The Spatiotemporal Power Spectrum of Natural Human Vision

DuTell, Vasha; Gibaldi, Agostino; Focarelli, Giulia; Olshausen, Bruno A.; Banks, M S

doi:10.1167/jov.20.11.1661

Cited by 7 publications

(5 citation statements)

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“…Therefore, such a system tends to oppose to the power-law falloff, counterbalancing the latter and enabling an equalized response to all discernible frequencies when the stimulus has such statistical properties. The investigation with natural image stimuli also proved that our neuromorphic system equipped with FEMs starts an early stage of redundancy suppression as a precursor of subsequent whitening processes 23 – 25 . Since no explicit spatial filtering is actually implemented from the DAVIS sensor, the origin of the observed whitening effect should be ascribed to the combination of three main characteristics of the sensing strategy: (1) the peculiar motion used 8 , (2) the transient response of the camera, and (3) some non-linear behavior 7 in the acquisition process of single pixels.…”

Section: Discussionmentioning

confidence: 61%

Active fixation as an efficient coding strategy for neuromorphic vision

Testa

Sabatini

Canessa

2023

Sci Rep

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Contrary to a photographer, who puts a great effort in keeping the lens still, eyes insistently move even during fixation. This benefits signal decorrelation, which underlies an efficient encoding of visual information. Yet, camera motion is not sufficient alone; it must be coupled with a sensor specifically selective to temporal changes. Indeed, motion induced on standard imagers only results in burring effects. Neuromorphic sensors represent a valuable solution. Here we characterize the response of an event-based camera equipped with fixational eye movements (FEMs) on both synthetic and natural images. Our analyses prove that the system starts an early stage of redundancy suppression, as a precursor of subsequent whitening processes on the amplitude spectrum. This does not come at the price of corrupting structural information contained in local spatial phase across oriented axes. Isotropy of FEMs ensures proper representations of image features without introducing biases towards specific contrast orientations.

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Section: Discussionmentioning

confidence: 61%

Active fixation as an efficient coding strategy for neuromorphic vision

Testa

Sabatini

Canessa

2023

Sci Rep

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“…Therefore, such a system tends to oppose to the power-law falloff, counterbalancing the latter and enabling an equalized response to all discernible frequencies when the stimulus has such statistical properties. The investigation with natural image stimuli also proved that our neuromorphic system equipped with FEMs starts an early stage of redundancy suppression as a precursor of subsequent whitening processes [23][24][25] . Since no explicit spatial filtering is actually implemented from the DAVIS sensor, the origin of the observed whitening effect should be ascribed to the combination of three main characteristics of the sensing strategy: (1) the peculiar motion used 8 , (2) the transient response of the camera, and (3) some non-linear behavior 7 in the acquisition process of single pixels.…”

Section: Discussionmentioning

confidence: 61%

Active Fixation as an Efficient Coding Strategy for Neuromorphic Vision

Testa

Sabatini

Canessa

2022

Preprint

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Contrary to a photographer, who puts a great effort in keeping the lens still, eyes insistently move even during fixation. This benefits signal decorrelation, which underlies an efficient encoding of visual information. Yet, camera motion is not sufficient alone; it must be coupled with a sensor specifically selective to temporal changes. Indeed, motion induced on standard imagers only results in burring effects. Neuromorphic sensors represent a valuable solution. Here we characterize the response of an event-based camera equipped with Fixational Eye Movements (FEMs) on both synthetic and natural images. Our analyses prove that the system starts an early stage of redundancy suppression, as a precursor of subsequent whitening processes on the amplitude spectrum. This does not come at the price of corrupting structural information contained in local spatial phase across oriented axes. Isotropy of FEMs ensures proper representations of image features without introducing biases towards specific contrast orientations.

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“…In this case, one could define the ideal observer prior with a mixture of Gaussians that matches an empirically measured distribution of scene statistics, forgoing the need to fit the prior from perceptual judgment data. Indeed, several groups have made progress in the estimating the distribution of spectral content in terrestrial scenes ( Field, 1987 ; Dong and Atick, 1995 ), tilt of objects in natural scenes ( Burge et al, 2016 ), binocular disparity ( Sprague et al, 2015 ), and the spectral content of retinal motion during eye and head movements ( DuTell et al, 2020 ). While the match between estimates of natural statistics and perceptual biases has been investigated previously with numerical methods ( Girshick et al, 2011 ; Sprague et al, 2015 ), a (relatively) low dimensional parameterization of these stimulus distributions opens up new opportunities for efficiency and experimental investigations.…”

Section: Discussionmentioning

confidence: 99%

A General Framework for Inferring Bayesian Ideal Observer Models from Psychophysical Data

Manning

Naecker²,

McLean³

et al. 2022

eNeuro

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A central question in neuroscience is how sensory inputs are transformed into percepts. At this point, it is clear that this process is strongly influenced by prior knowledge of the sensory environment. Bayesian ideal observer models provide a key link between data and theory that can help researchers evaluate how prior knowledge is represented and integrated with incoming sensory information. However, the statistical prior employed by a Bayesian observer cannot be measured directly, and must instead be inferred from behavioral measurements. Here we review the general problem of inferring priors from psychophysical data, and the simple solution that follows from assuming a prior that is a Gaussian probability distribution. As our understanding of sensory processing advances, however, there is an increasing need for methods to flexibly recover the shape of Bayesian priors that are not well-approximated by elementary functions. To address this issue, we describe a novel approach that applies to arbitrary prior shapes, which we parameterize using mixtures of Gaussian distributions. After incorporating a simple approximation, this method produces an analytical solution for psychophysical quantities that can be numerically optimized to recover the shapes of Bayesian priors. This approach offers advantages in flexibility, while still providing an analytical framework for many scenarios. We provide a MATLAB toolbox implementing key computations described herein.

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The Spatiotemporal Power Spectrum of Natural Human Vision

Cited by 7 publications

References 0 publications

Active fixation as an efficient coding strategy for neuromorphic vision

Active fixation as an efficient coding strategy for neuromorphic vision

Active Fixation as an Efficient Coding Strategy for Neuromorphic Vision

A General Framework for Inferring Bayesian Ideal Observer Models from Psychophysical Data

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