Peter Meer
ERROR TOLERANT METHOD FOR
INVARIANCE BASED FEATURE CORRESPONDENCE
Abstract:A two stage probabilistic algorithm for establishing feature correspondence between images is
presented. First, k-tuples of features are matched based on similar invariant representations.
The representation should be invariant not only to the group of image transformations but also
to the permutation group of the k elements. A projective and permutation invariant representation
for 5-tuples of points/lines in a plane is described. In the second stage, the algorithm
recovers feature. correspondence from a contingency table built with the ensemble of matched
k-tuples. The conditions for reliable performance are given, and it is shown that the correct
solution for the correspondence problem can be be found while most the data in the matched
k-tuples is erroneous. The algorithm does not use global information and recovers feature
correspondence in O[n2] time.