Literature DB >> 10927118

Seeing circles: what limits shape perception?

D M Levi1, S A Klein.   

Abstract

Humans are remarkably adept at judging shapes and discriminating forms. Forms and shapes are initially sampled by discrete localized visual filters (or receptive fields) in 'early' stages of visual processing. However, more complex higher level filters which integrate or pool information from many local filters may be needed to discern shapes. In order to understand the mechanisms that limit shape perception we asked observers to detect distortions in the shape of briefly presented circles constructed out of samples (Gabor patches, which are well matched to the early visual filters), and varied the radius of the circle, and the number and orientation of the samples. Our results show that shape perception is determined by two factors: the primary determinant is the separation between the samples; however, the orientation of the samples can modulate performance. At small separations, performance is best when the samples are aligned with the global shape, poorer when they are orthogonal, and intermediate when they are all horizontal or vertical. At larger separations these contextual differences disappear; however at all separations, performance is reduced when the orientations of the samples are mixed (i.e. each sample is randomly either aligned or orthogonal, or randomly either horizontal or vertical.). These results suggest an important role for sample separation in shape perception for sampled shapes and suggest that the mechanisms involved in feature binding may modulate the responses of the mechanisms underlying shape perception.

Entities:  

Mesh:

Year:  2000        PMID: 10927118     DOI: 10.1016/s0042-6989(00)00092-4

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  8 in total

1.  Paradoxical psychometric functions ("swan functions") are explained by dilution masking in four stimulus dimensions.

Authors:  Daniel H Baker; Tim S Meese; Mark A Georgeson
Journal:  Iperception       Date:  2013-01-02

2.  A common rule for integration and suppression of luminance contrast across eyes, space, time, and pattern.

Authors:  Tim S Meese; Daniel H Baker
Journal:  Iperception       Date:  2013-01-02

3.  Bayesian integration of position and orientation cues in perception of biological and non-biological forms.

Authors:  Steven M Thurman; Hongjing Lu
Journal:  Front Hum Neurosci       Date:  2014-02-24       Impact factor: 3.169

4.  Curvature Blindness Illusion.

Authors:  Kohske Takahashi
Journal:  Iperception       Date:  2017-11-24

5.  Shape representation modulating the effect of motion on visual search performance.

Authors:  Lindong Yang; Ruifeng Yu; Xuelian Lin; Na Liu
Journal:  Sci Rep       Date:  2017-11-02       Impact factor: 4.379

6.  Set-size effects for sampled shapes: experiments and model.

Authors:  Christian Kempgens; Gunter Loffler; Harry S Orbach
Journal:  Front Comput Neurosci       Date:  2013-05-28       Impact factor: 2.380

7.  Detecting shapes in noise: tuning characteristics of global shape mechanisms.

Authors:  Gunnar Schmidtmann; Gael E Gordon; David M Bennett; Gunter Loffler
Journal:  Front Comput Neurosci       Date:  2013-05-16       Impact factor: 2.380

8.  Responses in early visual areas to contour integration are context dependent.

Authors:  Cheng Qiu; Philip C Burton; Daniel Kersten; Cheryl A Olman
Journal:  J Vis       Date:  2016-06-01       Impact factor: 2.240

  8 in total

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