Robust Motion Segmentation From Pairwise Matches

Federica Arrigoni, Tomas Pajdla; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 671-681

In this paper we consider the problem of motion segmentation, where only pairwise correspondences are assumed as input without prior knowledge about tracks. The problem is formulated as a two-step process. First, motion segmentation is performed on image pairs independently. Secondly, we combine independent pairwise segmentation results in a robust way into the final globally consistent segmentation. Our approach is inspired by the success of averaging methods. We demonstrate in simulated as well as in real experiments that our method is very effective in reducing the errors in the pairwise motion segmentation and can cope with large number of mismatches.