Image content is more important than Bouma’s Law for scene metamers

We subjectively perceive our visual field with high fidelity, yet large peripheral distortions can go unnoticed and peripheral objects can be difficult to identify (crowding). A recent paper proposed a model of the mid-level ventral visual stream in which neural responses were averaged over an area of space that increased as a function of eccentricity (scaling). Human participants could not discriminate synthesised model images from each other (they were metamers) when scaling was about half the retinal eccentricity. This result implicated ventral visual area V2 and approximated “Bouma’s Law” of crowding. It has subsequently been interpreted as a link between crowding zones, receptive field scaling, and our rich perceptual experience. However, participants in this experiment never saw the original images. We find that participants can easily discriminate real and model-generated images at V2 scaling. Lower scale factors than even V1 receptive fields may be required to generate metamers. Efficiently explaining why scenes look as they do may require incorporating segmentation processes and global organisational constraints in addition to local pooling.

• Publication year

  2018

• Venue

  bioRxiv

• Publication date

  2018-07-30

• Fields of study

  Biology, Medicine, Computer Science, Psychology

• Identifiers
  DOI 10.7554/eLife.42512PMID 31038458PMCID 6491040
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• Explaining why scenes look as they do may require segmentation processes and global organisational constraints in addition to local pooling.

  Confidence 0.89

  박진우 (dztg5apj7m) extraction뀨 (7c402c1b98) reviewB (s683577b42) review
• Generating scene metamers may require scale factors lower than those of V1 receptive fields.

  Confidence 0.91

  박진우 (dztg5apj7m) extraction뀨 (7c402c1b98) reviewB (s683577b42) review
• Participants easily discriminated real images from model-generated images at V2 scaling, so that setting did not yield indistinguishable scene metamers.

  Confidence 0.96

  박진우 (dztg5apj7m) extraction뀨 (7c402c1b98) reviewB (s683577b42) review

• bouma's law

  psychophysical law

  A psychophysical rule linking the spatial extent of crowding to retinal eccentricity.

  Aliases: Bouma law

  박진우 (dztg5apj7m) extraction뀨 (7c402c1b98) reviewB (s683577b42) review
• global organisational constraints

  computational constraint

  Scene-level structural regularities that constrain how visual elements are arranged and interpreted.

  Aliases: global organization constraints

  박진우 (dztg5apj7m) extraction뀨 (7c402c1b98) reviewB (s683577b42) review
• local pooling

  model operation

  The aggregation of responses from a limited neighborhood of visual input into a single summary representation.

  Aliases: pooling

  박진우 (dztg5apj7m) extraction뀨 (7c402c1b98) reviewB (s683577b42) review
• real and model-generated images

  comparison set

  The comparison between original scene images and images synthesized by the metamer model in the experiment.

  Aliases: real images and model-generated images

  박진우 (dztg5apj7m) extraction뀨 (7c402c1b98) reviewB (s683577b42) review
• scene metamers

  perceptual object

  Synthesized images intended to match the perceptual appearance of a source scene under a visual model.

  Aliases: metamers

  박진우 (dztg5apj7m) extraction뀨 (7c402c1b98) reviewB (s683577b42) review
• segmentation processes

  computational process

  Processes that partition a visual scene into distinct objects or regions.

  Aliases: segmentation

  박진우 (dztg5apj7m) extraction뀨 (7c402c1b98) reviewB (s683577b42) review
• v1 receptive fields

  neural property

  The spatial regions over which neurons in primary visual cortex integrate visual input.

  Aliases: primary visual cortex receptive fields

  박진우 (dztg5apj7m) extraction뀨 (7c402c1b98) reviewB (s683577b42) review
• v2 scaling

  model parameter

  The model regime in which pooling area increases with retinal eccentricity at a rate associated with ventral visual area V2.

  Aliases: scaling

  박진우 (dztg5apj7m) extraction뀨 (7c402c1b98) reviewB (s683577b42) review

• Local contour symmetry facilitates scene categorization.

  2019cited by this paper
• ggplot2

  2019cited by this paper
• knitr: A Comprehensive Tool for Reproducible Research in R

  2018cited by this paper
• Image content is more important than Bouma’s Law for scene metamers

  2018cited by this paper
• ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

  2018cited by this paper
• Prediction shapes peripheral appearance.

  2018cited by this paper
• Prior object-knowledge sharpens properties of early visual feature-detectors

  2018cited by this paper
• Foundations of Vision

  2018cited by this paper
• A parametric texture model based on deep convolutional features closely matches texture appearance for humans

  2017cited by this paper
• Are we underestimating the richness of visual experience?

  2017cited by this paper
• Towards Metamerism via Foveated Style Transfer

  2017cited by this paper
• Object segmentation controls image reconstruction from natural scenes

  2017cited by this paper
• Evolving the Keys to Visual Crowding

  2017cited by this paper
• Eidolons: Novel stimuli for vision research.

  2017cited by this paper
• From Textures to Crowds : Multiple Levels of Summary Statistical Perception

  2017cited by this paper
• Advanced Bayesian Multilevel Modeling with the R Package brms

  2017cited by this paper
• Neural Dynamics of Grouping and Segmentation Explain Properties of Visual Crowding

  2017cited by this paper
• ggplot2 - Elegant Graphics for Data Analysis (2nd Edition)

  2017cited by this paper
• brms: An R Package for Bayesian Multilevel Models Using Stan

  2017cited by this paper
• Coefficient-wise tree-based varying coefficient regression with vcrpart

  2017cited by this paper
• Erratum to: Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC

  2016cited by this paper
• Can (should) theories of crowding be unified?

  2016cited by this paper
• Pooling of continuous features provides a unifying account of crowding

  2016cited by this paper
• Mid-level perceptual features distinguish objects of different real-world sizes.

  2016cited by this paper
• Search performance is better predicted by tileability than presence of a unique basic feature

  2016cited by this paper
• Capabilities and Limitations of Peripheral Vision.

  2016cited by this paper
• An overview of quantitative approaches in Gestalt perception.

  2016cited by this paper
• Deep Neural Networks as a Computational Model for Human Shape Sensitivity

  2016cited by this paper
• What is the Bandwidth of Perceptual Experience?

  2016influential reference
• Image Style Transfer Using Convolutional Neural Networks

  2016cited by this paper
• Finding faces, animals, and vehicles in far peripheral vision.

  2016cited by this paper
• Selectivity and tolerance for visual texture in macaque V2

  2016cited by this paper
• A general account of peripheral encoding also predicts scene perception performance.

  2016influential reference
• Specificity and timescales of cortical adaptation as inferences about natural movie statistics

  2016cited by this paper
• Extra Themes, Scales and Geoms for 'ggplot2'

  2016cited by this paper
• AVA Christmas Meeting, Queen Mary University of London, December 21, 2015

  2016cited by this paper
• Testing models of peripheral encoding using metamerism in an oddity paradigm.

  2016cited by this paper
• Texture Synthesis Using Convolutional Neural Networks

  2015cited by this paper
• Cube search, revisited.

  2015cited by this paper
• Dynamic Documents with R and knitr

  2015cited by this paper
• Crowding, grouping, and object recognition: A matter of appearance.

  2015cited by this paper
• Statistical Rethinking: A Bayesian Course with Examples in R and Stan

  2015cited by this paper
• Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC

  2015cited by this paper
• James Jurin (1684-1750): a pioneer of crowding research?

  2015cited by this paper
• Chapter 8 – JAGS

  2015cited by this paper
• Nonaccidental Properties Underlie Human Categorization of Complex Natural Scenes

  2014cited by this paper
• R: A language and environment for statistical computing.

  2014cited by this paper
• A formula for human retinal ganglion cell receptive field density as a function of visual field location.

  2014cited by this paper
• Adaptation to vergent and averted eye gaze.

  2014cited by this paper
• The statistics of local motion signals in naturalistic movies.

  2014cited by this paper
• The new visual neurosciences

  2014cited by this paper
• A predictive processing theory of sensorimotor contingencies: Explaining the puzzle of perceptual presence and its absence in synesthesia

  2014cited by this paper
• The Bouma law of crowding, revised: critical spacing is equal across parts, not objects.

  2014cited by this paper
• Visual crowding illustrates the inadequacy of local vs. global and feedforward vs. feedback distinctions in modeling visual perception

  2014cited by this paper
• Representation of Naturalistic Image Structure in the Primate Visual Cortex.

  2014cited by this paper
• Very Deep Convolutional Networks for Large-Scale Image Recognition

  2014influential reference
• Image statistics underlying natural texture selectivity of neurons in macaque V4

  2014cited by this paper
• Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan

  2014influential reference
• A functional and perceptual signature of the second visual area in primates

  2013cited by this paper
• Accurate Junction Detection and Characterization in Natural Images

  2013cited by this paper
• Seeing and Windows of Integration

  2013cited by this paper
• The radial and tangential extent of spatial metamers

  2013cited by this paper
• When crowding of crowding leads to uncrowding.

  2013cited by this paper
• Texture analysis and perception

  2013cited by this paper
• Understanding predictive information criteria for Bayesian models

  2013cited by this paper
• The role of stationary and dynamic test patterns in rapid forms of motion after-effect.

  2013cited by this paper
• What is the best fixation target? The effect of target shape on stability of fixational eye movements.

  2013cited by this paper
• The Role of Attention in Conscious Recollection

  2012cited by this paper
• Differential effects of exogenous and endogenous attention on second-order texture contrast sensitivity.

  2012cited by this paper
• Grouping, pooling, and when bigger is better in visual crowding.

  2012cited by this paper
• A century of Gestalt psychology in visual perception: II. Conceptual and theoretical foundations.

  2012cited by this paper
• The role of crowding in contextual influences on contour integration.

  2012cited by this paper
• Optimal integration of shading and binocular disparity for depth perception.

  2012cited by this paper
• Nonconscious Influences from Emotional Faces: A Comparison of Visual Crowding, Masking, and Continuous Flash Suppression

  2012cited by this paper
• A century of Gestalt psychology in visual perception: I. Perceptual grouping and figure-ground organization.

  2012cited by this paper
• Contrast Negation and Texture Synthesis Differentially Disrupt Natural Texture Appearance

  2012cited by this paper
• A Benchmark of Computational Models of Saliency to Predict Human Fixations

  2012cited by this paper
• Dynamics of oculomotor direction discrimination.

  2012cited by this paper
• Asymmetries and idiosyncratic hot spots in crowding.

  2011cited by this paper
• Image correlates of crowding in natural scenes.

  2011cited by this paper
• Metamers of the ventral stream

  2011cited by this paper
• The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo

  2011cited by this paper
• Rethinking the Role of Top-Down Attention in Vision: Effects Attributable to a Lossy Representation in Peripheral Vision

  2011cited by this paper
• Object-level visual information gets through the bottleneck of crowding.

  2011cited by this paper
• The Split-Apply-Combine Strategy for Data Analysis

  2011cited by this paper
• (In) sensitivity to spatial distortion in natural scenes.

  2010cited by this paper
• The role of higher order image statistics in masking scene gist recognition

  2010cited by this paper
• Local motion effects on form in radial frequency patterns.

  2010cited by this paper
• A temporal limit on judgments of the position of a moving object

  2010cited by this paper
• Language as a link between exact number and approximate magnitude

  2010cited by this paper
• Modern Applied Statistics with S

  2010cited by this paper
• Supercrowding: weakly masking a target expands the range of crowding.

  2009cited by this paper
• Crowding in peripheral vision: why bigger is better.

  2009cited by this paper
• DEoptim: An R Package for Global Optimization by Differential Evolution

  2009cited by this paper
• The aperture problem in contoured stimuli.

  2009cited by this paper
• A summary-statistic representation in peripheral vision explains visual crowding.

  2009cited by this paper
• Global stimulus configuration modulates crowding.

  2009cited by this paper
• Context influences contour integration.

  2009cited by this paper
• Dissociable effects of attention and crowding on orientation averaging.

  2009cited by this paper
• A summary statistic representation in peripheral vision explains visual search.

  2009cited by this paper

• Generating metamers of human scene understanding

  2026cites this paper
• MAME: Multidimensional Adaptive Metamer Exploration with Human Perceptual Feedback

  2025cites this paper
• Human visual grouping based on within- and cross-area temporal correlations

  2025cites this paper
• Responses of neurons in macaque V4 to object and texture images

  2025cites this paper
• Are we ready to tackle perceptual segmentation of natural scenes?

  2025cites this paper
• Dynamics of vision: Grouping takes longer than crowding

  2025cites this paper
• Choice- and trial-history effects on causality perception in Schizophrenia Spectrum Disorder

  2025cites this paper
• Metacognition of perceptual resolution across and around the visual field.

  2024cites this paper
• Neural Correlates of Crowding in Macaque Area V4

  2024cites this paper
• COCO-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery

  2024cites this paper
• A spatiotemporal style transfer algorithm for dynamic visual stimulus generation

  2024cites this paper
• The visibility of Eidolon distortions in things and stuff

  2024influential citation
• Measuring uncertainty in human visual segmentation

  2023cites this paper
• Neural correlates of crowding in macaque area V4

  2023cites this paper
• Measuring uncertainty in human visual segmentation

  2023cites this paper
• Foveated metamers of the early visual system

  2023influential citation
• Model metamers illuminate divergences between biological and artificial neural networks

  2023cites this paper
• Visual crowding: Double dissociation between orientation and brightness judgments

  2023cites this paper
• Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks

  2022cites this paper
• Hierarchical binding in convolutional neural networks: Making adversarial attacks geometrically challenging

  2022cites this paper
• Unsupervised learning of features and object boundaries from local prediction

  2022cites this paper
• Texture-like representation of objects in human visual cortex

  2022influential citation
• Generalized Rectifier Wavelet Covariance Models For Texture Synthesis

  2022cites this paper
• Evaluating the Adversarial Robustness of a Foveated Texture Transform Module in a CNN

  2021cites this paper
• Redundancy between spectral and higher-order texture statistics for natural image segmentation

  2021cites this paper
• Spatial structure, phase, and the contrast of natural images

  2021cites this paper
• Shrinking Bouma’s window: How to model crowding in dense displays

  2021cites this paper
• Efficient Dataflow Modeling of Peripheral Encoding in the Human Visual System

  2021cites this paper
• Opposing effects of selectivity and invariance in peripheral vision

  2021cites this paper
• Dissecting (un)crowding

  2021cites this paper
• The Portilla-Simoncelli Texture Model: towards Understanding the Early Visual Cortex

  2021cites this paper
• Global and high-level effects in crowding cannot be predicted by either high-dimensional pooling or target cueing

  2021cites this paper
• Metameric Varifocal Holograms

  2021cites this paper
• On the use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation

  2021cites this paper
• Redundancy masking: The loss of repeated items in crowded peripheral vision

  2020cites this paper
• Flexible contextual modulation of naturalistic texture perception in peripheral vision

  2020cites this paper
• Crowding and attention in a framework of neural network model

  2020cites this paper
• Visual Functions of Primate Area V4.

  2020cites this paper
• Emergent Properties of Foveated Perceptual Systems

  2020cites this paper
• Texture Interpolation for Probing Visual Perception

  2020cites this paper
• Multi-scale Transformer Language Models

  2020cites this paper
• Metamers of neural networks reveal divergence from human perceptual systems

  2019cites this paper
• A common framework for visual crowding in typical and amblyopic vision

  2019cites this paper
• Characterizing a snapshot of perceptual experience.

  2019cites this paper
• Object shape and surface properties are jointly encoded in mid-level ventral visual cortex.

  2019cites this paper
• Accelerated Texforms: Alternative Methods for Generating Unrecognizable Object Images with Preserved Mid-Level Features

  2019cites this paper
• Crowding Reveals Fundamental Differences in Local vs. Global Processing in Humans and Machines

  2019cites this paper
• Subjective inflation: phenomenology's get-rich-quick scheme.

  2018cites this paper
• Peripheral Representations: from Perception to Visual Search

  2018cites this paper
• etamerism via F oveated S tyle T ransfer

  2018influential citation
• Image content is more important than Bouma’s Law for scene metamers

  2018cites this paper
• Neural Dynamics of Grouping and Segmentation Explain Properties of Visual Crowding

  2017cites this paper