Robust Global Motion Estimation with Matrix Completion
Other literature type
In this paper we address the problem of estimating the attitudes and positions of a set of cameras in an external coordinate system.
Starting from a conventional global structure-from-motion pipeline, we present some substantial advances. In order to detect outlier
relative rotations extracted from pairs of views, we improve a state-of-the-art algorithm based on cycle consistency, by introducing
cycle bases. We estimate the angular attitudes of the cameras by proposing a novel gradient descent algorithm based on low-rank
matrix completion, that naturally copes with the case of missing data. As for position recovery, we analyze an existing technique from
a theoretical point of view, providing some insights on the conditions that guarantee solvability. We provide experimental results on
both synthetic and real image sequences for which ground truth calibration is provided.