Representation and measurement of stereoscopic volumes
Author(s) -
Ross Goutcher,
Laurie M. Wilcox
Publication year - 2016
Publication title -
journal of vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.126
H-Index - 113
ISSN - 1534-7362
DOI - 10.1167/16.11.16
Subject(s) - stereoscopy , binocular disparity , perception , binocular vision , stereopsis , artificial intelligence , computer vision , computer science , depth perception , mathematics , psychology , neuroscience
Binocular disparity information provides the human visual system with a basis for the compelling perception of both three-dimensional (3D) object shape, and of the 3D space between objects. However, while an extensive body of research exists into the perception of disparity-defined surface shape, relatively little research has been conducted on the associated perception of disparity-defined volume. In this paper, we report three experiments that examine this aspect of binocular vision. Participants were asked to make judgements about the 3D spread, location-in-depth and 3D shape of stereoscopic volumes. Volumes were comprised of random dots with disparities drawn from a uniform distribution, a Gaussian distribution, or a combination of both. These results were compared to two models: one of these made judgements about stereoscopic volumes using information about the distributions of disparities in each stimulus, while the other was limited to only maximum and minimum disparity information. Psychophysical results were best accounted for by the maximum-minimum decision rule model. This suggests that, although binocular vision affords a compelling phenomenal sense of 3D volume, when required to make judgements about such volumes, the visual system’s default strategies make only limited use of available binocular disparity signals
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