A spatial frequency spectral peakedness model predicts discrimination performance of regularity in dot patterns

Protonotarios, Emmanouil D.; Griffin, Lewis D.; Johnston, Alan; Landy, Michael S.

doi:10.1016/j.visres.2018.06.008

Cited by 3 publications

(12 citation statements)

References 55 publications

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“…8A), i.e. lower SFs, as seen earlier [16]. Increasing element size pushes the high peak to the right, toward higher SFs (Fig.…”

Section: Regularity Model Based On the Sf Distributionsupporting

confidence: 78%

“…It is made Implications for the use of MLCM Our study provides a new ANOVA-based statistical framework for using three-factor MLCM. Traditional MLCM has provided a framework for handling only two factors, comparing a full vs. additive model [16]. The main goal for the traditional MLCM approach has been to determine whether the two factors contribute to a perceptual judgment additively or in a nonlinear manner.…”

Section: Discussionmentioning

confidence: 99%

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Visual perception of texture regularity: conjoint measurements and a wavelet response-distribution model

Sun

Baker

Kingdom

et al. 2021

Preprint

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Texture regularity, such as the repeating pattern in a carpet, brickwork or tree bark, is a ubiquitous feature of the visual world. The perception of regularity has generally been studied using multi-element textures in which the degree of regularity has been manipulated by adding random jitter to the elements’ positions. Here we used three-factor Maximum Likelihood Conjoint Measurement (MLCM) to investigate the encoding of regularity information under more complex conditions in which element spacing and size, in addition to positional jitter, were manipulated. Human observers were presented with large numbers of pairs of multi-element stimuli with varying levels of the three factors, and indicated on each trial which stimulus appeared more regular. All three factors contributed to regularity perception. Jitter, as expected, strongly affected regularity perception. This effect of jitter on regularity perception is strongest at small element spacing and large texture element size, suggesting that the visual system utilizes the edge-to-edge distance between elements as the basis for regularity judgments. We then examined how the responses of a bank of Gabor wavelet spatial filters might account for our results. Our analysis indicates that SF-peakedness, a previously favored proposal, is insufficient for regularity encoding since it varied more with element spacing and size than with jitter. Instead, our results support the idea that the visual system may extract texture regularity information from the moments of the SF-distribution across orientation. In our best-performing model, the variance of SF-distribution skew across orientations can explain 70% of the variance of estimated texture regularity from our data, suggesting that it could provide a candidate read-out for perceived regularity.

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“…8A), i.e. lower SFs, as seen earlier [16]. Increasing element size pushes the high peak to the right, toward higher SFs (Fig.…”

Section: Regularity Model Based On the Sf Distributionsupporting

confidence: 78%

Section: Discussionmentioning

confidence: 99%

Visual perception of texture regularity: conjoint measurements and a wavelet response-distribution model

Sun

Baker

Kingdom

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Based on these SF models, it is expected that other factors which change the SF-distribution parameters, in addition to the widely used jittering of element position [ 5 – 7 , 13 , 14 ], may potentially affect regularity perception. For example, increasing element size can increase SF-peakedness substantially, and as expected, regularity discriminability is enhanced [ 16 ]. Element spacing can also affect SF-peakedness, but the peak in the SF-response distribution related to spacing might overlap with the peak from size, giving two separate peaks [ 16 ] or a composite peak if they overlap.…”

Section: Introductionmentioning

confidence: 74%

“…In line with the above studies, researchers have suggested that the peakedness of the distribution of oriented spatial frequency-tuned filter responses might help explain regularity encoding [ 5 , 6 , 16 ]. Based on these studies as well as evidence from our simultaneous regularity contrast study [ 7 ], we suggested that in addition to SF-peakedness, other statistics of the SF-distribution–such as the bandwidth (width at half maximum, FWHM), kurtosis, skew and standard deviation–are also good predictors of perceived regularity, and could therefore be used for coding regularity in the visual system.…”

Section: Introductionmentioning

confidence: 79%

“…Previous studies on regularity perception mostly utilized jitter of element positions as the main manipulation [5][6][7]13,14] and the results corresponded well with simple SF-peakedness [5,6,16]. In this study we investigated the representation and encoding of regularity information considering other factors in addition to element jitter, and utilize a different approachthe Maximum Likelihood Conjoint Measurement (MLCM) method [17,18].…”

Section: Introductionmentioning

confidence: 80%

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Visual perception of texture regularity: Conjoint measurements and a wavelet response-distribution model

et al. 2021

View full text Add to dashboard Cite

Texture regularity, such as the repeating pattern in a carpet, brickwork or tree bark, is a ubiquitous feature of the visual world. The perception of regularity has generally been studied using multi-element textures in which the degree of regularity has been manipulated by adding random jitter to the elements’ positions. Here we used three-factor Maximum Likelihood Conjoint Measurement (MLCM) for the first time to investigate the encoding of regularity information under more complex conditions in which element spacing and size, in addition to positional jitter, were manipulated. Human observers were presented with large numbers of pairs of multi-element stimuli with varying levels of the three factors, and indicated on each trial which stimulus appeared more regular. All three factors contributed to regularity perception. Jitter, as expected, strongly affected regularity perception. This effect of jitter on regularity perception is strongest at small element spacing and large texture element size, suggesting that the visual system utilizes the edge-to-edge distance between elements as the basis for regularity judgments. We then examined how the responses of a bank of Gabor wavelet spatial filters might account for our results. Our analysis indicates that the peakedness of the spatial frequency (SF) distribution, a previously favored proposal, is insufficient for regularity encoding since it varied more with element spacing and size than with jitter. Instead, our results support the idea that the visual system may extract texture regularity information from the moments of the SF-distribution across orientation. In our best-performing model, the variance of SF-distribution skew across orientations can explain 70% of the variance of estimated texture regularity from our data, suggesting that it could provide a candidate read-out for perceived regularity.

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Different symmetries, different mechanisms

Jennings

Tseng

Ouhnana

et al. 2022

Atten Percept Psychophys

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Three common symmetries exist in the natural visual world: (i) mirror symmetry, i.e., reflections around a vertical axis, (ii) radial symmetry, i.e., rotations around a point, and (iii) translational symmetry, i.e., shifted repetitions. Are these processed by a common class of visual mechanism? Using stimuli comprising arrays of Gaussian blobs we examined this question using a visual search protocol in which observers located a single symmetric target patch among varying numbers of random-blob distractor patches. The testing protocol used a blocked present/absent task and both search times and accuracy were recorded. Search times for mirror and radial symmetry increased significantly with the number of distractors, as did translational-symmetry patterns containing few repetitions. However translational-symmetry patterns with four repeating sectors produced search slopes close to zero. Fourier analysis revealed that, as with images of natural scenes, the structural information in both mirror- and radial-symmetric patterns is carried by the phase spectrum. However, for translational patterns with four repeating sectors, the amplitude spectrum appears to capture the structure, consistent with previous analyses of texture regularity. Modeling revealed that while the mirror and radial patterns produced an approximately Gaussian-shaped energy response profile as a function of spatial frequency, the translational pattern profiles contained a distinctive spike, the magnitude of which increased with the number of repeating sectors. We propose distinct mechanisms for the detection of different symmetry types: a mechanism that encodes local positional information to detect mirror- and radial-symmetric patterns and a mechanism that computes energy in narrowband filters for the detection of translational symmetry containing many sectors.

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A spatial frequency spectral peakedness model predicts discrimination performance of regularity in dot patterns

Cited by 3 publications

References 55 publications

Visual perception of texture regularity: conjoint measurements and a wavelet response-distribution model

Visual perception of texture regularity: conjoint measurements and a wavelet response-distribution model

Visual perception of texture regularity: Conjoint measurements and a wavelet response-distribution model

Different symmetries, different mechanisms

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