Literature DB >> 25780063

Cube search, revisited.

Xuetao Zhang1, Jie Huang2, Serap Yigit-Elliott3, Ruth Rosenholtz4.   

Abstract

Observers can quickly search among shaded cubes for one lit from a unique direction. However, replace the cubes with similar 2-D patterns that do not appear to have a 3-D shape, and search difficulty increases. These results have challenged models of visual search and attention. We demonstrate that cube search displays differ from those with "equivalent" 2-D search items in terms of the informativeness of fairly low-level image statistics. This informativeness predicts peripheral discriminability of target-present from target-absent patches, which in turn predicts visual search performance, across a wide range of conditions. Comparing model performance on a number of classic search tasks, cube search does not appear unexpectedly easy. Easy cube search, per se, does not provide evidence for preattentive computation of 3-D scene properties. However, search asymmetries derived from rotating and/or flipping the cube search displays cannot be explained by the information in our current set of image statistics. This may merely suggest a need to modify the model's set of 2-D image statistics. Alternatively, it may be difficult cube search that provides evidence for preattentive computation of 3-D scene properties. By attributing 2-D luminance variations to a shaded 3-D shape, 3-D scene understanding may slow search for 2-D features of the target.
© 2015 ARVO.

Entities:  

Keywords:  3-D shape; Feature Integration Theory; Texture Tiling Model; familiarity; image statistics; lighting direction; mongrel; peripheral vision; summary statistics; visual search

Mesh:

Year:  2015        PMID: 25780063      PMCID: PMC4362092          DOI: 10.1167/15.3.9

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


  54 in total

1.  The psychophysics of visual search.

Authors:  J Palmer; P Verghese; M Pavel
Journal:  Vision Res       Date:  2000       Impact factor: 1.886

2.  A saliency map in primary visual cortex.

Authors:  Zhaoping Li
Journal:  Trends Cogn Sci       Date:  2002-01-01       Impact factor: 20.229

3.  How important is lateral masking in visual search?

Authors:  A H Wertheim; I T C Hooge; K Krikke; A Johnson
Journal:  Exp Brain Res       Date:  2005-11-23       Impact factor: 1.972

4.  Crowding with conjunctions of simple features.

Authors:  Endel Põder; Johan Wagemans
Journal:  J Vis       Date:  2007-11-20       Impact factor: 2.240

5.  Spacing affects some but not all visual searches: implications for theories of attention and crowding.

Authors:  Lavanya Reddy; Rufin VanRullen
Journal:  J Vis       Date:  2007-02-02       Impact factor: 2.240

6.  The Psychophysics Toolbox.

Authors:  D H Brainard
Journal:  Spat Vis       Date:  1997

7.  Cortical magnification neutralizes the eccentricity effect in visual search.

Authors:  M Carrasco; K S Frieder
Journal:  Vision Res       Date:  1997-01       Impact factor: 1.886

8.  Separation of low-level and high-level factors in complex tasks: visual search.

Authors:  W S Geisler; K L Chou
Journal:  Psychol Rev       Date:  1995-04       Impact factor: 8.934

9.  A summary statistic representation in peripheral vision explains visual search.

Authors:  Ruth Rosenholtz; Jie Huang; Alvin Raj; Benjamin J Balas; Livia Ilie
Journal:  J Vis       Date:  2012-04-20       Impact factor: 2.240

10.  SUN: A Bayesian framework for saliency using natural statistics.

Authors:  Lingyun Zhang; Matthew H Tong; Tim K Marks; Honghao Shan; Garrison W Cottrell
Journal:  J Vis       Date:  2008-12-16       Impact factor: 2.240

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  5 in total

1.  Image content is more important than Bouma's Law for scene metamers.

Authors:  Thomas Sa Wallis; Christina M Funke; Alexander S Ecker; Leon A Gatys; Felix A Wichmann; Matthias Bethge
Journal:  Elife       Date:  2019-04-30       Impact factor: 8.140

2.  Is apparent instability a guiding feature in visual search?

Authors:  Yung-Hao Yang; Jeremy M Wolfe
Journal:  Vis cogn       Date:  2020-06-16

Review 3.  Guided Search 6.0: An updated model of visual search.

Authors:  Jeremy M Wolfe
Journal:  Psychon Bull Rev       Date:  2021-02-05

4.  Space of preattentive shape features.

Authors:  Liqiang Huang
Journal:  J Vis       Date:  2020-04-09       Impact factor: 2.240

5.  Visual Search in 3D: Effects of Monoscopic and Stereoscopic Cues to Depth on the Validity of Feature Integration Theory and Perceptual Load Theory.

Authors:  Ciara M Greene; John Broughan; Anthony Hanlon; Seán Keane; Sophia Hanrahan; Stephen Kerr; Brendan Rooney
Journal:  Front Psychol       Date:  2021-03-17
  5 in total

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