Processing feature density in preattentive perception

Taylor, Steven; Badcock, David R.

doi:10.3758/bf03207489

Cited by 14 publications

(8 citation statements)

References 21 publications

(38 reference statements)

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“…The difference in latencies between the Nonid (0:1) and Id (0:0) problems was 70 ms, and between the Nonid (0:1) and Id (1:1) problems was 120 ms. Even if the disparity in the numbers of features processed between the Id and Nonid problems is two or more, the estimated search speed would far exceed the criterion of less than 10 ms/feature in the parallel search (Taylor & Badcock, 1988; Treisman & Souther, 1985; see also Wolfe, 1998, pp. 17–18).…”

Section: Resultsmentioning

confidence: 99%

“…It would thus be meaningful to question whether the existence of a closure is critical, or if an increased number of closures is more effective in identification. As it is conceivable that the numbers of a specific feature embedded in a figure and the degree of completeness of a feature differently affect the efficiency in figural identification (Elder & Zucker, 1993; Taylor & Badcock, 1988; Treisman & Souther, 1985), Experiment 3 was contrived to examine whether or not an increase in the number of closures (more precisely termed, the number of cycles) affected the speed of identification. Here, the term cycle denotes a closed alternating sequence of the original points and lines beginning and ending with the original points.…”

Section: Methodsmentioning

confidence: 99%

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Which is more critical in identification of random figures, endpoints or closures?¹

Kanbe

2009

Jpn Psychol Res

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The present study intended to examine the criticality of the presence of endpoints and its complementary state, the presence of closures, in early figural identification. Three experiments used a same/different judgment task for simultaneously presented pairs of random figures. Rigorous control over the selections of stimulus figures containing closures and endpoints was ensured. Latencies predicted by six explanations of figural identification (i.e. parallel and the presence of endpoint detection; parallel and closure detection; serial, exhaustive and endpoint detection; serial, exhaustive and closure detection; serial, self-terminating and endpoint detection; and serial, self-terminating and closure detection) were evaluated by the obtained patterns of latencies. The experiments persistently indicated that serial, self-terminating feature detections were executed as the means of the identification. Experiments 1 and 2 showed that closures were detected faster than endpoints. Experiment 3 further suggested that multiple closures were detected faster than a single closure.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Which is more critical in identification of random figures, endpoints or closures?¹

Kanbe

2009

Jpn Psychol Res

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“…According to the linear regression analyses, the slopes of all problem types ( b 1 = 49 ms/element figure for ~/Cls, SE = 30 ms; 76 for ~/End, SE = 63; 12 for End/Cls, SE = 12; and 16 for Cls/End, SE = 15) exceeded the so‐called parallel search criterion of less than 10 ms/item (Taylor & Badcock, 1988; Treisman & Souther, 1985) and were significant: all p s < 0.01.…”

Section: Resultsmentioning

confidence: 99%

Role of endpoints and closures in feature search¹

Kanbe¹

2008

Jpn Psychol Res

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The present study intended to examine the role of endpoints and of closures, the two most frequently referred to features, in a feature-search paradigm. Two experiments were conducted with a rigorous stimulus control using random lined figures of different levels of complexity. The experiments gave almost identical results: there was no search asymmetry between the two features, smaller latencies were obtained in the presence of a feature as a target rather than in its absence, and the latencies were smaller for the displays having a background consisting of closures rather than for those having a background of endpoints. The results were more comprehensively explained by the high contrast between an endpoint as a target and closures as a background, rather than the conspicuity of an endpoint as a target. The possibility for closures to group into a homogeneous ground was discussed.

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“…There is a general consensus that in humans, the features of color, size, orientation, and motion are fundamental and significant in the context of pop-out (Wolfe & Horowitz, 2004. The effects of other features such as color change (Theeuwes, 1995;von Mühlenen & Conci, 2016), shape Treisman & Gormican, 1988;Wolfe & Bennett, 1997), or line termination (Julesz & Bergen, 1987;Taylor & Badcock, 1988) are less conclusive. Here we examined whether these four guiding features are specific to humans alone or if they also guide other vertebrates.…”

Section: Discussionmentioning

confidence: 99%

“…Indeed, it is unclear what aspects of shape guide attention in humans. For example, a feature such as a line terminator (Julesz & Bergen, 1987;Taylor & Badcock, 1988) can distinguish between O and Q but will not necessarily guide attention in all other cases. Our findings confirmed that the shape task (which presented the Pac-Man shape) did not trigger the underlying feature search that allows pop-out and parallel search.…”

Section: Color Experimentsmentioning

confidence: 99%

What pops out for you pops out for fish: Four common visual features

et al. 2019

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Visual search is the ability to detect a target of interest against a background of distracting objects. For many animals, performing this task fast and accurately is crucial for survival. Typically, visual-search performance is measured by the time it takes the observer to detect a target against a backdrop of distractors. The efficiency of a visual search depends fundamentally on the features of the target, the distractors, and the interaction between them. Substantial efforts have been devoted to investigating the influence of different visual features on visual-search performance in humans. In particular, it has been demonstrated that color, size, orientation, and motion are efficient visual features to guide attention in humans. However, little is known about which features are efficient and which are not in other vertebrates. Given earlier observations that moving targets elicit popout and parallel search in the archerfish during visualsearch tasks, here we investigate and confirm that all four of these visual features also facilitate efficient search in the archerfish in a manner comparable to humans. In conjunction with results reported for other species, these finding suggest universality in the way visual search is carried out by animals despite very different brain anatomies and living environments.

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Processing feature density in preattentive perception

Cited by 14 publications

References 21 publications

Which is more critical in identification of random figures, endpoints or closures?¹

Which is more critical in identification of random figures, endpoints or closures?¹

Role of endpoints and closures in feature search¹

What pops out for you pops out for fish: Four common visual features

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Processing feature density in preattentive perception

Cited by 14 publications

References 21 publications

Which is more critical in identification of random figures, endpoints or closures?1

Which is more critical in identification of random figures, endpoints or closures?1

Role of endpoints and closures in feature search1

What pops out for you pops out for fish: Four common visual features

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Which is more critical in identification of random figures, endpoints or closures?¹

Which is more critical in identification of random figures, endpoints or closures?¹

Role of endpoints and closures in feature search¹