Abstract

We subjectively perceive our visual field with high fidelity, yet peripheral distortions can go unnoticed and peripheral objects can be difficult to identify (crowding). Prior work showed that humans could not discriminate images synthesised to match the responses of a mid-level ventral visual stream model when information was averaged in receptive fields with a scaling of about half their retinal eccentricity. This result implicated ventral visual area V2, approximated 'Bouma's Law' of crowding, and has subsequently been interpreted as a link between crowding zones, receptive field scaling, and our perceptual experience. However, this experiment never assessed natural images. We find that humans can easily discriminate real and model-generated images at V2 scaling, requiring scales at least as small as V1 receptive fields to generate metamers. We speculate that explaining why scenes look as they do may require incorporating segmentation and global organisational constraints in addition to local pooling.

Highlights

  • IntroductionOur entire visual field looks subjectively crisp and clear

  • Vision science seeks to understand why things look as they do (Koffka, 1935)

  • We used 20 images to test the FS model. These images are split into two classes of ten images each, which we labelled ‘scene-like’ and ‘texture-like’. The distinction of these two classes is based on the results of a pilot experiment with a model we developed, which is inspired by the FS model but based on a different set of image features

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Summary

Introduction

Our entire visual field looks subjectively crisp and clear. It is clear that we can be insensitive to significant changes in the world despite our rich subjective experience. Visual crowding has been characterised as compulsory texture perception (Parkes et al, 2001; Lettvin, 1976) and compression (Balas et al, 2009; Rosenholtz et al, 2012a). This idea entails that we cannot perceive the precise structure of the visual world in the periphery. Image-computable texture summary statistics have been shown to be correlated with human performance in various tasks requiring the judgment of peripheral

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