ANSAC: Adaptive Non-minimal Sample and Consensus

27 Sep 2017Victor FragosoChris SweeneyPradeep SenMatthew Turk

While RANSAC-based methods are robust to incorrect image correspondences (outliers), their hypothesis generators are not robust to correct image correspondences (inliers) with positional error (noise). This slows down their convergence because hypotheses drawn from a minimal set of noisy inliers can deviate significantly from the optimal model... (read more)

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