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Methods for Presenting Real-world Objects Under Controlled Laboratory Conditions
06:54

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Published on: June 21, 2019

Visual search for arbitrary objects in real scenes.

Jeremy M Wolfe1, George A Alvarez, Ruth Rosenholtz

  • 1Departments of Ophthalmology and Radiology, Harvard Medical School, Boston, MA, USA. wolfe@search.bwh.harvard.edu

Attention, Perception & Psychophysics
|June 15, 2011
PubMed
Summary
This summary is machine-generated.

Visual search in real scenes is highly efficient. Scene context and familiarity guide attention, significantly reducing the number of items to search through, making target identification faster.

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Area of Science:

  • Cognitive Psychology
  • Visual Perception
  • Human-Computer Interaction

Background:

  • Visual search efficiency is typically measured by reaction time (RT) × Set Size functions.
  • Defining 'set size' in complex, real-world scenes presents a challenge compared to simple arrays of distractors.

Purpose of the Study:

  • To investigate the efficiency of visual search within naturalistic indoor scenes.
  • To explore how scene context and familiarity influence search performance.
  • To determine if visual search in scenes is more efficient than in non-scene settings.

Main Methods:

  • Hand-labeled 100 indoor scenes, using the number of labeled regions as a proxy for set size.
  • Conducted experiments where observers searched for named objects within these scenes.
  • Manipulated factors such as scene familiarity and target repetition to assess their impact on search efficiency.

Main Results:

  • Visual search in scenes was found to be highly efficient, with an approximate search rate of ~5 ms/item when using labeled regions as set size.
  • Even after controlling for guessing strategies, search slopes remained shallow (~15 ms/item), significantly more efficient than search in non-scene settings (~40 ms/item).
  • Scene familiarity had a modest effect, while repeating target items within a scene led to substantial reaction time improvements (>500 ms).

Conclusions:

  • Visual search in real scenes is remarkably efficient due to scene-specific attentional guidance mechanisms.
  • These mechanisms effectively reduce the 'functional set size' by prioritizing relevant regions within the scene.
  • Familiarity with the scene and repeated exposure to targets further enhance search performance, highlighting the adaptive nature of visual attention.