Robust Matching in an Uncertain World

Finding point correspondences which are consistent with a geometric constraint is one of the cornerstones of many computer vision problems. This is a difficult task because of spurious measurements leading to ambiguously matched points and because of uncertainty in point location. In this article we address these problems and propose a new robust algorithm that explicitly takes account of location uncertainty. We propose applications to SIFT matching and 3D data fusion.