This paper addresses the “boundary ownership” problem,
also known as the figure/ground assignment problem.
Estimating boundary ownerships is a key step in perceptual
organization: it allows higher-level processing to be applied
on non-accidental shapes corresponding to figural regions.
Existing methods for estimating the boundary ownerships
for a given set of boundary curves model the probability
distribution function (PDF) of the binary figure/ground
random variables associated with the curves. Instead of
modeling this PDF directly, the proposed method uses the
2.1D model: it models the PDF of the ordinal depths of
the image segments enclosed by the curves. After this PDF
is maximized, the boundary ownership of a curve is determined
according to the ordinal depths of the two image
segments it abuts. This method has two advantages:
first, boundary ownership configurations inconsistent with
every depth ordering (and thus very likely to be incorrect)
are eliminated f...