Literature DB >> 18300187

Detecting objects is easier than categorizing them.

Jeffrey S Bowers1, Keely W Jones.   

Abstract

Two experiments compared performance in an object detection task, in which participants categorized photographs as objects and nonobject textures, and an object categorization task, in which photographs were categorized into basic-level categories. The basic-level categorization task was either easy (e.g., dogs vs. buses) or difficult (e.g., dogs vs. cats). Participants performed similarly in the detection and the easy-categorization tasks, but response times to the difficult-categorization task were slower. This latter finding is difficult to reconcile with the conclusions ofGrill-Spector and Kanwisher (2005) who reported equivalent performance on detection and basic-level categorization tasks and took this as evidence that figure-ground segregation and basic-level categorization are mediated by the same mechanism.

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Year:  2008        PMID: 18300187     DOI: 10.1080/17470210701798290

Source DB:  PubMed          Journal:  Q J Exp Psychol (Hove)        ISSN: 1747-0218            Impact factor:   2.143


  10 in total

1.  The dynamics of categorization: Unraveling rapid categorization.

Authors:  Michael L Mack; Thomas J Palmeri
Journal:  J Exp Psychol Gen       Date:  2015-05-04

2.  Similarity relations in visual search predict rapid visual categorization.

Authors:  Krithika Mohan; S P Arun
Journal:  J Vis       Date:  2012-10-23       Impact factor: 2.240

3.  The timing of visual object categorization.

Authors:  Michael L Mack; Thomas J Palmeri
Journal:  Front Psychol       Date:  2011-07-15

4.  The characteristics and limits of rapid visual categorization.

Authors:  Michèle Fabre-Thorpe
Journal:  Front Psychol       Date:  2011-10-03

5.  Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer.

Authors:  Matin N Ashtiani; Saeed R Kheradpisheh; Timothée Masquelier; Mohammad Ganjtabesh
Journal:  Front Psychol       Date:  2017-07-25

6.  Categorization influences detection: A perceptual advantage for representative exemplars of natural scene categories.

Authors:  Eamon Caddigan; Heeyoung Choo; Li Fei-Fei; Diane M Beck
Journal:  J Vis       Date:  2017-01-01       Impact factor: 2.240

7.  Fragmented ambiguous objects: Stimuli with stable low-level features for object recognition tasks.

Authors:  Cheryl A Olman; Tori Espensen-Sturges; Isaac Muscanto; Julia M Longenecker; Philip C Burton; Andrea N Grant; Scott R Sponheim
Journal:  PLoS One       Date:  2019-04-11       Impact factor: 3.240

8.  Shape detection of Gaborized outline versions of everyday objects.

Authors:  Michaël Sassi; Bart Machilsen; Johan Wagemans
Journal:  Iperception       Date:  2012-10-11

9.  The time-course of visual categorizations: you spot the animal faster than the bird.

Authors:  Marc J-M Macé; Olivier R Joubert; Jean-Luc Nespoulous; Michèle Fabre-Thorpe
Journal:  PLoS One       Date:  2009-06-17       Impact factor: 3.240

10.  Explaining the Timing of Natural Scene Understanding with a Computational Model of Perceptual Categorization.

Authors:  Imri Sofer; Sébastien M Crouzet; Thomas Serre
Journal:  PLoS Comput Biol       Date:  2015-09-03       Impact factor: 4.475

  10 in total

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