Figure 9.

Schematic diagram of the generative process assumed by the estimator used in the model. The estimator assumes that figures are drawn from one of two categories – isotropic figures (e.g. circles) or figures with a distribution of random aspect ratios. The figure seen at any particular instance is randomly drawn from one of the two sets with probabilities p_isotropic and 1−p_isotropic. If it is drawn from the random ensemble, its aspect ratio is presumed to be drawn from the appropriate probability distribution. The likelihood function for slant from the retinal shape information is an additive mixture of likelihood functions computed for each of the two sets of figures, weighted by the probability that a figure is drawn form each set. While the peak of the likelihood function is roughly coincident with the isotropic interpretation of the figure, the possibility that the figure is drawn from the random set gives the likelihood function long tails. The likelihood function for the combined cues (obtained by multiplying the two likelihood functions for slant from disparity and slant from retinal shape) is “pulled” toward the isotropic interpretation if the disparities are roughly consistent with the slant suggested by the isotropic interpretation, but is pulled less and less toward that interpretation the larger the conflict between the two. Similar likelihood functions can be derived for the shape of the figure. These can drive adaptive changes in the internal model (e.g. of the assumed mixture proportion p_isotropic).