesting that statistical information about the entire array cannot pass through or circumvent the crowding bottleneck intact. However, studies have also shown that average emotional expression can be extracted from crowded arrays of faces (Fischer & Whitney, 2011; Haberman & Whitney, 2007; 2009; Kouider, Berthet, & Faivre, 2011), suggesting that the computation of the average may belie the impact of crowding on earlier, less holistic stages of processing. Comparing crowding performance in face recognition tasks to results obtained with simpler stimuli (e.g.…”

“…Presently, by dissociating featural and configural information we have made it possible to observe the extent to which global information is preserved and contributes to perception during crowding (Fischer & Whitney, 2011) while also finding evidence that individual features can impact the crowded percept despite disruption of global flanker appearance (Faivre & Kouider, 2011). The crowded perception of complex objects (faces, in particular) thus appears to be determined by integration of both the local and global features of an object.…”

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

“…Many studies rely on the above hierarchical, feedfoward models assuming that crowding is a low-level bottleneck and thus crowding can be used to study which features are filtered out at the early stage of vision and which features are passed on for conscious perception. Unconscious processing of orientation [32], objects [33] and facial expressions [34,35] were shown to pass through the bottleneck of crowding, placing its cortical mechanism higher and higher along the visual hierarchy.…”

Differential hemispheric and visual stream contributions to ensemble coding of crowd emotion

“…Ensemble coding provides precise global representation 1,7,8,10 , with little or no conscious perception 6,7,11–13 or sampling of individual members in a set 14,15 . Recent work has further shown that ensemble coding occurs for even more complex objects, such as averaging emotion from sets of faces 2,3,16–19 , facial identity 16,20–23 , as well as a crowd’s movements 24,25 and gaze direction 26,27 .…”

“…From a perceiver’s perspective, for example, an angry face elicits an avoidance reaction while a happy face elicits approach reaction 28,30–32 . To date, however, empirical work undertaken on ensemble perception of faces has largely concentrated on the efficiency and the fidelity of crowd perception 2,3,16–23 , but not on how this process is socially relevant. To our knowledge, no studies have examined how humans make speeded social decisions about which crowd of faces to approach or avoid, based on extracted ensemble features of facial crowds (e.g., crowd emotion).…”