Physiological Computation of Binocular Disparity
Ning Qian and Yudong Zhu, Vision Research, 1997, 37:1811-1827.
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Abstract
We previously proposed a physiologically realistic model for
stereo vision based on the quantitative binocular receptive field
profiles mapped by Freeman and coworkers. Here we present several new
results about the model that shed light on the physiological processes
involved in disparity computation. First, we show that our model can
be extended to a much more general class of receptive field profiles
than the commonly used Gabor functions. Second, we demonstrate that
there is, however, an advantage of using the Gabor filters: Similar to
our perception, the stereo algorithm with the Gabor filters has a
small bias towards zero disparity. Third, we prove that the complex
cells as described by Freeman et al. compute disparity by effectively
summing up two related cross products between the band-pass filtered
left and right retinal image patches. Fourth, we demonstrate that as
few as two complex cells at each spatial location are sufficient for a
reasonable estimation of binocular disparity. Fifth, we find that our
model can be significantly improved by considering the fact that
complex cell receptive fields are on average larger than those of
simple cells. This fact is incorporated into the model by averaging
over several quadrature pairs of simple cells with nearby and
overlapping receptive fields to construct a model complex cell. The
disparity tuning curve of the resulting complex cell is much more
reliable than that constructed from a single quadrature pair of
simple cells used previously, and the computed disparity maps for
random dot stereograms with the new algorithm are very similar to
human perception, with sharp transitions at disparity boundaries.
Finally, we show that our algorithm works equally well with either of
the two well-known receptive field models in the literature.
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