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.

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