In previous studies using VR, we found evidence that 3D shape estimation agrees to a superadditivity rule of depth-cue combination, by which adding depth cues leads to greater perceived depth and, in principle, to depth overestimation. Superadditivity can be quantitatively accounted for by a normative theory of cue integration, via adapting a model termed Intrinsic Constraint (IC). As for its qualitative nature, it remains unclear whether superadditivity represents the genuine readout of depth-cue integration, as predicted by IC, or alternatively a byproduct of artificial virtual displays, because they carry flatness cues that can bias depth estimates in a Bayesian fashion, or even just a way for observers to express that a scene “looks deeper” with more depth cues by explicitly inflating their depth judgments. In the present study, we addressed this question by testing whether the IC model’s prediction of superadditivity generalizes to real world settings. We asked participants to judge the perceived 3D shape of cardboard prisms through a matching task. To control for the potential interference of explicit reasoning, we also asked participants to reach-to-grasp the same objects and we analyzed the in-flight grip size throughout the reaching. We designed a novel technique to carefully control binocular and monocular 3D cues independently, allowing to add or remove depth information seamlessly. Even with real objects, participants exhibited a clear superadditivity effect in both tasks. Furthermore, the magnitude of this effect was accurately predicted by the IC model. These results confirm that superadditivity is an inherent feature of depth estimation.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)