Literature DB >> 12901715

Is it an animal? Is it a human face? Fast processing in upright and inverted natural scenes.

Guillaume A Rousselet1, Marc J-M Macé, Michèle Fabre-Thorpe.   

Abstract

Object categorization can be extremely fast. But among all objects, human faces might hold a special status that could depend on a specialized module. Visual processing could thus be faster for faces than for any other kind of object. Moreover, because face processing might rely on facial configuration, it could be more disrupted by stimulus inversion. Here we report two experiments that compared the rapid categorization of human faces and animals or animal faces in the context of upright and inverted natural scenes. In Experiment 1, the natural scenes contained human faces and animals in a full range of scales from close-up to far views. In Experiment 2, targets were restricted to close-ups of human faces and animal faces. Both experiments revealed the remarkable object processing efficiency of our visual system and further showed (1) virtually no advantage for faces over animals; (2) very little performance impairment with inversion; and (3) greater sensitivity of faces to inversion. These results are interpreted within the framework of a unique system for object processing in the ventral pathway. In this system, evidence would accumulate very quickly and efficiently to categorize visual objects, without involving a face module or a mental rotation mechanism. It is further suggested that rapid object categorization in natural scenes might not rely on high-level features but rather on features of intermediate complexity.

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Mesh:

Year:  2003        PMID: 12901715     DOI: 10.1167/3.6.5

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  45 in total

1.  A feedforward architecture accounts for rapid categorization.

Authors:  Thomas Serre; Aude Oliva; Tomaso Poggio
Journal:  Proc Natl Acad Sci U S A       Date:  2007-04-02       Impact factor: 11.205

2.  Object detection and basic-level categorization: sometimes you know it is there before you know what it is.

Authors:  Michael L Mack; Isabel Gauthier; Javid Sadr; Thomas J Palmeri
Journal:  Psychon Bull Rev       Date:  2008-02

3.  Quantifying neuronal network dynamics through coarse-grained event trees.

Authors:  Aaditya V Rangan; David Cai; David W McLaughlin
Journal:  Proc Natl Acad Sci U S A       Date:  2008-07-30       Impact factor: 11.205

4.  The dynamics of categorization: Unraveling rapid categorization.

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

5.  The effect of face inversion for neurons inside and outside fMRI-defined face-selective cortical regions.

Authors:  Jessica Taubert; Goedele Van Belle; Wim Vanduffel; Bruno Rossion; Rufin Vogels
Journal:  J Neurophysiol       Date:  2014-12-17       Impact factor: 2.714

Review 6.  Informatics in radiology: what can you see in a single glance and how might this guide visual search in medical images?

Authors:  Trafton Drew; Karla Evans; Melissa L-H Võ; Francine L Jacobson; Jeremy M Wolfe
Journal:  Radiographics       Date:  2012-10-25       Impact factor: 5.333

7.  The perception of two-tone Mooney faces in chimpanzees (Pan troglodytes).

Authors:  Jessica Taubert; Lisa A Parr
Journal:  Cogn Neurosci       Date:  2012       Impact factor: 3.065

8.  The neural dynamics of face detection in the wild revealed by MVPA.

Authors:  Maxime Cauchoix; Gladys Barragan-Jason; Thomas Serre; Emmanuel J Barbeau
Journal:  J Neurosci       Date:  2014-01-15       Impact factor: 6.167

9.  Face or building superiority in peripheral vision reversed by task requirements.

Authors:  Najate Jebara; Delphine Pins; Pascal Despretz; Muriel Boucart
Journal:  Adv Cogn Psychol       Date:  2009-09-08

10.  Visual search efficiency is greater for human faces compared to animal faces.

Authors:  Elizabeth A Simpson; Haley L Husband; Krysten Yee; Alison Fullerton; Krisztina V Jakobsen
Journal:  Exp Psychol       Date:  2014
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