The intrinsic constraint model for stereo-motion integration
Many visual tasks are carried out by using multiple sources of sensory information to estimate environmental properties. In this work, we present a new model for how the visual system combines disparity and velocity information. We propose that, in a first stage of processing, the best possible estimate of the affine structure is obtained by computing a composite score from the disparity and velocity signals. In a second stage, a maximum likelihood Euclidean interpretation is assigned to the recovered affine structure. Observers were asked to match the perceived amount of depth of two 3D smooth surfaces. Our results are consistent with the predictions of our model (the Intrinsic Constraints model; Domini, Caudek and Tassinari, 2006), both for the PSEs and the variability of observers' judgments. The present findings are also discussed in the framework of another theoretical approach of the depth cue combination process termed Modified Weak Fusion (MWF).