Visual Attention and Change Detection
Proceedings of the 33rd Annual Conference of the Cognitive Science Society
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.
Boyer, Ty W., Thomas G. Smith, Chen Yu, Bennett I. Bertenthal.
"Visual Attention and Change Detection."
Proceedings of the 33rd Annual Conference of the Cognitive Science Society Boston, Massachusetts.