Point/line correspondence under 2D projective transformation

The projective correspondence between planar point/line sets is determined using conic invariants. In each set six (4+2) randomly chosen points/lines define two conics to which two absolute projective invariants can be associated. Similar invariant values yield six-tuples matched between the sets. The order of features on a conic is not important and thus the probability of finding a match is maximized. Feature correspondence is recovered with a dynamic programming type analysis of the contingency table derived from the ensemble of matched six-tuples. The algorithm is very sensitive to feature accuracy, raising questions about the straightforward use of conic invariants in recognition of arbitrary objects. The employed new procedures, affine invariant conic fitting to noisy data, probabilistic two-stage matching, however, are of general interest.