Literature DB >> 19883490

Representation of shape in individuals from a culture with minimal exposure to regular, simple artifacts: sensitivity to nonaccidental versus metric properties.

Irving Biederman1, Xiaomin Yue, Jules Davidoff.   

Abstract

Many of the phenomena underlying shape recognition can be derived from the greater sensitivity to nonaccidental properties of an image (e.g., whether a contour is straight or curved), which are invariant to orientation in depth, than to the metric properties of an image (e.g., a contour's degree of curvature), which can vary with orientation. What enables this sensitivity? One explanation is that it derives from people's immersion in a manufactured world in which simple, regular shapes distinguished by nonaccidental properties abound (e.g., a can, a brick), and toddlers are encouraged to play with toy shape sorters. This report provides evidence against this explanation. The Himba, a seminomadic people living in a remote region of northwestern Namibia where there is little exposure to regular, simple artifacts, were virtually identical to Western observers in their greater sensitivity to nonaccidental properties than to metric properties of simple shapes.

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Mesh:

Year:  2009        PMID: 19883490     DOI: 10.1111/j.1467-9280.2009.02465.x

Source DB:  PubMed          Journal:  Psychol Sci        ISSN: 0956-7976


  5 in total

1.  Beyond core knowledge: Natural geometry.

Authors:  Elizabeth Spelke; Sang Ah Lee; Véronique Izard
Journal:  Cogn Sci       Date:  2010-05-01

2.  N170 face specificity and face memory depend on hometown size.

Authors:  Benjamin Balas; Alyson Saville
Journal:  Neuropsychologia       Date:  2015-02-07       Impact factor: 3.139

3.  Infants and toddlers show enlarged visual sensitivity to nonaccidental compared with metric shape changes.

Authors:  Greet Kayaert; Johan Wagemans
Journal:  Iperception       Date:  2010-12-20

4.  Sensitivity to Nonaccidental Configurations of Two-Line Stimuli.

Authors:  Jonas Kubilius; Charlotte Sleurs; Johan Wagemans
Journal:  Iperception       Date:  2017-04-03

5.  Deep Neural Networks as a Computational Model for Human Shape Sensitivity.

Authors:  Jonas Kubilius; Stefania Bracci; Hans P Op de Beeck
Journal:  PLoS Comput Biol       Date:  2016-04-28       Impact factor: 4.475

  5 in total

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