## TR#494: Large Occlusion Stereo

### Aaron F. Bobick and Stephen S. Intille

To appear in: Int'l Journal of Computer Vision
A method for solving the stereo matching problem in
the presence of large occlusion is presented. A data structure ---
the * disparity space image * --- is defined to facilitate
the description of the effects of occlusion on the stereo matching
process and in particular on dynamic programming (DP) solutions that
find matches and occlusions simultaneously. We significantly improve
upon existing DP stereo matching methods by showing that while some
cost must be assigned to unmatched pixels, sensitivity to
occlusion-cost and algorithmic complexity can be significantly reduced
when highly-reliable matches, or * ground control points *, are
incorporated into the matching process. The use of ground control
points eliminates both the need for biasing the process towards a
smooth solution and the task of selecting critical prior probabilities
describing image formation. Finally, we describe how the detection of
intensity edges can be used to bias the recovered solution such that
occlusion boundaries will tend to be proposed along such edges,
reflecting the observation that occlusion boundaries usually cause
intensity discontinuities.