Literature DB >> 7617422

Mechanisms of stereoscopic processing: stereoattention and surface perception in depth reconstruction.

C W Tyler1, L L Kontsevich.   

Abstract

Consideration of the range of phenomena from studies of human stereopsis suggests that a five-stage model is required to provide a complete account of the processes involved, within which any stereoattention mechanism must operate. The information from the disparity field of the optical projections to the two eyes (stage 1) goes to a set of parallel Keplerian arrays of disparity detectors, each array selective for a different spatiotemporal property of the visual images (stage 2). Global interactions produce a cyclopean depth image that is cleaned of the spurious ghost images in the Keplerian arrays (stage 3) and that may then be processed for its (hypercyclopean) from elements (stage 4). Finally, there must be a stage of integration of the stereoscopic depth cues with monocular and kinesthetic depth cues to form the overall map of perceived distance (stage 5). The fact that multiple cyclopean surfaces may be perceived as transparent implies that the stereoscopic system is not limited by a singular-surface constraint. However, it is unclear whether multiple surfaces can be seen simultaneously or whether only one surface is seen at a time by a selective-attention process, with the others perceived as a purely inchoate (qualitative) depth impression. New experiments on cueing of ambiguous stereocorrugations by singular flat planes suggest that selective stereoattention is a powerful mechanism. In fact, the results show that attention can be focused not just in horopteral planes but in a variety of depth configurations. Moreover, this attention focus may act as a tracking mechanism to allow perception of smooth cyclopean stereomotion, which has a frequency response up to approximately 5 Hz (in contrast to the approximately 15 Hz limit for detecting planar disparity shifts as jerky appearance and disappearance effects). Finally, the spatial limits of stereosurface reconstruction are explored with cyclopean targets to show some interesting asymmetries of the surface-wrapping process that may represent object-oriented constraints on depth reconstruction.

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Year:  1995        PMID: 7617422     DOI: 10.1068/p240127

Source DB:  PubMed          Journal:  Perception        ISSN: 0301-0066            Impact factor:   1.490


  14 in total

1.  Binocular fusion and invariant category learning due to predictive remapping during scanning of a depthful scene with eye movements.

Authors:  Stephen Grossberg; Karthik Srinivasan; Arash Yazdanbakhsh
Journal:  Front Psychol       Date:  2015-01-14

Review 2.  Cortical and subcortical predictive dynamics and learning during perception, cognition, emotion and action.

Authors:  Stephen Grossberg
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2009-05-12       Impact factor: 6.237

3.  Where's Waldo? How perceptual, cognitive, and emotional brain processes cooperate during learning to categorize and find desired objects in a cluttered scene.

Authors:  Hung-Cheng Chang; Stephen Grossberg; Yongqiang Cao
Journal:  Front Integr Neurosci       Date:  2014-06-17

4.  Neural dynamics of object-based multifocal visual spatial attention and priming: object cueing, useful-field-of-view, and crowding.

Authors:  Nicholas C Foley; Stephen Grossberg; Ennio Mingolla
Journal:  Cogn Psychol       Date:  2012-03-14       Impact factor: 3.468

5.  Recurrent connectivity can account for the dynamics of disparity processing in V1.

Authors:  Jason M Samonds; Brian R Potetz; Christopher W Tyler; Tai Sing Lee
Journal:  J Neurosci       Date:  2013-02-13       Impact factor: 6.167

6.  Desirability, availability, credit assignment, category learning, and attention: Cognitive-emotional and working memory dynamics of orbitofrontal, ventrolateral, and dorsolateral prefrontal cortices.

Authors:  Stephen Grossberg
Journal:  Brain Neurosci Adv       Date:  2018-05-08

7.  On Stereoscopic Art.

Authors:  Nicholas J Wade
Journal:  Iperception       Date:  2021-05-27

8.  Ideal Binocular Disparity Detectors Learned Using Independent Subspace Analysis on Binocular Natural Image Pairs.

Authors:  David W Hunter; Paul B Hibbard
Journal:  PLoS One       Date:  2016-03-16       Impact factor: 3.240

9.  Binocular Depth Judgments on Smoothly Curved Surfaces.

Authors:  Rebecca L Hornsey; Paul B Hibbard; Peter Scarfe
Journal:  PLoS One       Date:  2016-11-08       Impact factor: 3.240

10.  How the venetian blind percept emerges from the laminar cortical dynamics of 3D vision.

Authors:  Yongqiang Cao; Stephen Grossberg
Journal:  Front Psychol       Date:  2014-08-05
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