Parallel Projections for Stereo Reconstruction

This paper proposes a novel technique to computing geometric information from images captured under parallel projections. Parallel images are desirable for stereo reconstruction because parallel projection significantly reduces foreshortening. As a result, correlation based matching becomes more effective. Since parallel projection cameras are not commonly available, we construct parallel images by rebinning a large sequence of perspective images. Epipolar geometry, depth recovery and projective invariant for both 1D and 2D parallel stereos are studied. From the uncertainty analysis of depth reconstruction, it is shown that parallel stereo is superior to both conventional perspective stereo and the recently developed multiperspective stereo for vision reconstruction, in that uniform reconstruction error is obtained in parallel stereo. Traditional stereo reconstruction techniques, e.g. multi-baseline stereo, can still be applicable to parallel stereo without any modifications because epipolar lines in a parallel stereo are perfectly straight. Experimental results further confirm the performance of our approach.