Visual search in natural scenes explained by local color properties

Amano, Kinjiro; Foster, David H.; Mould, Matthew S.; Oakley, John P.

doi:10.1364/josaa.29.00a194

Cited by 16 publications

(25 citation statements)

References 49 publications

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“…The methods of data acquisition have been reported elsewhere [30] and are described here only in abbreviated form. The methods of gaze analysis and regression analysis, however, differ from those in [30] and are therefore described in full.…”

Section: Methodsmentioning

confidence: 99%

“…The methods of gaze analysis and regression analysis, however, differ from those in [30] and are therefore described in full.…”

Section: Methodsmentioning

confidence: 99%

“…Over observers and scenes, based on 1120 measurements, the mean calibration error was approximately 0.26 deg, with standard deviation 0.06 deg [30,41].…”

Section: Methodsmentioning

confidence: 99%

“…A previous report on target-detection performance in natural scenes estimated that 36-40% of the variance in observers' fixations could be explained by local scene color [30]. That estimate, however, did not include the possible effect on gaze behavior of observers' viewing strategy.…”

Section: Introductionmentioning

confidence: 92%

“…Data were taken from an experiment on visual search [30] in which images of natural scenes were presented on a color monitor. Within each scene, the target to be searched for was a small, shaded, gray sphere matched in mean luminance to its local surround.…”

Section: Introductionmentioning

confidence: 99%

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Influence of local scene color on fixation position in visual search

Amano

Foster

2014

J. Opt. Soc. Am. A

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Where observers concentrate their gaze during visual search depends on several factors. The aim here was to determine how much of the variance in observers' fixations in natural scenes can be explained by local scene color and how that variance is related to viewing bias. Fixation data were taken from an experiment in which observers searched images of 20 natural rural and urban scenes for a small target. The proportion R 2 of the variance explained in a regression on local color properties (lightness and the red-green and yellow-blue chromatic components) ranged from 1% to 85%, depending mainly on how well those properties were consistent with observers' viewing bias. When viewing bias was included in the regression, values of R 2 increased, ranging from 62% to 96%. By comparison, local lightness and local lightness contrast, edge density, and entropy each explained less variance than local color properties. Local scene color may have a much stronger influence on gaze position than is generally recognized, capturing significant aspects of scene structure on target search behavior.

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Section: Methodsmentioning

confidence: 99%

“…The methods of gaze analysis and regression analysis, however, differ from those in [30] and are therefore described in full.…”

Section: Methodsmentioning

confidence: 99%

“…Over observers and scenes, based on 1120 measurements, the mean calibration error was approximately 0.26 deg, with standard deviation 0.06 deg [30,41].…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Influence of local scene color on fixation position in visual search

Amano

Foster

2014

J. Opt. Soc. Am. A

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Near perfect visual compensation for atmospheric color distortions

Gomes

Linhares

Nascimento

2020

Color Research & Application

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Light is scattered and absorbed in the atmosphere producing visual effects that increase with viewing distance. Contrast and chromatic diversity decrease with distance, thereby modifying the way objects and scenes are perceived. Although some perceptual compensation to produce color constancy of individual surfaces has been reported, it is unclear to what extent unknown original images can be visually inferred from their distorted versions, that is, how much these effects can be discounted by the visual system. We investigated this issue with a paradigm akin to the paper‐matching paradigm used in color constancy studies but with complex natural images. Hyperspectral data from 11 natural scenes were used to simulate their colors for distances up to 2000 m using a precise physical model of the effects of atmosphere. In each trial of the experiment, observers viewed the range of simulated images derived from one scene displayed on a calibrated monitor and selected the one perceived as more natural, without color distortion. Pooling data across scenes and observers showed that the image selected as more natural was very close to the undistorted one, corresponding to a simulated distance of only 2 m. These results suggest that observers are sensitive to changes in the naturalness of colors due to atmospheric effects and, crucially, can retrieve the original chromatic content with good accuracy revealing an efficient form of color constancy.

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Keeping an eye on visual search patterns in visuospatial neglect: A systematic review

Cox

Davies

2020

Neuropsychologia

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Visual search in natural scenes explained by local color properties

Cited by 16 publications

References 49 publications

Influence of local scene color on fixation position in visual search

Influence of local scene color on fixation position in visual search

Near perfect visual compensation for atmospheric color distortions

Keeping an eye on visual search patterns in visuospatial neglect: A systematic review

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