title: Cross-matching: a modified cross-correlation underlying threshold energy model and match-based depth perception.
abstract: Three-dimensional visual perception requires correct matching of images projected to the left and right eyes. The matching process is faced with an ambiguity: part of one eye's image can be matched to multiple parts of the other eye's image. This stereo correspondence problem is complicated for random-dot stereograms (RDSs), because dots with an identical appearance produce numerous potential matches. Despite such complexity, human subjects can perceive a coherent depth structure. A coherent solution to the correspondence problem does not exist for anticorrelated RDSs (aRDSs), in which luminance contrast is reversed in one eye. Neurons in the visual cortex reduce disparity selectivity for aRDSs progressively along the visual processing hierarchy. A disparity-energy model followed by threshold nonlinearity (threshold energy model) can account for this reduction, providing a possible mechanism for the neural matching process. However, the essential computation underlying the threshold energy model is not clear. Here, we propose that a nonlinear modification of cross-correlation, which we term "cross-matching," represents the essence of the threshold energy model. We placed half-wave rectification within the cross-correlation of the left-eye and right-eye images. The disparity tuning derived from cross-matching was attenuated for aRDSs. We simulated a psychometric curve as a function of graded anticorrelation (graded mixture of aRDS and normal RDS); this simulated curve reproduced the match-based psychometric function observed in human near/far discrimination. The dot density was 25% for both simulation and observation. We predicted that as the dot density increased, the performance for aRDSs should decrease below chance (i.e., reversed depth), and the level of anticorrelation that nullifies depth perception should also decrease. We suggest that cross-matching serves as a simple computation underlying the match-based disparity signals in stereoscopic depth perception.
authors.affiliation: Laboratory for Cognitive Neuroscience, Center for Information and Neural Networks, Graduate School of Frontier Biosciences, Osaka University Suita, Japan.
authors.forename: Takahiro
authors.initials: T
authors.lastname: Doi
authors.affiliation: Laboratory for Cognitive Neuroscience, Center for Information and Neural Networks, Graduate School of Frontier Biosciences, Osaka University Suita, Japan ; Center for Information and Neural Networks, National Institute of Information and Communications Technology Suita, Japan.
authors.forename: Ichiro
authors.initials: I
authors.lastname: Fujita
keywords: anticorrelated; binocular disparity; correspondence problem; discrimination; nonlinearity; random-dot stereogram; stereo vision