Abstract
Purpose. We quantified the information provided by the outputs of biologically-plausible mechanisms sensitive to orientation disparity to determine the usefulness of this cue for estimating surface slant. Method. Using a modified disparity energy model tuned to orientation disparity, we computed responses to simulated surfaces textured with random mean-vertical or broadband noise and slanted away from the viewer about the horizontal axis. Based on the responses of our cell population, we estimated the slant of each surface using a Naïve Bayes decoder that compared the mean response levels with expected activity based on distributions for surfaces at a wide range of slants, and we compared this performance to estimates of the separability of different slants using linear discriminant analysis with gradient descent. To verify that the information used in the estimates were based on orientation disparity and not purely local orientation, we repeated the Naïve Bayes analysis using an energy model with monocular input. Results. The Naïve Bayes estimator and the linear discriminant analysis produced similar results with standard deviations ranging from 2–6 degrees, which is within the range of normal acuity for slant from stereo. The estimates from the monocular control were uninformative for the broadband noise textures and produced standard deviations that were more than 4 times larger for the oriented noise textures, indicating that the information was carried by orientation disparity. Conclusion. Given the performance of our model, orientation disparity appears to be a plausible source of information for estimating 3D surface orientation.