Feature matching for object localization in the presence of uncertainty
Todd A. Cass · 2002
The author focuses on the central problem of image and model feature matching. In particular he defines a model of the geometrical uncertainty of image features, and devises a tractable algorithm for determining all feasible sets of feature correspondences given the uncertainty tolerances. A key insight into the matching problem provided by this work is that the search for a matching should be guided by analysis of (feasible) transformation space rather than the space of feature correspondences. This is because the author is only interested in maximal feasible match-sets and not the exponentially many subsets of them as found by correspondence space search.>