Visual Causes versus Correlates of Attentional Selection in Dynamic Scenes

Visual Causes versus Correlates of Attentional Selection in Dynamic Scenes. Carmi, R. & Itti, L. Vision Research, 46(26):4333-4345, Dec, 2006.
abstract bibtex

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.

@article{ Carmi_Itti06vr,
  author = {R. Carmi and L. Itti},
  title = {Visual Causes versus Correlates of Attentional Selection in
Dynamic Scenes},
  journal = {Vision Research},
  year = {2006},
  volume = {46},
  number = {26},
  month = {Dec},
  pages = {4333-4345},
  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.},
  file = {http://ilab.usc.edu/publications/doc/Carmi_Itti06vr.pdf},
  type = {bu;sc;eye},
  if = {2005 impact factor: 2.027}
}

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{"_id":{"_str":"5298a1a09eb585cc26000838"},"__v":0,"authorIDs":[],"author_short":["Carmi, R.","Itti, L."],"bibbaseid":"carmi-itti-visualcausesversuscorrelatesofattentionalselectionindynamicscenes-2006","bibdata":{"html":"<div class=\"bibbase_paper\"> \n\n\n<span class=\"bibbase_paper_titleauthoryear\">\n\t<span class=\"bibbase_paper_title\"><a name=\"Carmi_Itti06vr\"> </a>Visual Causes versus Correlates of Attentional Selection in Dynamic Scenes.</span>\n\t<span class=\"bibbase_paper_author\">\nCarmi, R.; and Itti, L.</span>\n\t\n</span>\n\n\n\n<i>Vision Research</i>,\n\n46(26):4333-4345.\n\nDec 2006.\n\n\n\n\n<br class=\"bibbase_paper_content\"/>\n\n<span class=\"bibbase_paper_content\">\n \n \n \n <a href=\"javascript:showBib('Carmi_Itti06vr')\"\n class=\"bibbase link\">\n \n\t\n\t\n\t\n BibTeX\n <i class=\"fa fa-caret-down\"></i></a>\n \n \n  \n <a class=\"bibbase_abstract_link bibbase link\"\n href=\"javascript:showAbstract('Carmi_Itti06vr')\">\n Abstract\n <i class=\"fa fa-caret-down\"></i></a>\n \n \n \n\n \n \n \n</span>\n\n<div class=\"well well-small bibbase\" id=\"bib_Carmi_Itti06vr\"\n style=\"display:none\">\n <pre>@article{ Carmi_Itti06vr,\n author = {R. Carmi and L. Itti},\n title = {Visual Causes versus Correlates of Attentional Selection in\nDynamic Scenes},\n journal = {Vision Research},\n year = {2006},\n volume = {46},\n number = {26},\n month = {Dec},\n pages = {4333-4345},\n abstract = {What are the visual causes, rather than mere correlates, of\nattentional selection and how do they compare to each other during\nnatural vision? To address these questions, we first strung together\nsemantically unrelated dynamic scenes into MTV-style video clips, and\nperformed eye tracking experiments with human observers. We then\nquantified predictions of saccade target selection based on 7\nbottom-up models, including intensity variance, orientation contrast,\nintensity contrast, color contrast, flicker contrast, motion contrast,\nand integrated saliency. On average, all tested models predicted\nsaccade target selection well above chance. Dynamic models were\nparticularly predictive of a subset of saccades that were initiated\nimmediately after scene onsets, and led to minimal interobserver\nvariability. In comparison, static models showed mixed results in\nthese circumstances, with intensity variance and orientation contrast\nachieving particularly weak prediction accuracy (lower than their own\naverage, and approximately 4 times lower than dynamic models). These\nresults indicate that dynamic visual cues play a dominant causal role\nin attracting attention. In comparison, some static visual correlates\nof attentional selection play a weaker causal role, while other static\ncorrelates are not causal at all, and may instead reflect top-down\ncauses.},\n file = {http://ilab.usc.edu/publications/doc/Carmi_Itti06vr.pdf},\n type = {bu;sc;eye},\n if = {2005 impact factor: 2.027}\n}</pre>\n</div>\n\n\n<div class=\"well well-small bibbase\" id=\"abstract_Carmi_Itti06vr\"\n style=\"display:none\">\n 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.\n</div>\n\n\n</div>\n","downloads":0,"bibbaseid":"carmi-itti-visualcausesversuscorrelatesofattentionalselectionindynamicscenes-2006","role":"author","year":"2006","volume":"46","type":"bu;sc;eye","title":"Visual Causes versus Correlates of Attentional Selection in Dynamic Scenes","pages":"4333-4345","number":"26","month":"Dec","key":"Carmi_Itti06vr","journal":"Vision Research","if":"2005 impact factor: 2.027","id":"Carmi_Itti06vr","file":"http://ilab.usc.edu/publications/doc/Carmi_Itti06vr.pdf","bibtype":"article","bibtex":"@article{ Carmi_Itti06vr,\n author = {R. Carmi and L. Itti},\n title = {Visual Causes versus Correlates of Attentional Selection in\nDynamic Scenes},\n journal = {Vision Research},\n year = {2006},\n volume = {46},\n number = {26},\n month = {Dec},\n pages = {4333-4345},\n abstract = {What are the visual causes, rather than mere correlates, of\nattentional selection and how do they compare to each other during\nnatural vision? To address these questions, we first strung together\nsemantically unrelated dynamic scenes into MTV-style video clips, and\nperformed eye tracking experiments with human observers. We then\nquantified predictions of saccade target selection based on 7\nbottom-up models, including intensity variance, orientation contrast,\nintensity contrast, color contrast, flicker contrast, motion contrast,\nand integrated saliency. On average, all tested models predicted\nsaccade target selection well above chance. 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In comparison, some static visual correlates\nof attentional selection play a weaker causal role, while other static\ncorrelates are not causal at all, and may instead reflect top-down\ncauses.},\n file = {http://ilab.usc.edu/publications/doc/Carmi_Itti06vr.pdf},\n type = {bu;sc;eye},\n if = {2005 impact factor: 2.027}\n}","author_short":["Carmi, R.","Itti, L."],"author":["Carmi, R.","Itti, L."],"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. 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