The article considers the conforming identification of the fundamental matrix in the image matching problem. The method consists in the division of the initial overdetermined system into lesser dimensional subsystems. On these subsystems, a set of solutions is obtained, from which a subset of the most conforming solutions is defined. Then, on this subset the resulting solution is deduced. Since these subsystems are formed by all possible combinations of rows in the initial system, this method demonstrates high accuracy and stability, although it is computationally complex. A comparison with the methods of least squares, least absolute deviations, and the RANSAC method is drawn.
conforming identification; parallel algorithm; least squares method; least absolute deviations; epipolar geometry; projective geometry.
Fursov VA, Gavrilov AV, Goshin YeV, Pugachev KG. Conforming identification of the fundamental matrix in the image matching problem. Computer Optics 2017; 41(4). 559-563. DOI: 10.18287/2412-6179-2017-41-4-559-563.
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