Non-Bayesian Contour Synthesis

Recent research has witnessed an explosive increase in models that treat percepts as optimal probabilistic inference. The ubiquity of partial camouflage and occlusion in natural scenes, and the demonstrated capacity of the visual system to synthesize coherent contours and surfaces from fragmented image data, has inspired numerous attempts to model visual interpolation processes as rational inference. Here, we report striking new forms of visual interpolation that generate highly improbable percepts. We present motion displays depicting simple occlusion sequences that elicit vivid percepts of illusory contours (ICs) in displays for which they play no necessary explanatory role. These ICs define a second, redundant occluding surface, even though all of the image data can be fully explained by an occluding surface that is clearly visible. The formation of ICs in these images therefore entails an extraordinarily improbable co-occurrence of two occluding surfaces that arise from the same local occlusion events. The perceived strength of the ICs depends on simple low-level image properties, which suggests that they emerge as the outputs of mechanisms that automatically synthesize contours from the pattern of occlusion and disocclusion of local contour segments. These percepts challenge attempts to model visual interpolation as a form of rational inference and suggest the need to consider a broader space of computational problems and/or implementation level constraints to understand their genesis.