How distinct sources of nuisance variability in natural images and scenes limit human stereopsis

Johannes Burge

Abstract:

Stimulus variability—a form of nuisance variability—is a primary source of perceptual
uncertainty in everyday natural tasks. How do different properties of natural images
and scenes contribute to this uncertainty? Using binocular disparity as a model system,
we report a systematic investigation of how various forms of natural stimulus variability
impact performance in a stereo-depth discrimination task. With stimuli sampled from a
stereo-image database of real-world scenes having pixel-by-pixel ground-truth distance
data, three human observers completed two closely related double-pass psychophysical
experiments. In the two experiments, each human observer responded twice to ten thousand
unique trials, in which twenty thousand unique stimuli were presented. New analytical
methods reveal, from this data, the specific and nearly dissociable effects of two distinct
sources of natural stimulus variability—variation in luminance-contrast patterns and
variation in local-depth structure—on discrimination performance, as well as the relative
importance of stimulus-driven-variability and internal-noise in determining performance
limits. Between-observer analyses show that both stimulus-driven sources of uncertainty
are responsible for a large proportion of total variance, have strikingly similar effects on
different people, and—surprisingly—make stimulus-by-stimulus responses more predictable
(not less). The consistency across observers raises the intriguing prospect that
image-computable models can make reasonably accurate performance predictions in
natural viewing. Overall, the findings provide a rich picture of stimulus factors that contribute
to human perceptual performance in natural scenes. The approach should have
broad application to other animal models and other sensory-perceptual tasks with natural
or naturalistic stimuli.