Title
Disparity estimation through Green’s functions of matching equations
Abstract
Binocular disparities arise from positional differences of scene features projected in the two retinae, and constitute the primary sensory cue for stereo vision. Here we introduce a new computational model for disparity estimation, based on the Green’s function of an image matching equation. When filtering a Gabor-function-modulated signal, the considered Green’s function yields a similarly modulated but shifted version of the original signal. Since a Gabor function models the receptive field of a cortical simple cell, the Green’s kernel thus allows the simulation of relative shifts between the cell’s left and right binocular inputs. A measure of the local degree of matching of such shifted inputs can then be introduced which affords disparity estimation in a similar manner to the energy model of the complex cortical cells. We have therefore effectively reformulated, in physiologically plausible terms, an image matching approach to disparity estimation. Our experiments show that the Green’s function method allows the detection of disparities both from random-dot and real-world stereograms.
Year
DOI
Venue
2007
10.1007/s00422-007-0174-0
Biological Cybernetics
Keywords
Field
DocType
Energy Model,Stereo Vision,Simple Cell,Binocular Disparity,Gabor Function
Receptive field,Sensory cue,Kernel (linear algebra),Computer vision,Binocular disparity,Stereopsis,Simple cell,Filter (signal processing),Green S,Artificial intelligence,Mathematics
Journal
Volume
Issue
ISSN
97
4
0340-1200
Citations 
PageRank 
References 
2
0.38
13
Authors
1
Name
Order
Citations
PageRank
José R. A. Torreão15910.18