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.
Highlights
When an element is presented in the presence of nearby elements or clutter, it becomes harder to perceive, a well-known effect called crowding
The original image can subsequently be retrieved with good accuracy from the compressed representation, even though neighboring features encoded in the same patch are mingled
The global stimulus configuration plays a crucial role in crowding, which cannot be captured by local models
Summary
When an element is presented in the presence of nearby elements or clutter, it becomes harder to perceive, a well-known effect called crowding. In order to achieve translational invariance, the square neuron is sensitive to lines all over its receptive field and pools this information in order to decide whether a square is present According to this logic, crowding occurs when elements that do not belong to the same object are pooled. Other models have proposed that performance in crowding deteriorates because features of the target are substituted for features of the flanking elements [4,7] As mentioned, all these models are local in the sense that crowding is determined by nearby elements only. All these models are local in the sense that crowding is determined by nearby elements only Based on these two lines of thought, pooling and substitution, researchers have suggested that with more flankers performance deteriorates because more irrelevant features are pooled or substituted
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