Literature DB >> 17275301

Nonaccidental properties underlie shape recognition in Mammalian and nonmammalian vision.

Brett M Gibson1, Olga F Lazareva, Frédéric Gosselin, Philippe G Schyns, Edward A Wasserman.   

Abstract

An infinite number of 2D patterns on the retina can correspond to a single 3D object. How do visual systems resolve this ill-posed problem and recognize objects from only a few 2D retinal projections in varied exposure conditions? Theories of object recognition rely on the nonaccidental statistics of edge properties, mainly symmetry, collinearity, curvilinearity, and cotermination. These statistics are determined by the image-formation process (i.e., the 2D retinal projection of a 3D object ); their existence under a range of viewpoints enables viewpoint-invariant recognition. An important question in behavioral biology is whether the visual systems of nonmammalian animals have also evolved biases to utilize nonaccidental statistics . Here, we trained humans and pigeons to recognize four shapes. With the Bubbles technique, we determined which stimulus properties both species used to recognize the shapes. Both humans and pigeons used cotermination, the most diagnostic nonaccidental property of real-world objects, despite evidence from a model computer observer that cotermination was not the most diagnostic pictorial information in this particular task. This result reveals that a nonmammalian visual system that is different anatomically from the human visual system is also biased to recognize objects from nonaccidental statistics.

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Year:  2007        PMID: 17275301     DOI: 10.1016/j.cub.2006.12.025

Source DB:  PubMed          Journal:  Curr Biol        ISSN: 0960-9822            Impact factor:   10.834


  23 in total

1.  Visual object categorization in birds and primates: integrating behavioral, neurobiological, and computational evidence within a "general process" framework.

Authors:  Fabian A Soto; Edward A Wasserman
Journal:  Cogn Affect Behav Neurosci       Date:  2012-03       Impact factor: 3.282

2.  Why the leopard got its spots: relating pattern development to ecology in felids.

Authors:  William L Allen; Innes C Cuthill; Nicholas E Scott-Samuel; Roland Baddeley
Journal:  Proc Biol Sci       Date:  2010-10-20       Impact factor: 5.349

3.  View-invariance learning in object recognition by pigeons depends on error-driven associative learning processes.

Authors:  Fabian A Soto; Jeffrey Y M Siow; Edward A Wasserman
Journal:  Vision Res       Date:  2012-04-17       Impact factor: 1.886

4.  Experimental Divergences in the Visual Cognition of Birds and Mammals.

Authors:  Muhammad A J Qadri; Robert G Cook
Journal:  Comp Cogn Behav Rev       Date:  2015

5.  Error-driven learning in visual categorization and object recognition: a common-elements model.

Authors:  Fabian A Soto; Edward A Wasserman
Journal:  Psychol Rev       Date:  2010-04       Impact factor: 8.934

6.  Towards describing scenes by animals: Pigeons' ordinal discrimination of objects varying in depth.

Authors:  Suzanne L Gray; Muhammad A J Qadri; Robert G Cook
Journal:  Learn Behav       Date:  2020-09-23       Impact factor: 1.986

7.  The role of line junctions in object recognition: The case of reading musical notation.

Authors:  Yetta Kwailing Wong; Alan C-N Wong
Journal:  Psychon Bull Rev       Date:  2018-08

8.  Missing the forest for the trees: object-discrimination learning blocks categorization learning.

Authors:  Fabian A Soto; Edward A Wasserman
Journal:  Psychol Sci       Date:  2010-09-03

9.  Pigeons use high spatial frequencies when memorizing pictures.

Authors:  Matthew S Murphy; Daniel I Brooks; Robert G Cook
Journal:  J Exp Psychol Anim Learn Cogn       Date:  2015-04-27       Impact factor: 2.478

10.  The development of newborn object recognition in fast and slow visual worlds.

Authors:  Justin N Wood; Samantha M W Wood
Journal:  Proc Biol Sci       Date:  2016-04-27       Impact factor: 5.349

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