Recovering Affine Features from Orientation- and Scale-Invariant Ones

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11361)


An approach is proposed for recovering affine correspondences (ACs) from orientation- and scale-invariant, e.g. SIFT, features. The method calculates the affine parameters consistent with a pre-estimated epipolar geometry from the point coordinates and the scales and rotations which the feature detector obtains. The closed-form solution is given as the roots of a quadratic polynomial equation, thus having two possible real candidates and fast procedure, i.e. <1 ms. It is shown, as a possible application, that using the proposed algorithm allows us to estimate a homography for every single correspondence independently. It is validated both in our synthetic environment and on publicly available real world datasets, that the proposed technique leads to accurate ACs. Also, the estimated homographies have similar accuracy to what the state-of-the-art methods obtain, but due to requiring only a single correspondence, the robust estimation, e.g. by Graph-Cut RANSAC, is an order of magnitude faster.



D. Barath acknowledges the support of the OP VVV funded project CZ.02.1.01/0.0/0.0/16_019/0000765 and that of the Hungarian Scientific Research Fund (No. OTKA/ NKFIH 120499).


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Centre for Machine PerceptionCzech Technical UniversityPragueCzech Republic
  2. 2.Machine Perception Research LaboratoryMTA SZTAKIBudapestHungary

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