Motion segmentation with pairwise matches and unknown number of motions

In this paper we address motion segmentation, that is the problem of clustering points in multiple images according to a number of moving objects. Two-frame correspondences are assumed as input without prior knowledge about trajectories. Our method is based on principles from “multi-model fitting” and “permutation synchronization”, and – differently from previous techniques working under the same assumptions – it can handle an unknown number of motions. The proposed approach is validated on standard datasets, showing that it can correctly estimate the number of motions while maintaining comparable or better accuracy than the state of the art.