A Bayesian model of stereopsis depth and motion direction discrimination |
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Authors: | J C A Read |
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Institution: | (1) University Laboratory of Physiology, Parks Road, Oxford OX1 3PT, UK, GB |
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Abstract: | The extraction of stereoscopic depth from retinal disparity, and motion direction from two-frame kinematograms, requires
the solution of a correspondence problem. In previous psychophysical work Read and Eagle (2000) Vision Res 40: 3345–3358],
we compared the performance of the human stereopsis and motion systems with correlated and anti-correlated stimuli. We found
that, although the two systems performed similarly for narrow-band stimuli, broad-band anti-correlated kinematograms produced
a strong perception of reversed motion, whereas the stereograms appeared merely rivalrous. I now model these psychophysical
data with a computational model of the correspondence problem based on the known properties of visual cortical cells. Noisy
retinal images are filtered through a set of Fourier channels tuned to different spatial frequencies and orientations. Within
each channel, a Bayesian analysis incorporating a prior preference for small disparities is used to assess the probability
of each possible match. Finally, information from the different channels is combined to arrive at a judgement of stimulus
disparity. Each model system – stereopsis and motion – has two free parameters: the amount of noise they are subject to, and
the strength of their preference for small disparities. By adjusting these parameters independently for each system, qualitative
matches are produced to psychophysical data, for both correlated and anti-correlated stimuli, across a range of spatial frequency
and orientation bandwidths. The motion model is found to require much higher noise levels and a weaker preference for small
disparities. This makes the motion model more tolerant of poor-quality reverse-direction false matches encountered with anti-correlated
stimuli, matching the strong perception of reversed motion that humans experience with these stimuli. In contrast, the lower
noise level and tighter prior preference used with the stereopsis model means that it performs close to chance with anti-correlated
stimuli, in accordance with human psychophysics. Thus, the key features of the experimental data can be reproduced assuming
that the motion system experiences more effective noise than the stereoscopy system and imposes a less stringent preference
for small disparities.
Received: 2 March 2001 / Accepted in revised form: 5 July 2001 |
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