Perceptual Organization of Occluding Contours
Generated By Opaque Surfaces
Xerox Palo Alto Research Center
This paper offers computational theory and an algorithmic framework for
perceptual organization of image contours arising from static occluding
surfaces of constant lightness. We articulate constraints and biases
underlying the inference of such physical events as visible surface overlap and
invisible (modal and amodal) surface boundaries, from ambiguous visual evidence
including visible contrast edges and L-type and T-type junctions. For any
given scene, an energy or cost function is constructed over interpretation
labels for nodes of a sparse graph, or belief net. Annealing-style
optimization permits local cues to propagate smoothly to give rise to a global
solution. We demonstrate that this approach leads to correct interpretations
(in the sense of agreeing with human percepts) of popular simple ``Colorforms''
figures known to induce illusory contours, as well as more difficult figures
where interpretations acknowledging accidental alignment are preferred.
Paper (31M compressed to 2.4M)
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