Locally Optimized RANSAC

A new enhancement of RANSAC, the locally optimized RANSAC (LO-RANSAC), is introduced. It has been observed that, to find an optimal solution (with a given probability), the number of samples drawn in RANSAC is significantly higher than predicted from the mathematical model. This is due to the incorrect assumption, that a model with parameters computed from an outlier-free sample is consistent with all inliers. The assumption rarely holds in practice. The locally optimized RANSAC makes no new assumptions about the data, on the contrary it makes the above-mentioned assumption valid by applying local optimization to the solution estimated from the random sample. The performance of the improved RANSAC is evaluated in a number of epipolar geometry and homography estimation experiments. Compared with standard RANSAC, the speed-up achieved is two to three fold and the quality of the solution (measured by the number of inliers) is increased by 10-20%. The number of samples drawn is in good agreement with theoretical predictions.