Perceptual expertise improves category detection in natural scenes

Reshanne R Reeder, Timo Stein, Marius V Peelen

Research output: Contribution to journalArticle (journal)peer-review

12 Citations (Scopus)
28 Downloads (Pure)


There is much debate about how detection, categorization, and within-category identification relate to one another during object recognition. Whether these tasks rely on partially shared perceptual mechanisms may be determined by testing whether training on one of these tasks facilitates performance on another. In the present study we asked whether expertise in discriminating objects improves the detection of these objects in naturalistic scenes. Self-proclaimed car experts (N = 34) performed a car discrimination task to establish their level of expertise, followed by a visual search task where they were asked to detect cars and people in hundreds of photographs of natural scenes. Results revealed that expertise in discriminating cars was strongly correlated with car detection accuracy. This effect was specific to objects of expertise, as there was no influence of car expertise on person detection. These results indicate a close link between object discrimination and object detection performance, which we interpret as reflecting partially shared perceptual mechanisms and neural representations underlying these tasks: the increased sensitivity of the visual system for objects of expertise - as a result of extensive discrimination training - may benefit both the discrimination and the detection of these objects. Alternative interpretations are also discussed.

Original languageEnglish
Pages (from-to)172-179
Number of pages8
JournalPsychonomic Bulletin & Review
Issue number1
Early online date24 Jun 2015
Publication statusPublished - 1 Feb 2016


  • Adult
  • Automobiles
  • Humans
  • Middle Aged
  • Professional Competence
  • Recognition, Psychology/physiology
  • Visual Perception/physiology
  • Discrimination
  • Visual search
  • Within-category identification
  • Object recognition


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