Two-view Matching

Establishing correspondences between images of the same scene is one of the most challenging and critical stcps in motion and scene analysis. Part of the difficulty is due to a wide variety of three-dimension structural discontinuities and occlusions that occur in real world scenes. This paper describes a computational approach to image matching that uses multiple attributes associated with a pixel to yield a generally overdetermined system of constraints, taking into account possible structural discontinuities and occlusions. In the algorithm implemented, intensity, edgeness, and comemess 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 at pixel grids. A multiresolution multigrid structure is employed to deal with large disparities. Coarser level attributes are obtained by blurring the finer level attributes. The algorithms are tested on real world scenes containing depth discontinuities and occlusions. A special case of two-view matching is stereo matching where the motion between two images is known. The general algorithm given here can be easily spccialized to perfonn stereo matching using epipolar line constraint.