Title :
Correspondence of coplanar features through p2-invariant representations
Author :
Meer, Peter ; Ramakrishna, Sudhir ; Lenz, Reiner
Author_Institution :
Dept. of Electr. & Comput. Eng., Rutgers Univ., Piscataway, NJ, USA
Abstract :
The correspondence between two coplanar sets of points (or lines) is established making use of a novel invariant representation of five-tuples of features. The projective/permutation (p2) invariants are insensitive to the order of the features in the computation and thus provide a significant speedup in matching. Performance degradation due to the noise sensitivity of the invariants is avoided by using context independent constraints (noncollinearity of points, preservation of the convex hull); and by accumulating the feature correspondence hypotheses in a contingency table. Full projective correspondence can be recovered reliably for positional uncertainty of several pixels or in the presence of outliers
Keywords :
computer vision; context independent constraints; contingency table; coplanar features; feature correspondence hypotheses; full projective correspondence; noise sensitivity; outliers; p2-invariant representations; performance degradation; positional uncertainty; projective/permutation invariants; Eigenvalues and eigenfunctions; Polynomials; Scattering; Transmission line matrix methods; Uncertainty;
Conference_Titel :
Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
Conference_Location :
Jerusalem
Print_ISBN :
0-8186-6265-4
DOI :
10.1109/ICPR.1994.576256