Do target detection and target localization always go together? Extracting information from briefly presented displays

Ann J. Carrigan, Susan G. Wardle, Anina N. Rich

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The human visual system is capable of processing an enormous amount of information in a short time. Although rapid target detection has been explored extensively, less is known about target localization. Here we used natural scenes and explored the relationship between being able to detect a target (present vs. absent) and being able to localize it. Across four presentation durations (~ 33–199 ms), participants viewed scenes taken from two superordinate categories (natural and manmade), each containing exemplars from four basic scene categories. In a two-interval forced choice task, observers were asked to detect a Gabor target inserted in one of the two scenes. This was followed by one of two different localization tasks. Participants were asked either to discriminate whether the target was on the left or the right side of the display or to click on the exact location where they had seen the target. Targets could be detected and localized at our shortest exposure duration (~ 33 ms), with a predictable improvement in performance with increasing exposure duration. We saw some evidence at this shortest duration of detection without localization, but further analyses demonstrated that these trials typically reflected coarse or imprecise localization information, rather than its complete absence. Experiment 2 replicated our main findings while exploring the effect of the level
of openness in the scene. Our results are consistent with the notion that when we are able to extract what objects are present in a scene, we also have information about where each object is, which provides crucial guidance for our goal-directed actions.
Original languageEnglish
Pages (from-to)2685–2699
Number of pages15
JournalAttention, Perception and Psychophysics
Volume81
Issue number8
Early online date19 Jun 2019
DOIs
Publication statusPublished - Nov 2019

Keywords

  • visual perception
  • scene perception
  • object recognition

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