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R. Carmi, L. Itti, Visual Causes versus Correlates of Attentional Selection in Dynamic Scenes, Vision Research, Vol. 46, No. 26, pp. 4333-4345, Dec 2006. [2005 impact factor: 2.027] (Cited by 233)
Abstract: What are the visual causes, rather than mere correlates, of attentional selection and how do they compare to each other during natural vision? To address these questions, we first strung together semantically unrelated dynamic scenes into MTV-style video clips, and performed eye tracking experiments with human observers. We then quantified predictions of saccade target selection based on 7 bottom-up models, including intensity variance, orientation contrast, intensity contrast, color contrast, flicker contrast, motion contrast, and integrated saliency. On average, all tested models predicted saccade target selection well above chance. Dynamic models were particularly predictive of a subset of saccades that were initiated immediately after scene onsets, and led to minimal interobserver variability. In comparison, static models showed mixed results in these circumstances, with intensity variance and orientation contrast achieving particularly weak prediction accuracy (lower than their own average, and approximately 4 times lower than dynamic models). These results indicate that dynamic visual cues play a dominant causal role in attracting attention. In comparison, some static visual correlates of attentional selection play a weaker causal role, while other static correlates are not causal at all, and may instead reflect top-down causes.
Themes: Model of Bottom-Up Saliency-Based Visual Attention, Scene Understanding, Human Eye-Tracking Research
Copyright © 2000-2007 by the University of Southern California, iLab and Prof. Laurent Itti.
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