Quantifying peripheral and foveal perceived differences in natural image patches to predict visual search performance

Anna E. Hughes, Rosy V. Southwell, Iain Gilchrist, Tolhurst David J.

Research output: Contribution to journalArticle (Academic Journal)peer-review

3 Citations (Scopus)
321 Downloads (Pure)

Abstract

Duncan & Humphreys (1989) identified two key factors that affected performance in a visual search task for a target amongst distractors. The first was the similarity of the target to distractors (TD) and the second was the similarity of distractors to each other (DD). Here we investigate if it is the perceived similarity in foveal or peripheral vision that determines performance. We studied search using stimuli made from patches cut from coloured images of natural objects; differences between targets and their modified distractors were estimated using a ratings task peripherally and foveally. We used search conditions where the targets and distractors were easy to distinguish both foveally and peripherally (“high” stimuli), where they were difficult to distinguish both foveally and peripherally (“low”), and where they were easy to distinguish foveally but difficult to distinguish peripherally (“metamers”). In the critical metameric condition, search slopes (change of search time with number of distractors) were similar to the “low” condition, indicating a key role for peripheral information in visual search, as both conditions have low perceived similarity peripherally. Furthermore, in all conditions, search slope was well described quantitatively from peripheral TD and DD, but not foveal. However, some features of search, such as error rates, do indicate roles for foveal vision too.
Original languageEnglish
Article number18
Number of pages17
JournalJournal of Vision
Volume16
Issue number10
Early online date1 Aug 2016
DOIs
Publication statusPublished - Aug 2016

Structured keywords

  • Cognitive Science
  • Visual Perception

Keywords

  • visual search
  • peripheral vision
  • natural images
  • search slope

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