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Matching two perspective views J. Weng, Narendra Ahuja, and T. S. Huang A computational approach to image matching is
described. It uses multiple attributes associated with each image point to
yield a generally overdetermined system of
constraints, taking into account possible structural discontinuities and
occlusions. In the algorithm implemented, intensity, edgeness,
and cornerness attributes are used in conjunction
with the constraints arising from intraregional smoothness, field continuity
and discontinuity, and occlusions to compute dense displacement fields and
occlusion maps along the pixel grids. The intensity, edgeness,
and cornerness are invariant under rigid motion in
the image plane. In order to cope with large disparities, a multiresolution multigrid
structure is employed. Coarser level edgeness and cornerness measures are obtained by blurring the finer
level measures. The algorithm has been tested on real-world scenes with depth
discontinuities and occlusions. A special case of two-view matching is stereo
matching, where the motion between two images is known. The algorithm can be
easily specialized to perform stereo matching using the epipolar
constraint.
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