Abstract


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Click to download PDF version Click to download BibTeX data Clik to view abstract R. Carmi, L. Itti, Causal Saliency Effects During Natural Vision, In: Proc. ACM Eye Tracking Research and Applications, pp. 11-18, Mar 2006. (Cited by 29)

Abstract: Salient stimuli, such as color or motion contrasts, attract human attention, thus providing a fast heuristic for focusing limited neural resources on behaviorally relevant sensory inputs. Here we address the following questions: What types of saliency attract attention and how do they compare to each other during natural vision? We asked human participants to inspect scene-shuffled video clips, tracked their instantaneous eye-position, and quantified how well a battery of computational saliency models predicted overt attentional selections (saccades). Saliency effects were measured as a function of total viewing time, proximity to abrupt scene transitions (jump cuts), and inter-participant consistency. All saliency models predicted overall attentional selection well above chance, with dynamic models being equally predictive to each other, and up to 3.6 times more predictive than static models. Among static models, color contrast was up to 2.1 more predictive than intensity variance. These results establish the superiority of dynamic over static saliency in attracting attention during natural vision, while also indicating a special role for color. We propose that purely bottom-up or purely top-down saccades are rare in real world environments. Instead, attentional selections are typically determined by dynamic interactions between bottom-up and top-down influences, which are sometimes cooperative and sometimes competitive.

Note: Recipient of Best Paper Award

Themes: Computational Modeling, Model of Bottom-Up Saliency-Based Visual Attention, Model of Top-Down Attentional Modulation, Human Eye-Tracking Research, Human Psychophysics

 

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