Direct extraction of curvature-based metric shape from stereo by view-modulated receptive fields

Abstract

Any computation of metric surface structure from horizontal disparities depends on the viewing geometry, and analysing this dependence allows us to narrow down the choice of viable schemes. For example, all depth-based or slant-based schemes (i.e. nearly all existing models) are found to be unrealistically sensitive to natural errors in vergence. Curvature-based schemes avoid these problems and require only moderate, more robust view-dependent corrections to yield local object shape, without any depth coding. This fits the fact that humans are strikingly insensitive to global depth but accurate in discriminating surface curvature. The latter also excludes coding only affine structure. In view of new adaptation results, our goal becomes to directly extract retinotopic fields of metric surface curvatures (i.e. avoiding intermediate disparity curvature). To find a robust neural realisation, we combine new exact analysis with basic neural and psychophysical constraints. Systematic, step-by-step 'design' leads to neural operators which employ a novel family of 'dynamic' receptive fields (RFs), tuned to specific (bi-)local disparity structure. The required RF family is dictated by the non-Euclidean geometry that we identify as inherent in cyclopean vision. The dynamic RF-subfield patterns are controlled via gain modulation by binocular vergence and version, and parameterised by a cell-specific tuning to slant. Our full characterisation of the neural operators invites a range of new neurophysiological tests. Regarding shape perception, the model inverts widely accepted interpretations: It predicts the various types of errors that have often been mistaken for evidence against metric shape extraction.

Stereo-Curvature Aftereffect Is Due to More Than Shape Curvature Adaptation

“…These results supported stereo-curvature adaptation at the percept level. In a more recent study (Noest, Van Ee, & Van Den Berg, 2006), a significant sCAE was found in the context of moving fixation along Lissajous paths, suggesting a dominant adaptation to shape curvature.…”

“…The last type of adaptation stimuli were static curved surfaces with moving fixation, which was thought to be able to smear possible adaptation to disparity and its gradient. Observers in Noest et al (2006) inspected spherical or cylindrical adaptation stimuli consisting of a moderately sparse, semi-random array of wire-frame cubes centered on formal surfaces. The difference in aftereffect magnitude between static fixation and moving fixation along the Lissajous trajectory was used to examine whether adaptation to disparity or shape curvature occurred.…”

“…Thus, the previous studies we reviewed were unable to determine the processing levels of adaptation underlying sCAE because of their inappropriate adaptation stimuli for isolating disparity adaptation and shape-curvature adaptation. Only the dominant contribution of shape-curvature adaptation could be determined from the study of Noest et al (2006).…”

“…So far, the related studies have not drawn definite conclusions on the dependency. Noest et al (2006) claimed that shape curvature was dominantly coded in a retinotopic frame because no significantly different sCAE was found when adaptation and test stimuli were viewed between the same and opposite headcentric hemispheres. The adaptation stimuli were inspected with either static or moving fixation.…”

Cyclopean geometry of binocular vision

“…This differential approach can be extended in several ways; for example, it is possible to recover measures of surface shape, from the second-order structure of the disparity field [28,29,30]. These models are essentially local, and require that the disparity field is (or can be made) continuous.…”