Abstract
In this paper, we propose a robust metric structure from motion (SfM) algorithm for an extended sequence with outliers and missing data. There are three main contributions in the proposed SfM algorithm. The first is a novel jury-based preemptive LMedS procedure to achieve efficient outlier detection. The second contribution is a new iterative two-step scheme that consists of robust estimation techniques for projective structure from motion. The third contribution is a novel algorithm for robust metric upgrade by applying the M-estimator to the traditional linear constraints for metric upgrade. In addition, comparisons of the proposed algorithm with some previous methods through experiments on simulated data are shown to demonstrate the efficiency and robustness of the proposed algorithm