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Fast and Conspicuous? Quantifying Salience With the Theory of Visual Attention.

Krüger A, Tünnermann J, Scharlau I - Adv Cogn Psychol (2016)

Bottom Line: Only a few studies systematically related salience effects to a common salience measure, and they are partly outdated in the light of new findings on the time course of salience effects.With this procedure, TVA becomes applicable to a broad range of salience-related stimulus material.A 4th experiment substantiates its applicability to the luminance dimension.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Arts and Humanities, Paderborn University.

ABSTRACT
Particular differences between an object and its surrounding cause salience, guide attention, and improve performance in various tasks. While much research has been dedicated to identifying which feature dimensions contribute to salience, much less regard has been paid to the quantitative strength of the salience caused by feature differences. Only a few studies systematically related salience effects to a common salience measure, and they are partly outdated in the light of new findings on the time course of salience effects. We propose Bundesen's Theory of Visual Attention (TVA) as a theoretical basis for measuring salience and introduce an empirical and modeling approach to link this theory to data retrieved from temporal-order judgments. With this procedure, TVA becomes applicable to a broad range of salience-related stimulus material. Three experiments with orientation pop-out displays demonstrate the feasibility of the method. A 4th experiment substantiates its applicability to the luminance dimension.

No MeSH data available.


Related in: MedlinePlus

Estimated processing rates (υ) for Experiment 4. The processing rates ofthe high-salience condition (υhp = rate for the highlysalient probe; υhr = rate for the reference in thehigh-salient probe displays) are shown in blue, those of thelow-salience condition (υlp = rate for the lowly salientprobe; υlr = rate for the reference in the low-salient probedisplays) in red. The darker distributions belong to the probe stimulusand the lighter distributions belong to the reference stimulus.
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Figure 18: Estimated processing rates (υ) for Experiment 4. The processing rates ofthe high-salience condition (υhp = rate for the highlysalient probe; υhr = rate for the reference in thehigh-salient probe displays) are shown in blue, those of thelow-salience condition (υlp = rate for the lowly salientprobe; υlr = rate for the reference in the low-salient probedisplays) in red. The darker distributions belong to the probe stimulusand the lighter distributions belong to the reference stimulus.

Mentions: Figure 18 depicts the processing rates.This figure shows that the difference between the high- and low-saliencecondition lies mainly in the processing of the non-salient reference stimulus:High- and low-salience probes were processed nearly equally fast with a rate ofυhp = 18.7 and υlp = 18.3. The processingspeed of the reference stimulus, however, varied strongly with condition, with arate of υhr = 13.3 in the high-salience and one ofυlr = 17.1 in the low-salience condition. This is importantfor the theoretical explanation (see below).


Fast and Conspicuous? Quantifying Salience With the Theory of Visual Attention.

Krüger A, Tünnermann J, Scharlau I - Adv Cogn Psychol (2016)

Estimated processing rates (υ) for Experiment 4. The processing rates ofthe high-salience condition (υhp = rate for the highlysalient probe; υhr = rate for the reference in thehigh-salient probe displays) are shown in blue, those of thelow-salience condition (υlp = rate for the lowly salientprobe; υlr = rate for the reference in the low-salient probedisplays) in red. The darker distributions belong to the probe stimulusand the lighter distributions belong to the reference stimulus.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4862317&req=5

Figure 18: Estimated processing rates (υ) for Experiment 4. The processing rates ofthe high-salience condition (υhp = rate for the highlysalient probe; υhr = rate for the reference in thehigh-salient probe displays) are shown in blue, those of thelow-salience condition (υlp = rate for the lowly salientprobe; υlr = rate for the reference in the low-salient probedisplays) in red. The darker distributions belong to the probe stimulusand the lighter distributions belong to the reference stimulus.
Mentions: Figure 18 depicts the processing rates.This figure shows that the difference between the high- and low-saliencecondition lies mainly in the processing of the non-salient reference stimulus:High- and low-salience probes were processed nearly equally fast with a rate ofυhp = 18.7 and υlp = 18.3. The processingspeed of the reference stimulus, however, varied strongly with condition, with arate of υhr = 13.3 in the high-salience and one ofυlr = 17.1 in the low-salience condition. This is importantfor the theoretical explanation (see below).

Bottom Line: Only a few studies systematically related salience effects to a common salience measure, and they are partly outdated in the light of new findings on the time course of salience effects.With this procedure, TVA becomes applicable to a broad range of salience-related stimulus material.A 4th experiment substantiates its applicability to the luminance dimension.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Arts and Humanities, Paderborn University.

ABSTRACT
Particular differences between an object and its surrounding cause salience, guide attention, and improve performance in various tasks. While much research has been dedicated to identifying which feature dimensions contribute to salience, much less regard has been paid to the quantitative strength of the salience caused by feature differences. Only a few studies systematically related salience effects to a common salience measure, and they are partly outdated in the light of new findings on the time course of salience effects. We propose Bundesen's Theory of Visual Attention (TVA) as a theoretical basis for measuring salience and introduce an empirical and modeling approach to link this theory to data retrieved from temporal-order judgments. With this procedure, TVA becomes applicable to a broad range of salience-related stimulus material. Three experiments with orientation pop-out displays demonstrate the feasibility of the method. A 4th experiment substantiates its applicability to the luminance dimension.

No MeSH data available.


Related in: MedlinePlus