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Low Level Visual Saliency Does Not Predict Change
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Low Level Visual Saliency Does Not Predict Change

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  • 1. Low-level visual saliency does not predict change detection in natural scenes Stirk, A.,& Underwood, G.(2007). Journal of Vision , 7(10), 1-10.
  • 2.
    • change blindness
      • Maintenance failed (Rensink,2002; Simons & Levin, 1997)
    • Coherence field dissolves
      • Rensink (2000)
    • flicker
      • (Rensink ,1997)
      • A–blank–A’–blank-A
  • 3.
    • T op–down and/or B ottom–up
    • -> allocation of attention
    • Wright (2005)
      • change detection in natural scenes could be predicted
      • subjective measures
  • 4.
    • I nfluenced by top–down processes.
    • When semantic information is low, bottom–up processes may have a greater influence on the allocation of attention
  • 5. Methods
    • 2x2 design
    • Salience (high level vs. low level)
    • Scene-schema(consistent vs. inconsistent)
  • 6. Methods
  • 7.  
  • 8. Methods
  • 9.
    • 24 participants
    • 10scenes (19.7 ° × 13.9 ° )
      • 4 changed images
      • 1 original image
      • 80 trials :
      • 4*10 change pairs 、 4*10 no-change pairs
  • 10. Procedure
    • 按鍵回答 “ SAME” or “DIFFERENT”
    • 重複” Flicker” ,直到受試者做出反應
    • 練習: 8 trials ( 有 Feedback )
    • 正式: 80 trials ( 沒有 Feedback )
  • 11.  
  • 12. Results
    • Consistency RT :
      • F(1, 23) = 5.38, p = .03
      • IC 2341.7 < C 2549.2
    • Visual Saliency RT :
      • F(1, 23) = 1.78, p = .20,
      • No main effect
  • 13.  
  • 14.
    • Consistency ACC :
      • F(1, 23) = 15.55, p = .001
      • IC 87.3% > C 78.3%,
    • Visual Saliency ACC :
      • F(1, 23) = 0.26, p = .62,
      • No main effect
  • 15.  
  • 16. Discussion
    • I nconsistent-object detection advantage
    • C ategories of objects guide visual attention
    • Violations to the scene-schema
    • -> stronger perceptual representation
  • 17.
    • c hange detection based solely on the visual properties of a scene and finds that semantic salience.