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Download fileEstimating Object Region from Local Contour Configuration
journal contribution
posted on 2009-01-01, 00:00 authored by Tetsuaki Suzuki, Martial HebertIn this paper, we explore ways to combine boundary
information and region segmentation to estimate regions
corresponding to foreground objects. Boundary
information is used to generate an object likelihood image
which encodes the likelihood that each pixel belongs to a
foreground object. This is done by combining evidence
gathered from a large number of boundary fragments on
training images by exploiting the relation between local
boundary shape and relative location of the corresponding
object region in the image. A region segmentation is used to
generate a likely segmentation that is consistent with the
boundary fragments out of a set of multiple segmentations.
A mutual information criterion is used for selecting a
segmentation from a set of multiple segmentations. Object
likelihood and region segmentation are combined to yield
the final proposed object region(s).