Visual Attention and Change Detection

Ty W. Boyer; Linda B. Smith; Chen Yu; Bennett I. Bertenthal

Visual Attention and Change Detection

Ty W. Boyer, Linda B. Smith, Chen Yu, Bennett I. Bertenthal

Psychology

Indiana University

Research output: Contribution to conference › Presentation

Abstract

Studies suggest that visual attention, guided in part by features’ visual salience, is necessary for change detection. An image processing algorithm was used for measuring the visual salience of the features of scenes, and participants’ ability to detect changes made to high and low salience features was measured with a flicker paradigm while their eye movements were recorded. Changes to high salience features were fixated sooner, for shorter durations, and were detected faster and with higher accuracy than those made to low salience features. The implications of these results for visual attention and change detection research are discussed.

Original language	American English
State	Published - 2011
Event	Proceedings of the 33rd Annual Conference of the Cognitive Science Society - Duration: Jan 1 2011 → …

Conference

Conference	Proceedings of the 33rd Annual Conference of the Cognitive Science Society
Period	01/1/11 → …

Keywords

Change detection
Eye tracking
Visual salience

DC Disciplines

Psychiatry and Psychology
Psychology

Cite this

@conference{3b2c8f7032be4ea9b8961bc9e4a9ce6c,

title = "Visual Attention and Change Detection",

abstract = " Studies suggest that visual attention, guided in part by features{\textquoteright} visual salience, is necessary for change detection. An image processing algorithm was used for measuring the visual salience of the features of scenes, and participants{\textquoteright} ability to detect changes made to high and low salience features was measured with a flicker paradigm while their eye movements were recorded. Changes to high salience features were fixated sooner, for shorter durations, and were detected faster and with higher accuracy than those made to low salience features. The implications of these results for visual attention and change detection research are discussed.",

keywords = "Change detection, Eye tracking, Visual salience",

author = "Boyer, {Ty W.} and Smith, {Linda B.} and Chen Yu and Bertenthal, {Bennett I.}",

note = "Ty W. Boyer, Linda B. Smith, Chen Yu, and Bennett I. Bertenthal. {"}Visual Attention and Change Detection{"} Proceedings of the 33rd Annual Conference of the Cognitive Science Society. Ed. Laura Carlson, Christoph Hoelscher, and Thomas F. Shipley. Austin, TX: , 2011. source:http://mindmodeling.org/cogsci2011/papers/0329/paper0329.pdf; Proceedings of the 33rd Annual Conference of the Cognitive Science Society ; Conference date: 01-01-2011",

year = "2011",

language = "American English",

}

TY - CONF

T1 - Visual Attention and Change Detection

AU - Boyer, Ty W.

AU - Smith, Linda B.

AU - Yu, Chen

AU - Bertenthal, Bennett I.

N1 - Ty W. Boyer, Linda B. Smith, Chen Yu, and Bennett I. Bertenthal. "Visual Attention and Change Detection" Proceedings of the 33rd Annual Conference of the Cognitive Science Society. Ed. Laura Carlson, Christoph Hoelscher, and Thomas F. Shipley. Austin, TX: , 2011. source:http://mindmodeling.org/cogsci2011/papers/0329/paper0329.pdf

PY - 2011

Y1 - 2011

N2 - Studies suggest that visual attention, guided in part by features’ visual salience, is necessary for change detection. An image processing algorithm was used for measuring the visual salience of the features of scenes, and participants’ ability to detect changes made to high and low salience features was measured with a flicker paradigm while their eye movements were recorded. Changes to high salience features were fixated sooner, for shorter durations, and were detected faster and with higher accuracy than those made to low salience features. The implications of these results for visual attention and change detection research are discussed.

AB - Studies suggest that visual attention, guided in part by features’ visual salience, is necessary for change detection. An image processing algorithm was used for measuring the visual salience of the features of scenes, and participants’ ability to detect changes made to high and low salience features was measured with a flicker paradigm while their eye movements were recorded. Changes to high salience features were fixated sooner, for shorter durations, and were detected faster and with higher accuracy than those made to low salience features. The implications of these results for visual attention and change detection research are discussed.

KW - Change detection

KW - Eye tracking

KW - Visual salience

UR - http://mindmodeling.org/cogsci2011/papers/0384/index.html

M3 - Presentation

T2 - Proceedings of the 33rd Annual Conference of the Cognitive Science Society

Y2 - 1 January 2011

ER -

Visual Attention and Change Detection

Abstract

Conference

Keywords

DC Disciplines

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